Department of Astronomy – Stockholm University

A Photometric Variability Study Using Brown Dwarfs As Giant Planet Analogues

Investigating rotation periods and cloud structure

Master of Science Thesis

3 June 2016

Author: Simon Eriksson [email protected]

Supervisor: Markus Janson Abstract

Recent discoveries of large numbers of low- field brown dwarfs below the deuterium-burning limit, offers up a substantial sample of giant planet analogues which can be directly imaged without the severe contrast difficulties that regularly bound planets suffer from. By detecting significant periodic variability in such objects, enhanced by their lower surface-gravities, over several hours we can obtain estimates of their rotation periods. As this periodicity is possibly the result of heterogeneous cloud features in the upper atmosphere of a brown dwarf, atmospheric cloud models can then be used to discern some properties of its cloud structure. In this work we independently investigate 19 L0-L7 and 2 T2.5-T3.5 brown dwarfs with a mass-range of ∼ 6 − 22 MJup, spanning the deuterium-burning limit. We detect significant large amplitude (> 2%) sinusoidal variability of < 9.3 ± 2.0% through near-infrared observations of PSO J318.5-22. This unusually red, 6.5 MJup, giant planet analogue was observed in JS and KS at the NTT/SOFI through the ESO observing program 194.C-0827(A) by PI: Biller, B. We are able to constrain the rotation period of PSO 318, estimating a likely period of at least 7 hours. We further detect entirely new and significant (> 99% confidence) variability in 3 targets, with tentative detections in another 10, out of which 9 of are new discoveries. Our results indicate a minimum variability fraction for these targets, primarily outside the L/T transition, as high +8 as fmin = 70−12%. We conclude that very low-mass brown dwarfs, many of which show unusually red colours and signs of low-gravity, might be more likely to exhibit both greater amplitudes and frequencies of rotationally modulated variability.

ii Contents

1 Introduction 1

2 Background and Theory 3 2.1 Brown Dwarfs ...... 3 2.1.1 The Definition of BD vs. GP ...... 3 2.1.2 Observational properties ...... 4 2.1.3 Formation ...... 7 2.2 Giant Planets ...... 8 2.2.1 Observational properties ...... 8 2.2.2 Formation ...... 9 2.3 Previous Works ...... 10 2.3.1 Observational ...... 10 2.3.2 Modelling ...... 13 2.4 Summary ...... 13

3 Observations 14 3.1 NTT/SOFI ...... 17 3.1.1 Data reduction ...... 17 3.2 VLT/HAWK-I ...... 19 3.2.1 Data reduction ...... 20

4 Analysis 22 4.1 Aperture Photometry ...... 22 4.2 Light Curve Calibration ...... 26 4.3 Light Curve Analysis ...... 28 4.3.1 Polynomial subtraction ...... 28 4.3.2 Lomb-Scargle periodogram ...... 29

5 Results 30 5.1 Significantly Variable Targets ...... 31 5.2 Tentatively Variable Targets ...... 38 5.3 Non-Variable Targets ...... 45

6 Discussion 48 6.1 Implications of Binarity in the Sample ...... 48 6.2 PSO 318 ...... 49 6.3 HN Peg B ...... 51 6.4 Photometric Precision and the Reduction Process ...... 52 6.5 Frequency of Variability ...... 53 6.6 Comparisons with Previous Works ...... 53 6.7 Future Prospects ...... 55

7 Conclusions 55

References 57

A Binned light curves & finding charts of non-variable targets 61

iii B Polynomial subtraction results for tentative & non-variable targets 65

C L-S periodograms for tentative & non-variable targets 68

iv List of Figures

1 Optical spectra of SpT M7-T8 from 6800 to 8700 A...... ˚ 5 2 Radigan et al. (2014) SpT vs. 2MASS J − KS colour diagram ...... 6 3 Planet-Metallicity Correlation ...... 9 4 Biller et al. (2015) light curve for PSO 318 ...... 10 5 Radigan et al. (2012) light curves for 2M2139 ...... 11 6 Reduced light curves from Metchev et al. (2015) ...... 12 7 Colour-Magnitude diagram of our sample ...... 14 8 Single raw 60 s exposure from NTT/SOFI...... 18 9 Typical master dark frame from NTT/SOFI ...... 18 10 Typical master flat field from NTT/SOFI ...... 19 11 Illumination correction ...... 19 12 HD 106906 b close-up ...... 20 13 HD 106906 b median box filtering ...... 21 14 HD 106906 b identification ...... 22 15 Raw light curve examples ...... 23 16 HD 106906 b Standard deviation vs. Median flux ...... 24 17 PSO 318 Ks frame combination effects ...... 25 18 PSO 318 Js Nov. raw light curves ...... 25 19 Calibrated light curve of CB reference ...... 26 20 Binned light curve of CB reference star ...... 27 21 Polynomial subtraction of the CB reference star ...... 29 22 Simulated sinusoidal data ...... 29 23 Lomb-Scargle periodogram of simulated data ...... 29 24 Lomb-Scargle periodogram for the CB reference star ...... 30 25 PSO 318 JS Oct. binned light curves & finding chart ...... 31 26 PSO 318 JS Nov. binned light curves & finding chart ...... 32 27 Polynomial subtraction results for PSO 318 JS Oct, Nov...... 33 28 PSO 318 KS Nov. binned light curves & finding chart ...... 33 29 Polynomial subtraction result for PSO 318 KS Nov...... 34 30 Lomb-Scargle periodograms for PSO 318 ...... 34 31 2M0045 binned light curves & finding chart ...... 35 32 Polynomial subtraction result for 2M0045...... 35 33 2M0117 binned light curves & finding chart ...... 36 34 2M0501 binned light curves & finding chart ...... 37 35 Polynomial subtraction results for 2M0117 and 2M0501...... 37 36 Lomb-Scargle periodograms for 2M0045, 2M0117 and 2M0501 ...... 38 37 2M0303 binned light curves & finding chart ...... 40 38 2M0326 binned light curves & finding chart ...... 41 39 2M0342 binned light curves & finding chart ...... 41 40 2M0355 binned light curves & finding chart ...... 42 41 2M0421 binned light curves & finding chart ...... 42 42 2M0536 binned light curves & finding chart ...... 43 43 2M2224 binned light curves & finding chart ...... 43 44 GU Psc b binned light curves & finding chart ...... 44 45 HN Peg B binned light curves & finding chart ...... 44 46 SIMP2154 binned light curves & finding chart ...... 45 47 HD 106906 b and control star comparison ...... 46

v 48 Model fitting for PSO 318 by B15 ...... 50 49 November 2014 light curve for PSO 318 by B15 ...... 52 50 SpT vs. J-KS diagram ...... 54 51 2M0103 binned light curves & finding chart ...... 61 52 2M0234 binned light curves & finding chart ...... 61 53 2M0323 binned light curves & finding chart ...... 62 54 2M0357 binned light curves & finding chart ...... 62 55 2M0518 binned light curves & finding chart ...... 63 56 2M2322 binned light curves & finding chart ...... 63 57 HD 106906 b binned light curves & finding chart ...... 64 58 2M0045 - Example with all RS ...... 64 59 Polynomial subtraction plots I ...... 65 60 Polynomial subtraction plots II ...... 66 61 Polynomial subtraction plots III ...... 67 62 Lomb-Scargle periodograms I ...... 68 63 Lomb-Scargle periodograms II ...... 69

List of Tables

1 SOFI observations ...... 15 2 HAWK-I observations ...... 15 3 Field object properties ...... 16 4 Companion object properties ...... 16 5 Detections of Variability ...... 47

vi 1 Introduction - 1 - Section 1.0

1 Introduction technology allows. The detection method used for the Kepler mis- In this thesis project we investigate 21 directly im- sion focuses on photometric observations of plane- aged low-mass brown dwarfs (BD’s) for periodical tary transits in front of their host (e.g. Char- photometric variability. With a mass-range of 6-22 bonneau et al. 2007), producing light curves with Jupiter- (MJup) and with the majority at a clearly distinguishable drop in intensity which or just below the deuterium burning (DB) mass- can be analysed to obtain constraints on planetary limit of ∼ 13 MJup (Spiegel et al. 2011), these radius and parameters such as and objects can be treated as free-floating giant planet eccentricity. Due to the principles of this method (GP) analogues (Chabrier et al. 2014). For the it works best on systems viewed near edge-on, and sake of context however, before we get to the more has a bias for detecting planets with short periods detailed section of Background and Theory (§2), around cool stars. This naturally leads to large in- we first present a brief overview concerning recent completeness effects when considering the full pop- advances made and techniques used in extrasolar ulation of extrasolar planets. planet, or , research. To confirm candidates discovered by Kepler as , and to obtain mass limits, one gen- It has now been over two decades since the first erally looks to spectroscopic radial velocity (RV) exoplanet was discovered around the millisecond measurements of candidate host stars, searching pulsar PSR B1257+12 (Wolszczan & Frail 1992), for a Doppler shift arising due to orbital move- using pulsar timing variations. The fact that the ment around a common center of gravity (e.g. host star of this planet, being a rapidly rotating Plavchan et al. 2015). Like the transit method, neutron star, was as far from a ”normal” star as RV measurements are biased towards planets on one can imagine, seems in hindsight to have been tight orbits and more massive planets such as gas a very fitting omen of just how fantastically differ- giants (or ”hot Jupiters”). ent and diverse the stellar environments of planets and star systems other than our own would turn There are several other methods that can be out to be. The first bonafide exoplanet orbiting a used such as astrometry, polarimetry, other tim- main-sequence star was detected around 51 Pegasi ing methods and gravitational microlensing, but a few years later (Mayor & Queloz 1995) and by we will move on to discussing the one most rele- the end of the decade dozens of worlds had been vant for this work – direct imaging of exoplanets. discovered. As the name implies, the aim of this method is to The torrent of discoveries did not abate, but ac- image the target directly which in the case of ex- celerated with missions like CoRoT (Auvergne et oplanets is an extremely challenging prospect due al. 2009) in 2006 and the start of the unimagin- to the extreme contrast difference between a planet ably successful Kepler mission in 2009 (Koch et and its host star. al. 2010), which despite severe setbacks continues Earlier missions focused on space-based tele- to this day to provide us with an ever increasing scopes for very good reasons. The Earth’s sample of planet candidates. Confirmed planets atmosphere not only blocks several interesting from the Kepler data range in mass from several wavelength-regions, but it also distorts the path MJup down to Earth-mass planets and number al- of photons that manage to reach us. The result is most 2000, with over 5000 remaining candidates an unavoidable smearing (seeing) effect on obser- (Mullally et al. 2015). With the resounding suc- vations by any ground-based telescopes, which lim- cess of these early missions the field of exoplane- its resolution and photometric precision. With the tary science exploded and is still expanding rapidly introduction of adaptive optics (AO; e.g. Davies with an ever increasing diversity, investigating ev- & Kasper 2012, Males et al. 2014) and further ery aspect of planetary formation, evolution, com- improvement of these systems (Extreme AO; e.g. position and habitability that current methods and Jovanovic et al. 2015), the quality of ground- 1 Introduction - 2 - Section 1.0 based observations can start to approach parity troscopy, and while not central to this project it with space-based telescopes. The 39.3 m diame- is vital for the classification of BD’s and under- ter European Extremely Large Telescope (E-ELT) standing their evolution using spectral features. has the potential to revolutionize the search for and Obtaining spectra of exoplanets is inherently dif- study of terrestrial-sized exoplanets, and would not ficult, given the problems of achieving high con- be feasible without this technology. trast and precision. The James Webb Space Tele- The first exoplanet detection using direct imag- scope (JWST) has the potential to drastically ing can be attributed to Chauvin et al. (2005), improve the prospects for transit spectroscopy who detected the ∼ 5 MJup giant planet of terrestrial-sized worlds and characterization of orbiting a ∼ 25 MJup BD at a distance of 55 AU. their atmospheres (e.g. Barstow et al. 2016, Whether or not an object like 2M1207b actually Greene et al. 2016). qualifies as an exoplanet is a discussion for §2. For faint low-mass objects such as the planets 2M1207b is also of interest since Zhou et al. (2016) around HR 8799, field BD’s or GP’s with sepa- recently discovered that it displays low-amplitude rations of 100’s of AU, direct spectroscopy is cer- (∼ 1%) peak-to-peak variability with a rotational tainly possible with many ground-based telescopes. modulation, most likely caused by heterogeneous While excellent spectra have been obtained of the cloud features. planets in the HR 8799 system and the number of It should come as no surprise that an object like directly imaged exoplanets is increasing, at present 2M1207b was the first to be directly imaged, since only around twenty have been observed (e.g. Kalas it is a strong infrared emitter (Teff ∼ 1250 K) orbit- et al. 2008, Lagrange et al. 2010, Kraus & Ireland ing a relatively faint companion/host, allowing for 2012, Kuzuhara et al. 2013, Liu et al. 2013 – PSO high-contrast imaging without the use of a corona- J318.5-22, Rameau et al. 2013) graph that blocks out the light of a host star. Simi- larly, using the method on field BD’s or BD’s/GP’s The Wide-field Infrared Survey Explorer (WISE; with extreme separations from their companions Wright et al. 2010), still going after more than six or host stars has proven very successful, as this years, has so far discovered hundreds of low-mass project is another example of. BD’s in the Solar neighbourhood, with many of Around main-sequence stars, direct imaging is these below the DB-limit. As research into star, biased towards planets with wide orbits, as con- BD and GP formation continues it is becoming in- trast improves with distance from the star. The creasingly likely that BD and GP formation and method also has the potential to reveal multiple evolution have a lot in common (Chabrier et al. planets at once, as was the case with the 1.47 2014). If this is indeed the case, and similar-mass Solar-mass (M ) star HR 8799 where Marois et al. GP’s and BD’s are not that dissimilar, the WISE (2008) presented multi-epoch high-contrast obser- survey results offers up a vast amount of giant vations from the Very Large Telescope (VLT) of planet analogues that can be directly imaged and three planets, 5-13 MJup, orbiting the star with a analysed without the headaches associated with top-down perspective. This system was later ex- the direct imaging of exoplanets. panded to include the discovery of a fourth planet While there has been extensive research into on an inner orbit, with recent observations possi- BD’s in general by looking for photometric vari- bly indicating a fifth (Booth et al. 2016). Further ability (e.g. Apai et al. 2013, Biller et al. 2013, observations of these planets were later used by Buenzli et al. 2014, Metchev et al. 2015, Marley Madhusudhan et al. (2011) as a testing bed for & Robinson 2015, Radigan et al. 2012), until one their atmospheric models for massive gas giants, a week before the start of this project no photomet- set of models that we will be using and exploring ric variability studies had been published for BD’s further in Discussion (§6). close to the DB-limit. So while the technique it- self is not new, the substantial sample offered by Closely linked with direct imaging is spec- WISE allows for a new leap in its application. 2 Background and Theory - 3 - Section 2.1

Photometric variability studies of these lower- 10−100 Myr and located at a distance of ∼ 10−60 mass objects would therefore allow us to parsec (pc) (Gagn´eet al. 2014a). The age estima- tions of BD’s are generally obtained by looking at 1. constrain their rotation periods and compare their motion in space, i.e. determining their radial with estimates obtained from radial velocity velocities and assigning them to stellar associations measurements. Better statistics on rotation or moving groups with objects that exhibit similar periods across a broad range of masses could motion (e.g. Ducourant et al. 2014). The ages aid in the understanding of how it relates to of these associations can be estimated by the use the age of these objects and their formation of e.g. stellar models and theories of star forma- and evolution. tion or kinematic analysis (tracing motions back in time). These young objects are intrinsically very 2. aid the development of atmospheric models hot as they are still in the process of gravitationally and through these improve our understanding contracting, and as a result emit strongly in the in- of the evolution and structure of GP atmo- frared (IR). In general, this provides the observer spheres. with a natural high-contrast condition, improv- 3. make comparisons to the extensive literature ing the possibility to observe such objects closer that exists for photometric variability research to their host stars (e.g. Oppenheimer & Hinkley done for more massive BD’s and look for cor- 2009) than would be possible for older and cooler relations in e.g. lower surface gravity. objects. As the targets in this work are reasonably close to us in space, they are relatively bright with 4. improve the methodology so it can be applied apparent J-band magnitudes of ∼ 14 − 17 mag. with higher precision to even lower-mass ob- Before we move on, we need to decide how to jects and GP’s. tackle a somewhat controversial issue, namely one of definition. As the technique becomes more widely applied and refined, it paves the way for potential future ap- plications to Earth-sized exoplanets, where pho- 2.1 Brown Dwarfs tometric variability could map cloud structures 2.1.1 The Definition of BD vs. GP or even the shape of continents and oceans (e.g. Kawahara & Fujii 2011). As such it could prove to When discussing BD’s and GP’s in this context, be a powerful tool in the expanding toolbox that one must first establish a definition that distin- we need to finally answer Humanity’s ever-present guishes between the two. Unfortunately this is not question about life on other worlds. a simple task, and any attempts at a strict defi- Next, Background and Theory (§2) goes into nition is often highly controversial, even more so more detail concerning previous studies of BD’s, considering the increasing number of discoveries of their formation, evolution and connection to GP’s. BD’s well below the DB-limit (e.g. Chauvin et al. Observations (§3) and follows thereafter detailing 2005, Todorov et al. 2010, Delorme et al. 2012). the data sets, their reduction and continuing with Distinguishing between a star and a BD is more the Analysis (§4). The outcomes of which are then straight-forward, with the natural hard cut-off presented in Results (§5). Finally we end with the point between the two being a core temperature Discussion (§6) and Conclusions (§7). high enough to initiate hydrogen-burning (HB). Since core temperature is tied to stellar mass, this 2 Background and Theory gives us a HB minimum-mass for stars of ∼ 0.075 M or ∼ 80 MJup (e.g. Chabrier et al. 2000). There is one trait common to all of the targets The ”classical” definition used by the Interna- investigated in this work, which is that the vast tional Astronomical Union (IAU) states that if the majority are very young objects, with ages of ∼ object is above the DB-limit (∼ 13 MJup) but be- 2 Background and Theory - 4 - Section 2.1 low the hydrogen fusion limit it is classified as a As the effective temperature decreases, the con- BD. This definition seemed reasonable at a time ditions and chemistry in the atmosphere changes, when our knowledge of BD’s and GP’s outside leading to different atoms and molecules being our was limited, but with recent ad- favoured over others, which in turn leads to sed- vancements in astronomy, this limit appears un- imentation into clouds (e.g. Marley et al. 2002). necessarily arbitrary and confusing. To account for As such, the observational properties of BD’s can free-floating objects below the DB-limit, the term change drastically during their evolution, and be- planetary-mass object (PMO, planemo) is some- ing able to differentiate between them becomes a times used. Rather than perpetuating this defini- necessity. tion we choose to follow a different one. Chabrier et al. (2014), henceforth C14, argue The primary classification of BD’s is made by this point extensively, as they detail the observa- assigning them a spectral type (SpT) in a similar tional properties of BD’s and GP’s, their formation way as is done for stars, which are classified as SpT and evolution. Their classification, which we feel O B A F G K M. As a first step, this represents is more suitable for this work, states the following. a relatively simple way of ensuring that the object BD’s denominates any you are looking at is not a regular star or . The last type in the traditional classification, M, 1. free-floating object below the HB minimum- primarily contains red dwarfs, giants and super- mass, irrespective of it being above or below giants but also hosts young and hot BD’s at around the DB-limit. ∼M6. As the number of BD detections increased as 2. objects that are companions to a host star or observations improved, additional spectral classes another BD, and exhibit properties consistent needed to be defined to include (the fainter) cooler with that of a gaseous sphere with a global and older objects of lower mass. Kirkpatrick et chemical composition similar to the host star al. (1999) and Kirkpatrick (2005) introduced the or BD. two SpT’s L and T, and detailed optical spectra showing the transition from late-M to late-T can The last point is especially important as chem- be seen below in Figure (1), illustrating how the ical composition is affected by the mechanism be- spectral features evolve. Finally, for the ultra-cool hind the formation of the object, as we will see dwarfs discovered by WISE there is the class Y later on in this section. In short, this definition (Cushing et al. 2011). The stellar SpT sequence separates BD’s and GP’s depending on the way can also be thought of as a temperature sequence, they formed, rather than an arbitrary line at the with temperatures increasing from M to O. The DB-limit. same holds overall for T to L, except in the tran- While this is not by any means a final or perfect sition region between the two, from mid-/late-L definition, and becomes ambiguous for e.g. ob- to mid-T – also known as the L/T transition. As jects with very wide separations from their com- we will see later, it is in this spectral region where panion/host or when considering ejected/scattered clouds in the photosphere are expected to play a planets, it does offer an overlap between the two significant role in influencing the spectral and pho- object classes which does not exist under the IAU tometric appearance of BD’s. definition. We will return to C14 as we continue our discussion on BD formation later on. In addition to the optical SpT, which is mainly affected by temperature, there is also a near- 2.1.2 Observational properties infrared (NIR) SpT for BD’s which is more affected Since BD’s by definition lack a persistent internal by clouds, surface gravity and metallicity (e.g. Mc- energy source, they slowly cool over time as they Govern et al. 2004, Kirkpatrick 2006, Burgasser et radiate away the energy they obtained during for- al. 2008, Cushing et al. 2008, Bonnefoy et al. mation and subsequent gravitational contraction. 2014, Schmidt et al. 2014). 2 Background and Theory - 5 - Section 2.1

Figure 1: Optical spectra of SpT M7-T8 from 6800 to 8700 A˚ (Kirkpatrick 2005).

Since surface-gravity in particular is thought to = 1.25 µm, λmean, H = 1.63 µm and λmean, K = 2.19 have a large impact on the formation of conden- µm respectively. There are further variations to sate clouds that strongly affect the observational these, such as having a shorter wavelength range properties of BD’s, the classification of the L and with a similar midpoint, e.g. JS and KS which T SpT’s was expanded to include a suffix denoting are filters used for the majority of the observa- the surface-gravity (Cruz et al. 2009). Normal tions analysed in this work. As the 2MASS survey gravity is indicated by α or a lack of suffix, β for (Skrutskie et al. 2006) provided vast catalogues intermediate-gravity and γ for very-low gravity of photometric data in J, H and Ks, the colour (log(g) ∼ 4). Allers & Liu (2013) arrive at a sim- J −KS is often used in combination with the L and ilar classification, but the use of the greek suffix T SpT’s when discussing the observational proper- seems to have caught on. Kirkpatrick (2006) also ties of BD’s, with an increasing value representing suggests a suffix be used for metallicity, but as a reddening of the object. that has not been relevant for the objects studied in this work, we will not go into it any further. For L-dwarfs become progressively redder with de- more details on the specifics of spectral features, creasing effective temperature (Teff), down to a effective temperatures and luminosity the review SpT of around L7 where there is a drastic shift by Luhman (2012) is recommended. towards bluer colours, which represents the start of the so called L/T transition (∼L7-T4). Seek- ing to investigate which physical parameters pro- Since the cooler L and T BD’s are generally too vide the strongest influence on the observed colour, faint in the optical, most observations are done in Stephens et al. (2009) conducted a detailed study the NIR bands of J, H and K. Typical wavelength on an assortment of early- to mid-L and T dwarfs midpoints for these bands are (e.g. ESO) λmean, J (L3.5-T5.5) and used a range of atmospheric mod- 2 Background and Theory - 6 - Section 2.1 els to create synthetic spectra to compare with ob- on surface-gravity, so therefore lower-mass BD’s servations. They find that the L/T transition be- ought to stay redder at even lower temperatures. tween L7-T4 corresponds to a Teff between 1400 They acknowledge that the models are compara- K to 1100 K, which represents a relatively small tively simple compared to the full hydrodynamical change in temperature over a wide range of SpT’s, simulations that would be ideal, but still manage a similar result to that obtained by Saumon & to recreate the observed spectra with good accu- Marley (2008). The colour difference is then not racy. specifically temperature dependant, but rather the Further works since this study have reinforced result of a change in cloud opacity in the upper these assertions (e.g. Marley et al. 2010, Morley atmosphere, so that less cloudy atmospheres are et al. 2014) and as we will see towards the end bluer (see also e.g. Cushing et al. 2008). By of this section, numerous observational works fo- varying the grain sedimentation in the atmosphere cusing on photometric variability support the idea they could recreate the change in SpT’s over the that the changing spectral features over the L/T L/T transition while keeping Teff constant. The transition is primarily caused by changes in cloud dramatic shift towards bluer colours is therefore opacity, which is influenced by surface-gravity. A thought to be caused by a more rapid sedimenta- diagram from Radigan et al. (2014) that illustrates tion of these condensate clouds to a region below the L/T transition in a helpful manner can be seen the photosphere, creating a cloud-free atmosphere below in Figure (2), and we will return to this when after SpT ∼T4. Additionally their results sug- discussing Previous Works (§2.3). gest that this rate of sedimentation is dependent

Figure 2: SpT vs. 2MASS J − KS colour diagram from Radigan et al. (2014). Grey points represent known field L and T dwarfs. Purple circles indicate detection of variability, and the L/T transition is indicated by the dashed ellipse. 2 Background and Theory - 7 - Section 2.1

2.1.3 Formation definitive answer eventually.

There are several theories concerning the forma- Regardless of the fundamental mechanisms be- tion of BD’s (e.g. Whitworth et al. 2007), and hind BD formation, all scenarios naturally include while none of them exclude any of the others, there some way of limiting the final mass, to prevent the are some that are likely to be more dominant. Here formation of a low-mass star rather than a BD. we will briefly discuss these formation scenarios, This is either inherent in the formation scenario or one of which is shared with GP’s as a possible for- included as an environmental factor as a means of mation mechanism, and the Initial Mass Function halting accretion. (IMF, e.g. Bonnell et al. 2007, Offner et al. 2014) Bonnell et al. (2008) investigated, through nu- for BD’s. For a more in-depth exploration of the merical simulations, the issue of whether or not formation scenarios of BD’s and GP’s we also rec- it should be possible for BD’s to form via gravi- ommend e.g. Chabrier et al. (2014, i.e. C14), and tational fragmentation in the same way as stars. Luhman (2012, henceforth L12) for a more general They conclude that both BD’s and low-mass stars review on the IMF and formation of low-mass stars can form from the fragmentation of high-density and BD’s. gas in a stellar cluster, even if they are in the mi- In the first hundred BD’s discovered by WISE nority. In their simulations, the mechanism pre- (Kirkpatrick 2011), the vast majority of them were venting further accretion for BD’s is the strong cold ≥ T6 dwarfs, too faint to be have been found tidal shear of the cluster combined with the fact previously. With WISE, BD’s had now been ob- that its gravitational potential imparts high veloc- served all the way down to very-low masses (∼ 5 ities to the fragments. MJup) and the question about whether or not the An alternative way of halting accretion is the regular stellar IMF could extend down to such low ejection of the BD core-fragments out of the masses became even more relevant – i.e what is cluster through dynamical interactions. This the minimum mass of the IMF? C14 argue that accretion-ejection scenario was originally proposed the recent WISE discoveries agree well with the by Reipurth & Clarke (2001), with subsequent IMF proposed by Chabrier (2005, see also 2001 simulations done by e.g. Bate (2009, 2012). & 2002), and find no strong arguments as to why C14 argues extensively as to why this is likely BD’s should not share the same underlying IMF not the dominant formation mechanism for BD’s. as stars. They list numerous properties that seem Two main points of the argument being that 1) to be shared by young stars and BD’s, indicating accretion-ejection would not work for low-density a close connection in regards to their formation. environments where dynamical interaction is not A consequence of this argument is that they strong enough, and that 2) observed average dis- should then be formed predominantly by a similar persion velocities of prestellar cores are low enough mechanism – e.g. gravitational compression and to suggest that no substantial dynamical evolution fragmentation (Hartmann 2002). This has been takes place at that stage. suggested in other works as well, such as Scholz A fairly situational halting mechanism includes et al. (2012) who observed very low-mass objects the idea that photoionization from close-by O,B in a young and estimated a minimum stars are responsible for preventing further accre- mass of at least 6 MJup. L12 does not come down tion on the prestellar cores (Whitworth & Zin- strongly in favour of any particular resolution to necker 2004). However, the BD mass-function re- the question of a shared IMF between BD’s and mains the same for clusters with or without these stars, but rather discusses the IMF in general, stars and the fact that BD’s also form in isolated as observed in the Solar neighbourhood, Galactic environments suggests that this is not a dominant disk and young clusters. Both L12 and C14 agree mechanism (C14). however, that the continuously improved statistics Concluding the BD-specific formation scenarios from the WISE data has the potential to give a is the one of turbulent fragmentation (Padoan & 2 Background and Theory - 8 - Section 2.2

Nordlund 2002, 2004). Instead of primarily be- stabilities play in the formation of BD’s and GP’s, ing driven by gravity, fragmentation is induced by and C14 considers the contribution of GI to their large-scale turbulence that propagates down the overall formation to be limited, it should become hierarchy of the molecular cloud to smaller scales. more evident in the coming years. C14 comes down in favour of this ”gravoturbulent fragmentation” as the dominant formation mech- 2.2 Giant Planets anism and while not excluding the other potential scenarios, argue that this agrees the best with cur- 2.2.1 Observational properties rent observations. Unlike BD’s, where one often has to rely on mass The final scenario, disk instability/fragmenta- estimates being derived from models that in turn tion, is one shared between both GP’s and BD’s. use e.g. age estimates and observed bolomet- The physics and conditions behind disk instabili- ric luminosity as parameters, we can determine ties in protostellar or protoplanetary disks are de- both mass and radius accurately for many GP’s. tailed further in §4 in C14. The methods used in these observations were dis- Originally formulated by Kuiper (1951), it pri- cussed previously, namely radius measurements marily gained traction over the past two decades from transits and mass estimates from RV, and as a way of explaining GP’s located at wide- one or the other are applicable to many GP’s, as- separations from their host stars (Boss 1997). Cen- suming they are relatively close to their host stars. tral to the theory is that disks are expected to be There are however some complications that ex- gravitationally unstable during the early stages of ist specifically for observing short-period GP’s that star formation, with massive disks being especially have been given the nickname hot Jupiters, or in- prone to gravitational instabilities (GI). This is un- flated hot Jupiters (e.g. Laughlin et al. 2011, likely to happen in the inner part of the disk, due Lopez & Fortney 2016). While both young GP’s to conditions required for cooling, but could occur and BD’s will be naturally inflated due to still be- further out, leading to partial fragmentation in the ing in the process of gravitationally contracting, disk, a part of which in turn collapses into a clump hot Jupiters are generally billions of years old but that can contract into a GP. Whether such an ob- appear to have radii as large as ∼ 2RJup, nearly ject will survive or not (e.g. Boss 2005, Galvagni twice the typical radius for an older GP. They re- & Mayer 2014), due to migrating into the star or main a curious anomaly as no real consensus on being disrupted in the disk, is still very much up the exact underlying mechanic of inflation has been for debate (e.g. Helled et al. 2014). reached, other than that it is closely connected to As has been discussed earlier, direct imag- how much irradiance the planet receives from the ing is especially well-suited for observing wide- host star. separation companions after formation, and the ex- The work of Santerne et al. (2016) offers an tremely high-resolution observations possible with excellent and detailed view of the process of con- the recently completed ALMA radio telescope of- firming and characterizing the properties of GP’s, fers the ability to observe a disk during the forma- and as such we refer the reader to their work for a tion stages (e.g. Douglas et al. 2013, Dipierro et view at an in-depth analysis. al. 2014). Janson et al. (2011) observed nearby B & A stars, which are thought to have the most In addition the various physical properties of massive disks and therefore the most prone to GI, GP’s that one seeks to determine, there is a vi- and found that their number of wide companion tal and more fundamental relation connecting the detections fell far short of that predicted by mod- formation of GP’s with their stars – the Planet- els, indicating that disk fragmentation is likely not Metallicity correlation (Santos et al. 2004, Fischer the dominant formation mechanism. & Valenti 2005). Formulated by Fischer & Valenti So while it is still unclear how big a role disk in- (2005) as a result of an extensive spectral analysis 2 Background and Theory - 9 - Section 2.2 of 850 FGK-type stars where Doppler observations presented their case for CA as a formation me- were also available, it correlates planet abundance chanic that could help explain why the Solar sys- with the metallicity of the host star. Metallicity tem gas giants had a different proportion of ele- (Z) refers to the fraction of elements heavier than ments compared to the , and how such gas gi- Helium (i.e. ”metals”) compared to Hydrogen, and ants would have had time to form before the gas for this relation the fraction is typically expressed dissipates from the protoplanetary disk. We will as the logarithmic value [Fe/H], where [Fe/H] = 0 here focus on the overall mechanics, and direct the is Solar metallicity and [Fe/H] = -1 a tenth of that. reader to C14 who present an in-depth discussion In their analysis, they find a strong correlation on CA, and specifically the issue of how GP’s can between the iron abundance in the host star and form fast enough while there is still gas to accrete, the probability of finding a GP orbiting it (see Fig- an issue that so far has not been entirely resolved. ure 3 below) and are able to fit a power-law to this CA for GP’s is essentially a two-stage bottom- relation using finer binning of the data. up process, where the first stage is the accre- tion of planetesimals, similar to the formation of terrestrial-mass planets. For GP’s however, the accretion continues to a critical point (∼ 10 Earth-masses, M⊕) where gas can now be accreted from the disk and retained (stage two) in an en- velope around the core. At this point the mass of the envelope increases faster than the core, lead- ing to a continued rapid gas accretion. The first stage would therefore be the primary reason for the difference in relative composition between the star and the GP, as it naturally leads to a higher concentration of heavier elements compared to a collapse scenario where both star and GP form Figure 3: The Planet-Metallicity correlation as from the same nebular gas. found by Fischer & Valenti (2005), indicating a clear increase in the percentage of stars hosting This mechanism provides an elegant explanation massive planets with increasing iron abundance. for the observed planet-metallicity correlation for GP’s, and why there seems to be no such correla- Since their findings were published there has tion for the probability of finding terrestrial-mass been continued research (e.g. Johnson et al. 2010, planets. The greater the abundance of heavy ele- Miller & Fortney 2011, Thorngren et al. 2015) ments in the nebular gas, the easier it is to form into this correlation and its importance in differ- cores massive enough to start accreting gas, and ent applications in regards to exoplanets. For our if the metallicity is substantially lower, the critical purposes we will focus on its relevance for the for- mass might not be attainable and GP formation mation of GP’s specifically, and will continue dis- becomes highly unlikely. cussing it in the next section. Johnson et al. (2010) analysed 1266 stars in a mass range of 0.2 < M < 1.9 and concluded that, 2.2.2 Formation in addition to again verifying the correlation, GP occurrence also seems to increase with the stellar There are predominantly two formation mechan- mass. This could be seen to favour GI, as we pre- ics to consider for GP’s – core accretion (CA) and viously discussed that more massive stars can host gravitational/disk-instability, with the latter being larger disks and thus be more prone to GI, but discussed previously in §2.1.3. Backed up by exten- as Johnson et al. (2010) argues, GI is supposed sive numerical simulations, Pollack et al. (1996) to have no environmental dependence, so there- 2 Background and Theory - 10 - Section 2.3 fore GP’s should be prevalent even among low- published the results of their observations of PSO metallicity stars. J318.5338-22.8603 (Liu et al. 2013, also 2MASS Thorngren et al. (2015) study 38 transiting GP’s J21140802-2251358, hereafter PSO 318), a free- and find a clear correlation between the heavy ele- floating ∼7 MJup BD which showed clear signs of ment mass of a√ planet (MZ ) and the total mass M, significant variability (> 10 ± 1.3%), that evolved so that MZ ∝ M. In addition to finding further over multiple observations (Figure 4). support for CA, they also suggest that the ma- jority of the heavy elements should be present in the gaseous envelope of the planet, and not exclu- sively in the core. If this is the case for GP’s, they should exhibit enriched atmospheres compared to BD’s, and as such enable a distinction between the two to be made based on atmospheric com- position. This is explored in their work as they compare the less massive HAT-P-20b (7.2 MJup) to Kepler-75b (10.1 MJup), where the former shows a substantially greater enrichment than the latter, from which one could suppose that they formed by different mechanisms. So to conclude, there does seem to be substantial evidence in the literature discussed here and else- Figure 4: Final reduced light curves for PSO 318 where that CA is the dominant formation mecha- and reference stars from Biller et al. (2015), show- nism rather than GI, and that it seems likely that a ing a peak-to-peak amplitude of > 10% with a pe- definitive answer to the question could be found in riod of at least 5 hours. the coming years. Combined with the fact that there should be observable compositional differ- ences between BD’s and GP’s due to the enrich- These observations were part of a larger ob- ment as a result of CA, we should also see more serving programme of over 20 low-mass BD’s, the arguments being made for a less arbitrary distinc- data of which was publicly released as this project tion between the two objects. started. This data set has been the primary focus of our work, as it represents the latest and most extensive source of photometric variability data 2.3 Previous Works for low-mass BD’s, and will be explored further in In this section we present an overview of the obser- Observations (§3). vational and modelling works that have been done recently in regards photometric variability studies Early efforts on studying variability in BD’s of BD’s. focused on optical (I-band) observations of late- M or early-L dwarfs (e.g. Bailer-Jones & Mundt 2.3.1 Observational 2001, Gelino et al. 2002, Enoch et al. 2003) and found amplitudes of a few percent, conclud- At the inception of this project there were no pub- ing that they were most likely caused by either lished detections of photometric variability in very inhomogeneous cloud coverage, but that magnetic low-mass objects below the DB-limit that could spots, although assumed to be increasingly rare in be thought of as GP analogues, and the extensive ultra-cool dwarfs, could be another source. Con- work that had been done was for more massive trary to more recent studies, Enoch et al. (2003) BD’s. found no increased variability fraction in the L/T Shortly after our work began, Biller et al. (2015) transition. Following this, there was not much 2 Background and Theory - 11 - Section 2.3 progress in terms of new detections until Clarke that the rotationally modulated variability is de- et al. (2008) found < 4% variability in a number pendant on wavelength, which indicates an atmo- of L7-T6 BD’s and Artigau et al. (2009) detected spheric origin. multi-wavelength variability at 10σ in their pre- They rule out the possibility of a binary system viously discovered L/T transition BD SIMP0136 giving rise to the variability and conclude that the (T2.5). This detection set it apart from previous evolution of the light curve over a four-month pe- studies, particularly in terms of the precision of riod strongly indicates that it is caused by atmo- the observations, and was soon followed by many spheric changes. Through modelling, and given more surveys presenting high-precision photome- that L/T transition BD’s are expected to have try. patchy clouds due to their spectral evolution in this region, they also argue in favour of heterogeneous With their multi-wavelength observations of the clouds rather than magnetically induced spots as BD 2MASS J21392676+0220226 (2M2139), Radi- the underlying cause. In short, their work provided gan et al. (2012) advanced the field in a number of further critical empirical results that back up the ways, and their exhaustive analysis illustrates a far hypothesis of fragmenting clouds being primarily more detailed application of modelling than what responsible for the spectral changes observed dur- has been possible for this work. ing the L/T transition. 2M2139 became the second L/T transition BD to show significant variability and still holds the Continuing their work with the largest survey record as the most variable BD discovered thus yet, Radigan et al. (2014) looked at 62 L4-T9 BD’s far. The first four days of multi-wavelength ob- for photometric variability and a summary of their servations, seen in Figure (5), also clearly indicate detections could be seen previously in Figure (2).

Figure 5: The reduced multi-wavelength light curves for 2M2139, with reference stars in the panel below, showing a peak-to-peak amplitude of up to 26% in the J-band with a period of 7.72 hours if the light curve has a single peak (Radigan et al. 2012). 2 Background and Theory - 12 - Section 2.3

Buenzli et al. (2015a, 2015b) used the Hubble Taking different inclinations into consideration, Space Telescope (HST) to observe the closest BD they conclude that essentially all L dwarfs should binary system Luhman 16AB, searching for photo- have spots and exhibit some variability. In com- metric variability and found significant amplitudes paring with other surveys (Radigan et al. 2014, (4.5 and 9.3%) for both components (L7.5/T0.5). Buenzli et al. 2014), their results suggests that This result is particularly surprising as while Radi- variability in L/T transition BD’s, while ubiqui- gan et al. (2014) found that most L/T transition tous, is not as prominent at the Spitzer IRAC BD’s are weakly variable at the percent level, it wavelengths (approximately L- and M-bands) as seems unusual to find two strongly variable BD’s it is for the shorter J, H and K bands. This lends in the same system, which could indicate that they further credence to the idea that cloud structures both have common, and as of yet unclear, proper- are responsible for this type of variability, and that ties that favour variability. different wavelengths are sensitive to changes in Metchev et al. (2015) present an extensive different layers of the atmosphere. Furthermore space-based survey of 44 L3-T8 BD’s with both they suggest that their data could also be used in unparalleled photometric precision and duration of the Doppler imaging of clouds/surface features, an the time-series data, using the Spitzer Space Tele- interesting technique utilized by Crossfield (2014) scope. They find that the vast majority (∼ 80%) for Luhman 16B, revealing a patchy photosphere. of L dwarfs are variable by ≥ 0.2% and that ∼ 36% In addition to the works discussed above, there of T dwarfs vary by ≥ 0.4%. The light curves of are several others focused on observations of L/T some of these shown below in Figure (6), and take transition BD’s, such as Buenzli et al. (2012), note of the light curve for HN Peg B (right panel), Biller et al. (2013), Apai et al. (2013) and Radigan as we will return to it later in our own analysis. (2014).

Figure 6: Reduced light curves from Metchev et al. (2015) of 11 (out of 21) variable L and T BD’s, displaying Spitzer IRAC data [3.6 µm] (filled symbols) and [4.5 µm] (open symbols), including fitted curves. For future reference (§5), make note of the long-period and weakly variable HN Peg B light curve. 2 Background and Theory - 13 - Section 2.4

Next, we move on to mention some of the var- In short, the former suggests that new models that ious atmospheric modelling efforts that are trying deal specifically with the thick cloudy atmospheres to put limits on the atmospheric conditions that of the HR 8799 planets are required, while the lat- could be responsible for the variability observed in ter argues against the need for such a new class L/T transition BD’s. of models. However both are able to reproduce the observed spectra, and for further application 2.3.2 Modelling of the models by Madhusudhan et al. (2011) see Skemer et al. (2014), where they are applied to the While this work is primarily focused on observa- HR 8799 system and 2M1207b. For the purposes tions and we make use of limited modelling due of this project we have used the models by Mad- to constraints on project scope and our data, it is husudhan et al. (2011), following the reasoning by useful to briefly discuss some of the atmospheric Biller et al. (2015). models that are under development. For an ex- haustive review on these modelling efforts we refer 2.4 Summary the reader to Marley & Robinson (2015). Work on modelling the atmospheres in very-low Defining what is a Brown Dwarf versus a Giant mass stars and BD’s has been ongoing for more Planet is not an easy task, and one that has be- than about two decades (e.g. Ackerman & Marley come increasingly important and complex over the 2001 and references therein). It is only in recent years. A less arbitrary definition most likely lies in years that directly imaged data of gas giants out- the underlying dominant mechanism of their for- side the Solar system, from low-mass BD’s or GP’s mation – core-accretion in a protoplanetary disk such as those around HR 8799, has become avail- for GP’s and a collapse scenario for BD’s. able for direct comparison. Observations of the The WISE survey of low-mass BD’s has intro- four planets around HR 8799 are especially impor- duced a large sample of potential GP analogues tant and were used by both Marley et al. (2012), that due to their free-floating nature can be more whose models have been under continuous devel- easily studied compared to their star-bound GP opment (e.g. Saumon & Marley 2008, Marley et cousins. As the BD’s cool down through the spec- al. 2010, Madhusudhan et al. 2011). tral types L and T we can use IR photometry of In general, the models tune various parameters these objects to detect periodic variations and from such as grain size of the particles in the atmo- them discern rotation periods and, when combined sphere, how effectively these particles dissipate to with atmospheric modelling, possible cloud struc- areas below the photosphere (sedimentation effi- tures. ciency), surface gravity (log (g)) and Teff to repro- By doing this we not only learn more about the duce observed spectra and photometric variabil- evolution of BD’s, especially in the critical L/T ity. Madhusudhan et al. (2011) and Marley et al. transition, but we also develop methods that can (2012) are somewhat at odds in interpreting the more readily be used on directly imaged GP’s, observations of HR 8799 in relation to the more and ultimately could be used in observations of traditional models (e.g. Saumon & Marley 2008). terrestrial-like worlds in the future. 3 Observations - 14 - Section 3.0

3 Observations lard et al. 2001). These produce synthetic spectra and magnitudes for a set of ages, masses and tem- In this section we start by declaring the origins of peratures. To estimate the correction we used the the observational data, followed by a walkthrough magnitudes obtained from the 2MASS- and of the data reduction process for both of the in- MKO-Vega models for a 0.010 M BD, with the struments used. correction for going from MKO to 2MASS in e.g. J Table (1) & (2) list the targets and observa- then being 14.943−14.652 = 0.291 mag. A similar tional information from 23 observing runs. Table correction was done for HN Peg B and compared (3) & (4) list the properties of our 18 targets in the with known 2MASS and MKO magnitudes as a field and the 3 that are companions, respectively. control to ensure that this was a reasonable ap- A colour-magnitude diagram of our target sample proximation. compared with that of Radigan et al. (2014) and Metchev et al. (2015) is shown below in Figure (7). The data used in this project originated from two observing programmes done during 2014. All observations except one are from the 3.5 m New 12 Radigan et al. (2014) Metchev et al. (2015) Technology Telescope (NTT) at the La Silla Ob- This work servatory in Chile, using the IR instrument Son 13 PSO 318 OF ISAAC (SOFI; Moorwood et al. 1998a), a smaller version of the instrument built for the VLT 14 (ISAAC; Moorwood et al. 1998b). HD106906 b was observed using the High Acu- ity, Wide field K-band Imaging (HAWK-I; Pirard

J 15 et al. 2004, Casali et al. 2006, Kissler-Patig et M al. 2008, Siebenmorgen et al. 2011) instrument 16 installed at the VLT at the Paranal Observatory in Chile. All NTT/SOFI observations were obtained from 17 the publicly released data found in the ESO archive, one year after the observing date, pro- 18 duced by the ESO observation program 194.C- 0827(A) – The First Search for Exoplanet Weather, −1.0−0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 PI: Biller, B. The program was allocated a total of J-KS 13 nights during October and November 2014 and 21 targets were observed, 20 of which were one- Figure 7: Colour-Magnitude diagram of our sam- time observations while PSO 318 was observed on ple compared with recent surveys. No differenti- multiple nights in JS and once in KS. ation in terms of variability is done in this plot. The VLT/HAWK-I observation was done un- The left-most red dot is the T2.5 dwarf HN Peg der the ESO observation program 292.C-5024(A) B, which would be found near the middle of the – Measuring the Rotation Period of a Directly Im- L/T transition. The extremely red T3.5 compan- aged Extrasolar Giant Planet, PI: Apai, D. This ion GU Psc b can be seen at the very bottom and was a single night allocation of 4 hours spent ob- HD 106906 b (L2.5) just below PSO 318. serving HD 106906 b in March 2014 and the data was publicly released in March 2015. In this diagram, the MKO magnitudes for GU Further details on both of these instruments Psc b listed in Table (4) were converted to 2MASS can be found in the NTT/SOFI (§3.1) and magnitudes using an estimated correction obtained VLT/HAWK-I (§3.2) sections. from the AMES-Cond BD atmospheric models (Al- Software used in the reduction of these obser- 3 Observations - 15 - Section 3.0 vations include routines from PyRAF/IRAF and Gasgano. Their application is explored in more de- pipelines from the ESO Common Pipeline Library tail in the Data Reduction sections §3.1.1 & §3.2.1. (CPL) executed using the graphical user interface

Table 1: SOFI observations, Program ID: 194.C-0827(A).

Target name Filter Date DIT NDIT Exp. Time On-Sky Time

2MASS J00452143+1634446 JS 2014-11-11 8 s 6 2.70 hours 4.06 hours 2MASS J01033203+1935361 JS 2014-11-03 10 s 6 4.27 hours 5.27 hours 2MASS J01174748-3403258 JS 2014-11-08 10 s 6 2.80 hours 4.42 hours 2MASS J02340093-6442068 JS 2014-11-10 10 s 6 4.40 hours 5.78 hours 2MASS J03032042-7312300 JS 2014-11-09 10 s 6 4.45 hours 5.51 hours 2MASS J03231002-4631237 JS 2014-11-07 10 s 6 4.00 hours 5.19 hours 2MASS J03264225-2102057 JS 2014-10-09 10 s 6 3.58 hours 4.70 hours 2MASS J03421621-6817321 JS 2014-11-03 10 s 6 2.80 hours 3.32 hours 2MASS J03552337+1133437 JS 2014-10-07 10 s 6 3.60 hours 4.73 hours 2MASS J03572695-4417305 JS 2014-10-10 10 s 6 3.05 hours 4.12 hours 2MASS J04210718-6306022 JS 2014-10-08 10 s 6 4.10 hours 5.50 hours 2MASS J05012406-0010452 JS 2014-11-11 10 s 6 3.20 hours 4.05 hours 2MASS J05184616-2756457 JS 2014-11-05 10 s 6 2.80 hours 3.98 hours 2MASS J05361998-1920396 JS 2014-10-11 10 s 6 2.40 hours 3.06 hours 2MASS J22244381-0158521 JS 2014-11-05 10 s 6 2.80 hours 3.59 hours 2MASS J23225299-6151275 JS 2014-10-10 10 s 6 2.73 hours 4.47 hours GU Psc b JS 2014-10-11 10 s 6 2.93 hours 4.08 hours HN Peg B JS 2014-11-08 10 s 6 3.00 hours 3.79 hours PSO J318.5338-22.8603 JS 2014-10-09 10 s 6 3.80 hours 5.07 hours PSO J318.5338-22.8603 JS 2014-11-09 15 s 6 2.40 hours 2.79 hours PSO J318.5338-22.8603 KS 2014-11-10 20 s 6 2.80 hours 3.10 hours SIMP J215434.5-105530.8 JS 2014-11-07 10 s 6 2.48 hours 3.44 hours 71.1 hours 94.0 hours

Table 2: HAWK-I observations, Program ID: 292.C-5024(A).

Target name Filter Date DIT NDIT Exp. Time On-Sky Time HD 106906 b J 2014-03-08 8 s 47 3.13 hours 3.91 hours 3 Observations - 16 - Section 3.0

Table 3: Field object properties.

Name SpT 2MASS 2MASS J-KS Mass d Opt. NIR Ref. J (mag) KS (mag) (mag) (MJup) (pc) Ref. 2M0045 L2β L2 1,1 13.06 11.37 1.69 13 − 14 13.3 ± 0.8a 1,1 2M0103 L6β L6 1,1 16.29 14.15 2.14 10 − 11 21.3 ± 3.4b 1,1 2M0117 . . . L1 1 15.18 13.49 1.69 13 − 14 40.6 ± 2.0a 1,1 2M0234 L0γ . . . 1 15.32 13.85 1.47 13 − 14 45.8 ± 2.8a 1,1 2M0303 L2γ . . . 1 16.14 14.32 1.82 12 − 14 34.6 ± 3.2a 1,1 2M0323 L0γ . . . 1 15.39 13.70 1.69 14 − 15 49.4 ± 3.2a 1,1 2M0326 L4 . . . 1 16.13 13.92 2.21 13 − 15 26.1 ± 2.0a 1,1 2M0342 L2 . . . 1 16.85 14.54 2.31 11 − 13 50.2 ± 3.6a 1,1 2M0355 L5γ L3 1,1 14.05 11.53 2.52 13 − 14 9.1 ± 0.1b 1,1 2M0357 L0β . . . 1 14.37 12.91 1.46 14 − 15 48.6 ± 3.2a 1,1 2M0421 L5γ . . . 1 15.56 13.45 2.11 10 − 11 16.5 ± 1.2a 1,1 2M0501 L4γ L3 1,1 14.98 12.96 2.02 9 − 11 13.1 ± 0.8b 3,1 2M0518 L1γ L1 1,1 15.26 13.61 1.65 14 − 22 46.8 ± 15.0b 1,1 2M0536 L2γ L2 1,1 15.77 13.85 1.92 12 − 13 39.0 ± 14.0a 1,1 2M2224 L4.5 L3.5 1,1 14.07 12.02 2.05 . . . c 11.6 ± 0.1b 1,1 2M2322 L2γ . . . 1 15.55 13.86 1.69 12 − 13 43.0 ± 2.4a 1,1 PSO 318 . . . L7 1 16.71 14.74 1.97 6.5 ± 1.0 24.6 ± 1.4b 4,1 SIMP J2154 . . . L4β 2 16.44 14.20 2.24 10 − 11 22.1 ± 2.8b 2,2

Notes.– a Statistical prediction of d. b Measurement of d. c No mass-estimate located in literature. The Greek suffixes for SpT denotes signs of low-gravity (§2.1.2.) References. – (1) Gagn´eet al. (2014a); (2) Gagn´eet al. (2014b); (3) Gagn´eet al. (2015); – mass estimates listed in these publications were typically obtained from isochrones; (4) Liu et al. (2013).

Table 4: Companion object properties.

Name SpT J KS J-KS Mass d Opt. NIR Ref. (mag) (mag) (mag) (MJup) (pc) Ref. GU Psc b . . . T3.5 ± 1 3 18.12a 17.40a 0.72a 9 − 13 48 ± 5 3,3 HD 106906 b . . . L2.5 ± 1 1 17.60b 15.46b 2.14b 11.0 ± 2 92 ± 6 1,1 HN Peg B . . . T2.5 ± 0.5 2 16.06c 15.04c 1.02c 22.0 ± 9.4 18.4 ± 0.3 2,2

Notes.– a Magnitudes according to Manua Kea Observatory system (MKO; Simons & Tokunaga 2002, Tokunaga & Vacca 2005). b 2MASS magnitudes from (1). c 2MASS magnitudes from Metchev et al. (2015). References. – (1) Bailey et al. (2014); (2) Luhman et al. (2007); (3) Naud et al. (2014). 3 Observations - 17 - Section 3.1

3.1 NTT/SOFI an NDIT of 6 results in 60s exposures. In the case of 2M0045, imaging was done initially with a DIT The SOFI instrument is a cryogenically cooled (77 of 10s followed by a change to 8s, presumably due K) spectrograph and imaging camera with a field to the brightness of the target. This was accounted 0 of view of 4.92 × 4.92 arc minutes ( ) on a single for during reduction. 1024×1024 detector chip, corresponding to a pixel The exposure times listed in Table (1) are based 00 scale of 0.288 arc seconds ( ). The gain, i.e. the on the raw data and a few of the raw frames were amount of electrons converted by the detector to discarded during the reduction process. The rea- − one Analog-Digital Unit (ADU), is ∼5.4 e /ADU sons for their rejection include: cosmic ray strikes and the Read-Out Noise (RON) is ∼2.1 ADU. This close to the target, distorted frames from observa- gain value is linear to within less than 1.5% up to tions during late morning, interrupted NDIT runs 10000 ADU, meaning that pixels past this level can where no counterpart jitter frames exist and ex- not be relied upon to provide accurate photometry. tremely poor weather conditions. The on-sky time The detector will also start saturating somewhere on the other hand is the elapsed time of the data past this point, leading to electrons ”spilling over” that actually gets reduced. The seeing for these ob- to other pixels in that column, again contaminat- servations, typically estimated as the full-width at ing the photometry. Special attention to this limit half-maximum (FWHM) of the point spread func- is therefore paid when suitable reference stars are tion (PSF), ranged from 0.500 to 1.700 with typical to be selected for the analysis. Finally, the JS fil- values around 0.9 - 1.100 equivalent to 3.1 - 3.8 pix- ter has a central wavelength of 1.240 µm and a els. width of 0.160 µm with a transmission efficiency of around 90%. The corresponding statistics for 3.1.1 Data reduction the KS filter are 2.162 µm, 0.275 µm and 88%. The imaging strategy used in these observations, The SOFI reduction pipeline was run using also described in Biller et al. (2015), henceforth Gasgano, the graphical user interface that is an B15, involved nodding the target back and forth alternative to the command-line environment Es- between two precise locations on the detector. The orex. Gasgano automatically groups observa- nodding pattern often used here and in general is tions after program- and run-ID, offering an easy an ABBA sequence, where you take a number of overview of all obtained frames in sequence and exposures at position A, move to position B where easy access to the file header information. It can you take two sets of the same number of expo- also be linked with e.g. DS9 for viewing and inter- sures before moving back to A again, whereafter acting with each individual frame which allows for the process is repeated. This method, also referred a much more rapid viewing of a large series of im- to as jitter imaging or microscanning, allows for ages, typical for jitter observations – roughly 4000 extremely accurate sky-subtraction in the reduc- individual frames throughout this project. A typ- tion process (see e.g. Devillard 1999). During the ical raw frame prior to reduction can be seen in reduction process, the jitter frames are combined Figure (8). to produce a single frame and this can be done in In addition to the basic reduction steps like cor- a number of ways. One can either combine the recting for dark current – thermal noise in the frames in each nod position and then use the nod- detector, and flat-fields – caused by variations in ding pattern to obtain the sky-subtraction, or com- pixel-to-pixel response and other inhomogeneities bine frames from one nod position with those of the that are relatively persistent, the SOFI detector other and do sky-subtraction during this process, has a unique defect that need to be accounted for. as is done in the SOFI pipeline. The implications Interquadrant row crosstalk, in short, is a shading of these various options will be discussed further. effect on rows that run parallel with other illumi- The typical detector integration time (DIT) was nated rows that are read out simultaneously. As 10 seconds for most targets, which combined with this is a predictable effect, it is easily corrected for 3 Observations - 18 - Section 3.1 as a first step of reduction in the SOFI pipeline Flatfielding with SOFI is done using special routine sofi img jitter. Before this is run however, dome flats in an on-off pattern for each filter used, master darks and flatfields need to be obtained. where 4 frames are taken with illumination inside the dome, and 4 without. These can then be re- combined using the sofi img dark routine and a typical master flat can be seen in Figure (10). Ac- cording to the documentation, the SOFI flatfields are extremely stable over long periods of time and using new flatfields each night is not necessary. However, as the data was available to us we opted for new master flats and darks for each night. A further illumination correction can be done to the master flat to improve the quality. Radigan (2014), seeking to verify the photometric variabil- ity findings of Wilson et al. (2014) among other things, investigate if such an illumination correc- Figure 8: Single raw 60 s exposure from NTT/- tion has an effect on this type of data. While SOFI. PSO 318 is barely visible, encircled in the they find that there is no difference in that regard, upper part of the image, and numerous flatfield they also conclude that applying the correction can artifacts can also be seen. never induce any variability in a non-variable tar- get, and we therefore apply one as we are able to. The next step in this routine is the dark cor- ESO provides an archive of illumination correc- rection. During the observation run, dark frames tions, typically updated every 6 months due to are exposures taken without any illumination on being even more stable than the flatfields, with a the detector, with exposure times corresponding variation of < 0.2% per month. However, as the to the desired DIT, e.g. 10 s. In general, a number latest available was from 2012, we opted to use of darks are taken with different DITs with two ex- standard star observations done during one of the posures at each setting. These are then typically nights in this programme, using the IRAF/PyRAF averaged to create a master dark frame (Figure script illumination.cl obtained from the SOFI web 9). In the SOFI pipeline this is handled by the pages. The correction is done by observing a stan- sofi img dark routine. dard star over 16 frames, moving the star about on the detector in a 4x4 grid. After sky-subtraction and flatfield correction, photometry is done for the star in all frames with the results and correspond- ing frame coordinates for the star being used by surfit to fit a second order polynomial. The re- sulting 1024 × 1024 frame, with pixel values of ∼ 0.98 - 1.02, is then multiplied with the master flat. The process has to be repeated for multiple filters, as both the flatfield and correction is filter dependant, as can be seen in Figure (11).

With the master dark and flat applied by the jit- ter routine, the next step is sky-subtraction. If no separate sky-frame is input in the routine, the sky- Figure 9: Typical master dark frame from NTT/- subtraction is computed from the object frames. SOFI. In short, this is done by considering that for each 3 Observations - 19 - Section 3.2 pixel on the detector, the sky value is the aver- this part of the frame can be used reliably as the age of the value of a given pixel in the current sky-subtraction for these pixels was one-sided, as frame and the next frame, with rejection of out- it were. Each frame has been visually inspected liers. Following this step the sky-subtracted frames for obvious defects, and in the event a cosmic ray are stacked through the application of a 2D cross- strike was indicated during analysis (e.g. tempo- correlation routine. Further details on these steps rary spike in flux) the relevant raw frames were can be found in version 1.2 of the SOFI pipeline also inspected. Special care had to be taken with manual. the data from HN Peg B, whose companion star had been placed outside the field of view of the detector, but still contributed significant flux with ”rays” landing on the detector. Occasionally these intersected with the target, and several frames had to be removed as a result. All targets were successfully located in the re- duced frames using either the Simbad database ser- vice in connection with the web-based Aladin Lite viewer to view 2MASS/DSS2/SDSS9 data, which was sufficient for most targets, or by accessing/- downloading frames directly from the 2MASS cat- alogue through the IPAC/Caltech website when identification was more difficult. Finding charts Figure 10: Typical master flat field from NTT/- for all targets using the SOFI data are included in this report alongside the results, displayed at a SOFI in JS. ∼90◦ counter-clockwise rotation in relation to true North, as this was the orientation all frames were obtained at.

3.2 VLT/HAWK-I HAWK-I is a cryogenically cooled (75 K) infrared wide-field imager with a field of view of 7.50 × 7.50 across 4 detector chips, each with 2048 × 2048 pix- Figure 11: Illumination corrections for SOFI flat- els and a pixel scale of 0.10600. For the observation fields in KS and JS. of HD 106906 b only the lower-left quadrant chip (Q1 or Chip #66 ) was used, presumably because Given that we have three exposures in each nod the wide-field capabilities of the imager was not re- position, there are two possible ways to combine quired for this task. This chip has a gain of 1.705 the raw frames using this routine. We either com- e−/ADU and RoN of 8 e− for a DIT of 10s, 5 e− for bine three A with three B nods, or simply one A > 15s. Each chip has a different gain, so as to en- with one B. Both options were tried and investi- sure that we had correctly identified the chip used, gated, and for reasons that will be discussed dur- a quick inspection of the obtained flatfields com- ing the Analysis (§4) the final stacked frames are a pared with flatfields from the HAWK-I web pages combination of two raw frames, resulting in about was done. The gain is linear to within 1% up to 2000 reduced frames. The combination of different 30000 ADUs with detector saturation above 40000 nod positions also creates noisy edge-areas in the ADUs. The J filter used has a central wavelength final frame where only data from one of the nod of 1.258 µm and a width of 0.154 µm with a trans- positions is used. As such, no objects that fall in mission efficiency of 88%. 3 Observations - 20 - Section 3.2

The telescope was oriented such that the host nated with a C was later chosen as a control, to see star HD 106906 itself was placed outside of the what influence the halo-effect had on variability. chip, which we assume was done to try to reduce detector saturation from the bright F5V star. The separation between HD 106906 and HD 106906 b is about 7.110, and as we will see in the analysis of the data, placing the host star out of the field of view to avoid saturation of the chip was not entirely successful. Typical seeing during the ob- servation was 0.900 with an airmass starting at 1.41 and ending at 1.18. Unlike the SOFI observations, the HAWK-I data was not obtained through jit- tered imaging, and there was no shift in the field during the observation. Therefore the reduction process is somewhat different.

3.2.1 Data reduction The HAWK-I pipeline was run in Gasgano for the Figure 12: Close-up view of HD 106906 b, desig- reduction of the 30 frames obtained from this ob- nated as zero in the image, in one of the reduced servation. Compared to the SOFI observations, frames. A halo-effect originating from the out-of- these had a longer exposure time of DIT × NDIT frame host F5V star contaminates much of the up- = 376 seconds and were not executed using any per right part of the detector. The star designated nodding or other form of dithered imaging. We as C was chosen to be a control for the influence are unsure as to the reasoning for this choice of of this halo during analysis. observation technique, but we suspect it is related to the very bright host star. A master dark and The halo contributed up to 1000-3000 ADUs flat were created using the hawki img dark and where this effect was the most intense, with the hawki img flat routines and for this observation no rays in particular having high counts. The ray near illumination correction of the flatfield was done. HD 106906 b peaked at around 1000 ADUs, and The routine hawki step basic calib was then run overall the target was covered by the halo at about with the master dark and flat, producing the fi- 400-600 ADUs. This was very much comparable nal reduced frames. We were unable to locate to the peak ADU count one might expect from the any sky frames obtained for the purposes of sky- target itself. The total halo contribution varied subtraction, so that was handled afterwards in from frame to frame, but nonetheless efforts were PyRAF. undertaken to try to salvage some information. Upon completion of the basic reduction, we were We opted for applying a method referred to as somewhat dismayed at the prospects of obtaining median box filtering, which creates a smoothed anything useful from the data, as illumination from version of the original frame where flat features the host star had produced a halo-effect covering such as sky contribution dominate. This smoothed most of the upper right quadrant of the detector, frame can then be subtracted from the original with lesser influence reaching out to 300-400 pix- frame, greatly reducing most of the flat features. els away from the source. This can be seen in the Since the halo-effect was by and large very much a zoomed-in part of one of the reduced frames, shown flat contribution, this seemed like the best option in Figure (12) with the target marked with a zero, available. and how it was identified as HD 106906 b will be The filter is applied by having a rectangular win- detailed at the end of this section. The star desig- dow move across the frame, replacing the center 3 Observations - 21 - Section 3.2 pixel in the window by the median of all pixels in equally on all objects in the frame, it should not the window. Typically a box which is 3-5 times be able to induce variability in any target, not af- the FWHM in size is desirable, as too small a box fected by the halo, that did not have it previously. risks removing large contributions from the objects Finally, by using this filter with such a small box, themselves in the frame. This can be seen in the we subsequently had to limit our aperture pho- PSF as it changes in shape from a regular Gaussian tometry to a maximum radius of 4.5 pixels due to to having troughs of negative flux contribution in- introducing negative troughs in the PSF at greater stead of extended wings, as the median value cho- radii. The 15 pixel box was similarly affected so sen for these pixels is greater than their original the same limit had to be used there. values. This is noticeable during photometry, as the flux will stop increasing and plateau rapidly As no specific coordinates for HD 106906 b were or even decrease, with an increase in aperture size. available, coupled with the lack of the host star However, if done with a sufficiently large box, these for reference, confident identification of the tar- problems are generally avoided but should always get was somewhat difficult. Bailey et al. (2014) be kept in mind and accounted for. do provide the angular separation of 7.1100 along In our case, we were in the end forced to use with the position angle, but with frame coordi- a 10 × 10 pixel box, equivalent to ∼ 2× FWHM. nates not corresponding well enough with actual Applying this filter we used the IRAF task fme- coordinates in RA and Dec, coupled with the left- dian under images.imfilter in PyRAF to create the overs of the host star halo possibly obscuring the smooth frames which were then subtracted from target, we opted for confirming the position using the originals. A box size lower than 8 pixels dam- the HST data from 2004. This was done through aged the PSF extensively and a larger box would simple vector geometry as can be seen in Figure not remove enough of the halo to enable photom- (14), which also allowed us to easily rule out the etry to be done reliably in all frames. Figure (13) possible point source left of ”D” in the figure as shows one of the more badly affected frames and being HD 106906 b. If that had been our target, the difference between a box size of 10, 15 and 20 it would have been obscured by the nearby ray. pixels. As the PSF looked acceptable with a 10 Finally, the much stronger emission in the J-band pixel box filtering we opted to go with that over the from ”D” is also a clear indication of it being the 15 pixel box filtering. Since the filtering is applied correct target.

Figure 13: The three panels show HD 106906 b and the remaining influence from the host star in one of the most badly affected frames, following the application of a median box filtering with a box size of 10, 15 and 20 pixels respectively. The green circles indicate radii of 7, 17 and 22 pixels. 4 Analysis - 22 - Section 4.1

field, and while the absolute minimum required for this type of analysis is 2, 3-5 are preferable. For some targets, e.g. 2M0045, a relatively low num- ber of suitable stars were present in the field, but in general 10-20 were selected initially. Other than the very basic requirement that the reference star is not too close to other stars, the first criterion is the linearity limit, 10000 and 40000 ADUs for SOFI and HAWK-I respectively. In the case of the HAWK-I observations, the reference star selection was done prior to the median box filtering, as this naturally lowers the ADU count of the sources in the frame. The lower ADU limit for our selection was de- pendant on the number of potential stars in the field and the brightness of the target. For the ini- tial selection we typically chose stars down to 10% of the flux of the target, up to the linearity limit. Figure 14: HD 106906 b identification (”D” in the Stars brighter than the target are generally pre- frame) using a reduced and median box filtered ferred, assuming there is no clear variation in the HAWK-I frame and a cosmic-ray riddled 1250 s data that correlates with brightness, as these of- HST exposure of HD 106906 with the coronagraph fer data points with a higher photometric preci- applied. sion. A healthy number of stars fainter than the object were however always chosen to make sure 4 Analysis there were no variations unique to either faint or bright objects. With the exception of the GU Psc In this section we go through in detail the steps b observation, where the peak counts of the target involved in the analysis of our data. This starts off were on occasion as low as 20 ADUs, no reference with reference star selection and aperture photom- star with a peak count below 60 needed to be se- etry, followed by the calibration of the raw light lected at this stage. For the SOFI observations, the curves and their analysis. reference stars were typically numbered according In general we follow the process of analysis laid to increasing magnitude, with the target always out in Radigan et al. (2014), where a set of ref- being denominated as 0, followed by the faintest erence stars are chosen from the same field as the reference star as 1, and so on. target and then evaluated for photometric stabil- Following the selection of reference stars, aper- ity. Following photometry with a suitable aperture ture photometry was done in PyRAF using the size, these are then used to calibrate the raw light IRAF task phot which is part of the apphot pack- curves of the target and reference stars for varia- age. This is done by first defining the radius of tions in flux other than intrinsic target variability. an inner annulus within which the total flux is Once a calibrated light curve has been constructed, summed up, and an outer annulus from which the estimates of the peak-to-peak amplitude as well as sky background is estimated, with the two annuli lower limits of the rotation period can be obtained. being separated by 10-20 pixels. For photometry done on the SOFI observations, the radii selec- 4.1 Aperture Photometry tion for the inner aperture was 3.25, 3.50, 3.75, 4.00, 4.25, 4.50, 4.75, 5.00, 5.50, 6.00, 6.50, 7.00 The first step following reduction is the selection of and 7.50. This corresponds to an aperture size of a large number of suitable reference stars from the ∼ 1 − 3 FWHM and in most cases the data cho- 4 Analysis - 23 - Section 4.1 sen for the final light curve was from a ∼ 1.5 − 2 continuing the analysis. FWHM aperture. For fainter objects, a smaller aperture can be preferred as it reduces the amount With the raw flux exported from PyRAF using of background that is included, while a larger one txdump and imported into Python, the first step is is not considered detrimental for brighter objects to normalize it by its median value. The calcula- where the background is less significant by com- tion of the standard deviation (SD) of each object parison. The outer aperture was subsequently de- for each aperture size follows and serves as a check fined at 20-35 pixels from the center of the ob- to detect any critical errors in the photometry and ject, corresponding to about 2500 pixels used to as a first indication of which reference stars were estimate the background, rejecting outlier values unstable. At this stage, a reference star should (∼ 250 pixels) that were 2σ above the background have at most a SD of ∼ 1 − 2 times that of the level determined by a centroid (intensity-weighted target itself to be considered reasonably stable. mean) algorithm in phot. Following execution of the photometry, which The raw light curves for the target and reference by necessity was done with the help of coordinate stars are then plotted, showing fluctuations caused lists for the target and reference stars, the output by changing transparency of the atmosphere, air- was checked for errors due to e.g. incorrect cen- mass, seeing and other instrumental effects. To il- tering of the aperture and other anomalies such lustrate some of these effects, and point out a very as extended PSFs. The latter can originate from interesting reference star (RS) that we discovered double-stars or distant that were misiden- in our data, we include Figure (15a) & Figure (15b) tified as point-sources, and become evident in the below. The Elapsed Time value for a given data data as an increase in flux with aperture radius point represents the mid-point of a set of combined that is anomalous when compared to actual stars. frames. Barring any substantial weather effects or On two occasions at this stage a galaxy was in- changes in airmass or seeing, the raw flux tends to correctly identified as a star and removed before vary at the ∼ 5% level.

1.20 1.8 2M0421 1.15 RS1 1.6 RS2 1.10 RS4 1.4 RS6 RS7 1.05 1.2 Airmass

1.00 1.0

0.95 0.8 2M2322

Relative Flux Relative Flux Relative RS4 RS5 0.90 0.6 RS6 RS7 0.85 0.4 RS8 Airmass 0.80 0.2 1 2 3 4 5 1 2 3 4 Elapsed time [h] Elapsed Time [h]

(a) Raw light curve showing 2M0421 along with a (b) As in a) but for 2M2322. This observation was few reference stars. The change in (normalized) very badly impacted by weather, as can be seen by airmass is clearly correlated with a decrease in flux. the extreme changes in flux over time and the 1.5 h Also note the apparently very variable RS 7 (cyan) break in the observation. By contrast, the airmass that immediately piqued our interest. was fairly constant and would not have contribute to any significant changes.

Figure 15: Examples of raw light curves displaying decreased flux due to high airmass (a) and extremely poor weather leading to large changes in flux (b). Here, Elapsed Time is equivalent to on-sky time. 4 Analysis - 24 - Section 4.1

The strangely variable RS 7 in the 2M0421 data longer DIT, as was seen in the November observa- represented the strongest variable object observed tions of PSO 318 in JS and KS. These had DITs of in all of our data. Initially we thought we might 15 and 20 s respectively and the light curve we ob- have grossly misidentified the target so we went tained in JS was of surprisingly poor quality. Since to the 2MASS catalogue to verify the locations of exposure time seemed to be a factor, we made the both 2M0421 and this unknown star. There we assumption that the time between the first and last identified RS 7 as 2MASS J04211873-6306237, an frame in a set of 3 A nods and 3 B nods, ∼ 7.5 m object with JS 13.78 mag and J − KS 0.44 mag. for a DIT of 10 s, affected the quality of the pho- With that brightness and colour it does not fit in tometry. as a BD and further examination of images from To test this hypothesis we re-reduced the PSO DSS2 indicates it is most likely a regular star that 318 November data in JS and KS, combining one A is just not listed in Simbad. We will go on to ex- frame with the closest B frame in time. The result- plore this anomaly further as we continue detailing ing change in the SD vs. median plots for KS can the analysis process. be seen in Figure (17). Similarly for JS, the slope of the trend changed from 0.73 to 0.98 and the Before we move on to the calibration of the raw improvement of the raw light curve of this obser- light curves we return to the question of how to vation can be seen in Figure (18). These raw light best combine the raw jitter frames during the re- curves clearly illustrate the improvement from this duction process. The difference between combining finer ”sampling” of the data. We conclude that too them as AAA + BBB as opposed to A + B only long a separation in time between the first and last becomes apparent at this point in the analysis. We frame to be combined during reduction introduces originally went with the former option, believing it some additional noise to the final frame, likely due would offer us more precise photometry due to hav- to atmospheric variations which might also affect ing six frames to combine rather than two. How- fainter objects more. Following this outcome we ever, during our analysis which started with GU re-reduced previously completed data sets and pro- Psc b and HD 106906 b we began to notice a stark ceeded to use the A + B jitter frame combination contrast between the SOFI and HAWK-I data. for all our targets. In addition to looking at the raw light curves and their SD, plotting this against the median flux for an object and specific aperture size can indi- 3.50 40000 cate if the obtained photometry is anomalous in 3.75 some way or strongly dependant on aperture size. 30000 4.00 An example of such a plot from the otherwise ex- 4.25 cellent HAWK-I data can be seen in Figure (16). 20000 4.50 The trend present has a slope of 0.99, so it is almost 10000 perfectly linear, which is what one should expect in the optimal case. The same plot for the GU Psc 0 Standard Deviation of the Flux ofthe StandardDeviation 0 50000 100000 150000 200000 b data (not shown) displays a slope of 0.66 and Median Flux indicates a logarithmic trend. Initially we were unable to pin down the under- Figure 16: SD of the flux vs. median flux for the lying cause and as our analysis progressed and in- HD 106906 b observation. The data points rep- cluded other targets from SOFI, such as 2M0045 resent different aperture sizes used in photometry. and PSO 318, we came to two conclusions. a) It The close to perfectly linear trend indicates no dif- primarily affected fainter objects, and 2M0045, be- ference in the accuracy of the photometry for faint ing the brightest of our targets along with its sim- vs. brighter targets. Here HD 106906 b and the ilarly bright reference stars, displayed an almost control star C from Figure (12) have median fluxes linear trend. b) The problem became worse with a of ∼ 26000 and ∼ 13000 respectively. 4 Analysis - 25 - Section 4.2

2500 3.50 2500 3.50 4.00 4.00 2000 4.50 2000 4.50 5.00 5.00 1500 5.50 1500 5.50 6.00 6.00 1000 1000

500 500

0 0 Standard Deviation of the Flux ofthe StandardDeviation 0 5000 10000 15000 20000 Flux ofthe StandardDeviation 0 5000 10000 15000 20000 Median Flux Median Flux (a) SD of the flux vs. median flux for the PSO 318 Ks (b) Same as a), but using exposures that were combined observation in Nov. 2014, using 120s exposures that from single A + B nod positions. Note the radical re- were combined using 3A + 3B nod positions closest in duction in the SD for the same set of reference stars. time. The data points represent different aperture sizes Objects that were clear outliers in a) now behave nor- used in photometry. mally.

Figure 17: Plots showcasing the difference between combining jitter frames in pairs of three as compared to a pair of single frames during the reduction process. Faint objects such as GU Psc b and observations with a DIT longer than 10 s were especially prone to this type of degradation in the data.

Finally, the aperture photometry also provides 1.4 a photometric uncertainty or error in magnitudes. 1.3 In IRAF, phot estimates this in the following way 1.2 1.1 1.0 s 2 2 Flux Area × SD 0.9 σ = + Area × SD2 + mag Flux Relative 0.8 PSO 318 JS Nov. Gain Nsky 0.7 Airmass 0.6 − 0.5 1.0 1.5 2.0 2.5 Where the gain is e / ADU, area is the area of Elapsed Time [h] the aperture in square pixels and Nsky the num- (a) Raw light curve of the PSO 318 JS Nov. observa- ber of sky pixels. As we are using relative fluxes tion with some reference stars. Here the jitter frames and therefore have not used any standard star cal- were combined as 3A + 3B during reduction. ibrations for our observations to properly calibrate 1.4 the magnitude scale, we choose to convert the er- 1.3 ror into one of relative flux. This is also described 1.2 in the documentation for the phot package, where 1.1 σ is also defined as σ = 1.0857 × σ /Flux, 1.0 mag mag flux 0.9

which for the relative flux simply becomes σflux = Flux Relative 0.8 PSO 318 JS Nov. σmag/1.0857, and can be expressed as an error in 0.7 Airmass 0.6 percent that we will refer to as σphot. For our vari- 0.5 1.0 1.5 2.0 2.5 able targets we do not solely rely on this estimate of Elapsed Time [h] the uncertainty, which is the median of the photo- (b) Same as a), but here with the A + B combination metric error in all frames, but also do a polynomial during reduction. Some weak indications of variability can also be seen here, as the red data points are con- subtraction of the calibrated light curve, which re- sistently above the reference stars for the first ∼ 1.5 moves the astrophysical variability, and take the hours, and then consistently below. SD of the residual (§4.3). Figure 18: Plots showing the raw light curves pro- duced by the two different jitter frame combina- tions possible during reduction. 4 Analysis - 26 - Section 4.2

4.2 Light Curve Calibration sequence star or a giant with a smaller companion e.g. a white dwarf in an orbit that is tight enough After selecting a large number of reference stars that the stars are more or less in contact with each and completing aperture photometry, followed by other. While it seems like a reasonable possibil- an initial refinement of the RS selection based on ity due to the short period and almost perfectly the SD of their raw light curves, we arrive at sinusoidal curve, for the purposes of its use in this the central point in the analysis of photometric work, we have not investigated the true nature of variability. As previously discussed, all raw light this object further. As such we recognize that it curves display fluctuations due to various atmo- could very well be an intrinsic variable rather than spheric or instrumental effects. The principal idea extrinsic, caused by e.g. a δ Scuti star (Hartman behind the calibration of these raw light curves is et al. 2007). that these effects influence all targets in the field in the same way. It is therefore possible to isolate 1.2 most sources of variability other than that of an Contact Binary 2M0421, SD = 0.0053 astrophysical nature, and divide them out of the RS 2, SD = 0.0081 RS 4, SD = 0.0057 relative flux light curve. 1.1 RS 6, SD = 0.0045 As Radigan et al. (2014) points out, some mi- RS 8, SD = 0.0039 nor effects can remain in a few reference stars even after such a calibration. A few key points in their 1.0 analysis is that airmass and sky brightness have Relative Flux negligible correlations with these residual effects, 0.9 and that a by-eye assessment of the calibrated ref- erence star light curves is essentially sufficient to minimize the impact of residual effects on the anal- 0.8 0 1 2 3 4 5 ysis. Elapsed Time [h] The calibration curve is created by median- Figure 19: Showcasing a calibrated light curve with combining the relative flux light curves of all the a number of reference stars (RS), here with the sus- reference stars, excluding the target or specific ref- pected contact binary RS from the 2M0421 obser- erence star in question. The median-combining it- vation, with the intended target being shown with self is done by taking the median of the relative the red data points. The SD of calibrated light flux value of all reference stars in a specific frame, curves aid in selecting a final set of RS. and dividing the relative flux of the target by this value. Doing this for all frames creates the cali- bration curve. Therefore, with a selection of e.g. Reaching a final selection of RS is an iterative 5 reference stars and a target BD, the BD is cali- process. For the first iteration, we typically in- brated by the median-combined light curves of all cluded all RS if their total number was less than RS, and RS 1 is calibrated by RS 2 - 5, RS 2 by ten, otherwise they were split up in two groups, one RS 1 & 3 - 5, etc. The standard deviation is then for RS of similar brightness as the target and one again taken on these now calibrated light curves, containing the brighter stars. There were a number as a means of identifying noisy or variable RS. of ideas behind this initial large-scale calibration. Continuing with using the mysteriously variable Firstly, if there was any variability detected in the RS uncovered in the 2M0421 observation as an on- target when using a very large number of RS this going example, Figure (19) shows the calibrated would provide a good reference when iteratively light curve, also using 2M0421 as a ”reference reducing the RS to the final selection. If the na- star”, of what we concluded could be an unresolved ture of the variability changed drastically when a contact binary star, viewed near edge-on. That is, only a select few RS was used for the calibration, a binary system where there is typically a main this could indicate that the variability was instead 4 Analysis - 27 - Section 4.2 induced by one or more of these RS. was unusually poor with the majority of them be- Secondly, it served as a good control of the pho- ing noisy or unstable, a further 1-3 iterations past tometry, as one would not expect any major dif- the initial one that contained all the RS tended be ference in the variability of the target depending enough to arrive at the final selection. During this on if fainter or brighter RS were used, beyond ran- process it also often became apparent that for a dom variations caused by the intrinsically greater given observation there were a few apertures that photometric uncertainties in fainter objects. were clearly better than others, when it came to In addition to producing calibrated light curves minimizing scatter in the time-series data of the in each iteration, the data was also binned, with target or RS. the total number of frames typically divided into 8 1.2 1.2 bins unless doing so would introduce a bin contain- C-Binary, MAX-MIN=0.182 2M0421, MAX-MIN=0.008 1.1 1.1 ing too many or very few frames, at which point 1.0 1.0 0.9 0.9

either 7 or 9 bins were used. A bin would there- Relative Flux 0.8 0.8 1.2 1.2 RS2, MAX-MIN=0.009 RS4, MAX-MIN=0.011 fore represent the mean value of the relative flux of 1.1 1.1 the frames it contained, and with each observation 1.0 1.0 0.9 0.9 producing ∼ 80 − 130 final frames, the typical bin 0.8 0.8 1.2 1.2 RS6, MAX-MIN=0.011 RS8, MAX-MIN=0.01 was the average of ∼ 10 − 16 frames. 1.1 1.1 This binning allowed for an easier visual inspec- 1.0 1.0 0.9 0.9 tion of any variability trend and provided a means 0.8 0.8 0 1 2 3 4 5 0 1 2 3 4 5 of estimating the peak-to-peak amplitude in a con- Elapsed Time [h] Elapsed Time [h] sistent manner, by taking the maximum of the Figure 20: The binned light curves of the candi- binned data and subtracting the minimum. This date contact binary with several RS and 2M0421. MAX - MIN value, combined with the SD of the In this case, the data for the binary was not binned calibrated curve, served as the quantitative mea- as it was unnecessary given the amplitude and sures of which RS should be chosen for the final set. the 0.4% precision in the photometry. At this The optimal number of bins was arrived at through scale, any variability of 2M0421 is naturally not some iteration, where it was found that more bins discernible. than this would typically not show the overall vari- ability trend but rather pick up too much on the influences of outlying data points, and therefore In that regard, aperture selection was done more not produce a representative MAX - MIN value. or less in parallel to the RS selection, with the final Figure (19) shows the binned light curves for the choice boiling down to a few points. The first was candidate contact binary and a number of RS, indi- that the overall shape of the light curve should re- cating a peak-to-peak amplitude of 18.2 ± 0.4% for main relatively stable over several aperture sizes. this unusual star. We choose not to represent the This was primarily affected by the intrinsic scatter typical errors in these final plots using error bars, in the target which for fainter objects tended to because while this could be done on e.g. the first increase with greater aperture size. The stability data point, it ends up not being of much use most of the RS was sometimes also tied to aperture size, of the time, as multiple points tend to overlap and where a larger one could stabilize a RS that was block such a representation. Instead the obtained exceptionally noisy or unstable. In the event that errors are always clearly stated in the accompany- the RS selection was limited, this meant a com- ing figure caption and are available throughout the promise had to be made between an aperture that text as well as in the final results table. was large enough to minimize the scatter in the Further iterations of the RS selection then pro- RS, while not increasing it significantly in the tar- ceeded using these two quantitative values and get. The 2M0421 observation is a good example of careful by-eye inspection of the light curves for all this, and we will mention it further in the results. aperture sizes. Unless the available selection of RS The second point pertained to observations af- 4 Analysis - 28 - Section 4.3 fected by weather, where sometimes a very large served minimum being accurately represented by aperture could stabilize the light curve while us- a quadratic polynomial, while e.g. the candidate ing a smaller one would produce large amounts contact binary requires higher orders to obtain a of clearly artificial scatter in certain parts of the fit, as will be demonstrated in an example. curve, with the 2M0117 observation being repre- The second tool that we can apply for all obser- sentative of this effect. vations is the Lomb-Scargle periodogram (Scargle To summarize, the initial selection of reference 1982) which is designed to locate sinusoidal period- stars (RS) is iterated upon through the light curve icity in the data by applying Fourier transforms to calibration process, where light curves of several estimate the most probable periods that are appli- RS are median-combined to provide a calibration cable to the observation. We won’t go into the de- curve that is divided out of the raw, normalized, tails of the underlying mathematics, but in essence light curve. This removes the majority of non- it is similar to performing a least-squares fit to the astrophysical sources of variability, with the re- data using sinusoids. maining few that can affect the light curve in a In addition to the above we also apply further reference star effectively being filtered out of the methods of analysis or modelling to unique targets final selection to a large extent, through visual in- such as PSO 318, but those will be detailed in the spection. The time-series data in the calibrated relevant subsection of the Discussion (§6). light curves is then binned in a consistent manner and a MAX - MIN amplitude is obtained, which is 4.3.1 Polynomial subtraction what use as our amplitude estimate. An alterna- tive method would be to fit a sinusoidal curve to This is a very straight forward tool and is both eas- the data and from that extract an amplitude. ily applied and helpful for all our observations. The Final binned light curves of non-variable targets x and y components, time and relative flux respec- can be found in Appendix A, with the rest shown tively, of the calibrated light curves of the targets in §5.1 & §5.2. are input into e.g. polyfit in Python. Through a for/if-loop written in Python, a range of polyno- 4.3 Light Curve Analysis mial orders are fitted, then subtracted from the data producing a residual light curve from which With the final binned light curves having been ob- the standard deviation is calculated. The results tained, there are a few additional steps that can of each outcome is plotted for easy visual inspec- be taken to analyse the validity of the results. tion, as can be seen for e.g. the contact binary in The first of these, a polynomial subtraction of the Figure (21). light curve, attempts to remove the astrophysical Through the iteration of orders a reasonable fit variability and ideally leaving only random pho- is obtained for the target, yielding a SD of the ton noise. Following the subtraction, the standard residual that is comparable to σphot in the case of deviation is taken of this residual light curve and the contact binary. In general, the lowest order compared with σphot which was obtained from the required to obtain an accurate fit was chosen, as aperture photometry, to indicate over- or under- higher orders risk fitting the polynomial to struc- estimated errors. B15 opt for using this SD of the tures in the curve caused by random noise rather residual as a final measure of the uncertainty. We than astrophysical variability. For some targets find that by large, σphot is consistent with the es- that display variability which is not clearly sinu- timates we get from this subtraction process, but soidal, a compromise between accurately fitting the in a few cases we are motivated to use the SD of curve and obtaining a fit that appeared reasonably the residual instead, and in the event this occurs periodic had to be reached. In the end however, it will be clearly stated why. this particular aspect played a very minor role in Depending on the shape of the variability, poly- the outcome of the analysis. nomials of varying orders are required, with an ob- Polynomial subtraction plots for targets not in- 4 Analysis - 29 - Section 4.3 cluded in §5 can be found in Appendix B. ing mathematics and statistics is available in both Scargle (1982) and VanderPlas & Zeljkoˇ (2015).

C-Binary, MAX - MIN = 0.182 σphot = 0.004 1.2 0.15 So rather than focusing on the mathematics, and SD = 0.052 1.1 P(2) 0.10 0.05 due to our unfamiliarity with this method prior to 1.0 0.00 this work coupled with the fact that we decided to 0.9 0.05

Relative Flux 0.8 0.10 use a non-standard package for Python, we tested 1.2 0.06 P(3) SD = 0.021 1.1 0.04 the application of the gatspy L-S periodogram on 0.02 1.0 0.00 some simulated variability data seen below in Fig- 0.9 0.02 0.8 0.04 ure (22). The sinusoidal data of 100 points with 1.2 0.04 P(4) SD = 0.015 1.1 0.02 random noise added was generated using a period 0.00 1.0 0.02 of 2π h, so we would expect to obtain a period 0.9 0.04 0.8 0.06 estimate of ∼ 6.3 h from the L-S periodogram in 1.2 0.020 P(6) 0.015 SD = 0.005 1.1 0.010 Figure (23). 0.005 1.0 0.000 0.9 0.005 0.010 0.8 0.015 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h]

Figure 21: The results of the polynomial fitting (green curve) and subtraction of the candidate con- tact binary data. A polynomial of order six, P(6), is needed to reasonably approximate the astro- Arbitrary flux physical variability, leaving a residual with a stan- 0 1 2 3 4 5 6 dard deviation of 0.5%, consistent with the error Time [h] obtained from photometry. Figure 22: Simulated sinusoidal variability data with a period of 2π used for testing the L-S pe- 4.3.2 Lomb-Scargle periodogram riodogram package gatspy in Python. The Lomb-Scargle periodogram (Lomb 1976, Scar- gle 1982) is the method used for the analysis of L-S Test - Best Fit Period = 6.32 h periodic time-series data, and is most commonly 1.0 used for e.g. variable stars. It is also well suited for variable BD’s as the detected variability is of- 0.8 ten sinusoidal in origin due to being rotationally modulated. For the use in this work, we obtained a relatively new package for Python, gatspy (Vander- 0.6 Plas & Zeljkoˇ 2015), used for the creation of Lomb- Scargle (L-S) periodograms using either single- or 0.4 multi-band observations. We decided to use this specific package as it offered more options and from Lomb-Scargle Power 0.2 what we read, seemed like the best L-S tool avail- able for Python. 0.0 In short, the L-S analysis is essentially a least 2 4 6 8 10 12 squares frequency estimation, often computed us- Period [h] ing a Fast Fourier Transform. It locates vari- ous possible frequencies in the data and assigns Figure 23: L-S periodogram of the simulated vari- a ”power” value, between 0 and 1, to each specific ability data, indicating a best-fit period of 6.32 h frequency. A detailed explanation of the underly- at a peak power of ∼ 0.85. 5 Results - 30 - Section 5.1

To get Figure (23) we supplied the LombScar- C-Binary - Best Fit Period = 4.3 h gleFast routine in gatspy with our simulated data 1.0 and specified a range of 50000 possible periods be- tween the minimum period of 0.25 h and 2 times 0.8 the length of the ”observation”. Running this re- peatedly and with a varying amount of data points 0.6 (60-1000) we found that the method rarely under- estimated the period with more than ∼ 1.5% and the largest overestimation was ∼ 5%. While we do 0.4 not intend to apply these as error estimates to the periods obtained from the real observation data, it Lomb-Scargle Power 0.2 is good to have a rough idea of the accuracy in- volved and it gives an indication of how to set a 0.0 lower limit on the estimated period. The reason 2 4 6 8 10 for the peak not being more pronounced is simply Period [h] that longer periods, or a long period with multiple Figure 24: L-S periodogram of the 18.4 ± 0.4% peaks, can not be ruled out based on the limita- variable star detected in the 2M0421 observation, tion of the data, where in this case not even a full indicating a very strong peak at a period of 4.3 h. period is ”observed”, which also applies to all of our actual observations. The minimum period used for our observations 5 Results is set to 0.25 h to avoid extremely short period spikes. In a few instances on non-variable tar- In this section we present our results in three parts. gets, this was increased to a higher limit for the The first contains 4 targets what we consider to be same reason. The maximum period in turn has significantly variable – significant in the sense that an impact on the optimizing routine used for the the detection of variability is at least 3σ (> 99% best-fit period, so the interval has to be reasonably confidence). We consider all our measured ampli- defined. For this analysis to be consistent across tudes in this work to be upper limits, as none of observations with different on-sky times we opted them are at the 5σ level, even if PSO 318 comes for the value of 2× elapsed time. These limits used close at 4.6σ. All relevant plots for these targets for the period optimization end up being similar are presented in §5.1. to the ones used by Radigan et al. (2014). Following that is the section on our 10 tenta- tively variable targets – these all show variability that in most cases appears to be periodic, but falls Now, turning our attention again to the case of between 1 − 2.5σ in significance. §5.2 contains fi- the compact binary, the resulting L-S periodogram nal binned light curves and finding charts for all from that data set can be viewed in Figure (24). targets in this category, with the remaining plots As none of our other observations produce strong being available in Appendix B & C. peaks of this power in L-S periodograms we of- Finally we have our 7 non-variable targets, ten estimate the minimum period for a target at where a detection of possible variability fell below a value lower than that suggested as the best fit 1σ, or the data was of such poor quality that no period. Typically this value is set at either the determination could be made. Binned light curves length of the observation or closer to where the of these targets are available in Appendix A with power starts to increase in the periodogram. remaining plots located in the other two following L-S periodograms are listed for all significantly Appendix sections listed above. variable targets under §5.1 and the rest can be The results of all targets are presented at the found in Appendix C. end in Table (5). 5 Results - 31 - Section 5.1

5.1 Significantly Variable Targets RS and aperture selection, and a final aperture size of 3.75 pixels, equivalent to ∼1.2 FWHM, We start with presenting the results of the most was selected as this was found to minimize the important target, PSO 318, as it was observed in scatter in the majority of the data points of the multiple wavelengths and on three different nights target. Airmass changed from 1.03 to 1.83 over and displayed the strongest variability. 2M0045, the course of the observation, but no decrease 2M0117 and 2M0501 then follow. in normalized relative flux correlated to this is observed in any of the reference stars initially PSO J318.5338-22.8603 – It is perhaps some- selected for photometry. The polynomial sub- what fitting that the target that could be con- traction done for this observation (Figure 27) sidered to be our best GP analogue at ∼ 7 MJup shows that our photometric error is consistent turned out to be the most interesting. The first with the SD of the residual through a number of three observations of the L7 BD PSO 318 of polynomial orders, indicating that the domi- (Liu et al. 2013) was done in October 2014 nant component in the light curve can be easily and the resulting binned light curve in JS can fitted and subtracted, as expected. The corre- be seen below in Figure (25). We detect clear sponding L-S periodogram for all the PSO 318 and significant variability with an estimated observations can be seen in Figure (30), and peak-to-peak amplitude of 9.3 ± 2.0% during for the October observation there is a strong the 5 hour observation. A likely maximum can peak indicating a best fit sinusoidal period of be seen at ∼ 1.5 hours in with the beginnings 7.6 hours. However as we do not observe a full of a minimum at the end of the observation. period we can only set a definite lower limit on The shape and amplitude of the light curve the period of > 5 h, and say that it is likely was highly consistent through the iteration of longer than ∼ 7 h.

1.10 1.10 PSO 318 J , MAX-MIN=0.093 RS7, MAX-MIN=0.005 1.05 S 1.05 1.00 1.00 0.95 0.95 0.90 0.90 Relative Flux 1.10 1.10 RS10, MAX-MIN=0.013 RS11, MAX-MIN=0.007 1.05 1.05 1.00 1.00 0.95 0.95 0.90 0.90 1.10 1.10 RS13, MAX-MIN=0.01 RS16, MAX-MIN=0.009 1.05 1.05 1.00 1.00 0.95 0.95 0.90 0.90 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h]

Figure 25: Binned light curves and finding chart for the PSO 318 JS observation in October 2014 using reference stars (RS) 7, 10, 11, 13 and 16. Airmass changed from 1.03 to 1.83 throughout the observation. Photometry was done with a 3.75 pixel aperture and a peak-to-peak amplitude of 9.3 ± 2.0% was obtained from the binned light curve. The circles in the finding chart represent the typical maximum inner aperture of 7.5 pixels, and the inner and outer boundaries of the sky-subtraction aperture between 20-35 pixels. As mentioned previously, the finding charts presented are rotated ∼90◦ counter-clockwise in relation to true North. 5 Results - 32 - Section 5.1

This period estimate also assumes the light curve as the DIT was 50% longer which should have pro- is single peaked during this observation, i.e. that vided greater photometric precision. The aperture there is only one source responsible for the variabil- size that minimized scatter in the target was 3.75 ity that is rotationally modulated, e.g. a hotspot pixels, corresponding to ∼ 1.5 FWHM for this ob- in the upper cloud layers. As we will see from servation. Efforts were made to use the same RS the JS observation just one month later, this is far as for the Oct. observation, but a change in the from certain. B15 obtained a very similar light field of view made that difficult. In the end two curve for this observation, reporting an amplitude RS were re-used, #11 and #15 corresponding to of 10.3±1.3%. Similarities and differences between #11 and #13 from Oct. our results and their findings will be discussed in The polynomial subtraction (Figure 27) again §6.2 as we analyse them further. showed consistency between our error estimates The binned light curve for the JS observation in and the L-S periodogram (Figure 30) providing a November is seen below in Figure (26) and presents best fit period estimate of 2.9 h, which agrees well a rather unexpected result, given what we detected with a visual inspection of the curve. It does how- in the data one month earlier. For this observation ever stand in stark contrast to what was observed we measure a significantly lower peak-to-peak am- just one month earlier, indicating significant evolu- plitude of ∼ 4.3 ± 1.8% with a potential maximum tion in the source of the variability. Based on this at 1 h and minimum at ∼ 2.5 h, which indicates observation alone, we would set a definite lower a much shorter period. During our initial reduc- limit for the period at 2.7 h if the light curve was tion using 3A + 3B jitter frames, this detection single peaked, but given the previous result it ap- did not even show up and the light curve was es- pears the shape is more complex than that. B15 sentially just noise. This was yet another clear report an amplitude of 7.0 ± 1.0% for this observa- indication that something was affecting our data, tion.

1.06 1.06 1.04 PSO 318 JS, MAX-MIN=0.043 1.04 RS10, MAX-MIN=0.008 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 Relative Flux 1.06 1.06 1.04 RS12, MAX-MIN=0.006 1.04 RS13, MAX-MIN=0.007 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94

1.06 1.06 1.04 RS15, MAX-MIN=0.004 1.04 RS16, MAX-MIN=0.007 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 Elapsed Time [h] Elapsed Time [h]

Figure 26: Binned light curves and finding chart for the PSO 318 JS observation in November 2014, with airmass changing from 1.09 to 1.88 throughout. A change in the field of view required a slightly different selection of RS compared to the Oct. observation (Figure 25). Photometry was done with a 3.75 pixel aperture and a peak-to-peak amplitude of 4.3 ± 1.8% was obtained from the binned light curve, indicating a period radically different from the Oct. observation. 5 Results - 33 - Section 5.1

The following night, PSO 318 was observed of RS had to be used. From the binned light curve again and this time in KS for 3 hours. From this in Figure (28) we obtain a continuous increase in data we obtain yet again a very different light curve flux throughout the observation equivalent to a compared with previous observations. As PSO 318 MAX - MIN amplitude of 2.8 ± 0.7%. While this is significantly brighter in KS a different selection flux increase occurs in parallel with the airmass

PSO 318 JS Oct., MAX - MIN = 0.093 σphot = 0.020 PSO 318 JS Nov., MAX - MIN = 0.043 σphot = 0.018 0.08 0.04 1.10 1.06 P(2) 0.06 SD = 0.022 P(2) 0.03 SD = 0.020 1.05 0.04 1.04 0.02 1.02 0.01 1.00 0.02 1.00 0.00 0.00 0.98 0.01 0.95 0.02 0.96 0.02 0.90 0.04 0.94 0.03 Relative Flux 0.06 Relative Flux 0.04 0.06 1.10 1.06 0.04 P(3) 0.04 SD = 0.021 1.04 P(3) SD = 0.018 1.05 0.02 1.02 0.02 1.00 0.00 1.00 0.00 0.95 0.02 0.98 0.02 0.04 0.96 0.90 0.94 0.04 0.06 0.06 1.10 1.06 0.04 P(4) 0.04 SD = 0.020 1.04 P(4) SD = 0.018 1.05 0.02 1.02 0.02 1.00 0.00 1.00 0.00 0.95 0.02 0.98 0.02 0.04 0.96 0.90 0.94 0.04 0.06 0.06 1.10 1.06 0.04 P(5) 0.04 SD = 0.019 1.04 P(5) SD = 0.018 1.05 0.02 1.02 0.02 1.00 0.00 1.00 0.00 0.95 0.02 0.98 0.02 0.04 0.96 0.90 0.94 0.04 0.06 0 1 2 3 4 5 0 1 2 3 4 5 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

Figure 27: Results of the polynomial subtraction done for the JS observations of PSO 318. The order of the polynomial is included in the parenthesis, e.g. P(2). The obtained standard deviations (SD) of the residuals are consistent with the photometric errors (σphot).

1.04 1.04 PSO 318 K , MAX-MIN=0.028 RS7, MAX-MIN=0.014 1.02 S 1.02 1.00 1.00 0.98 0.98

Relative Flux 0.96 0.96 1.04 1.04 RS8, MAX-MIN=0.012 RS9, MAX-MIN=0.015 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 1.04 0.0 0.5 1.0 1.5 2.0 2.5 3.0 RS12, MAX-MIN=0.009 Elapsed Time [h] 1.02 1.00 0.98 0.96 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h]

Figure 28: Binned light curves and finding chart for the PSO 318 KS observation in November 2014, with airmass changing from 1.08 to 1.85 throughout. Due to different luminosities in KS vs. JS, a different set of RS had to be used. Photometry was done with a 3.75 pixel aperture (∼ 1.2 FWHM) and a continuous increase in flux corresponding to a MAX - MIN amplitude of 2.8 ± 0.7% was obtained from the binned light curve. 5 Results - 34 - Section 5.1

increasing from 1.08 to 1.85, we do not observe As there are no clear indications of sinusoidal similar trends in the reference stars. While these variability in the light curve, the L-S periodogram are not as stable as in previous observations, given is also not of much use other than that it indicates the negligible correlations found for airmass with a period greater than 3 h, similar to the limit ob- residual noise by Radigan et al. (2014), it seems tained from the length of the observation. B15 to be an unlikely cause for the observed change in report a linear variability trend of < 3.0±0.7% for flux. The polynomial subtraction plot seen below this observation. in Figure (29) yields slightly higher errors from the Given the significant variability in the Oct. ob- SD of the residual, but agrees well with a linear in- servation and the discrepancies introduced into the crease in flux. interpretation of this data by the follow-up obser- vations, PSO 318 is a prime candidate for further PSO 318 KS Nov., MAX - MIN = 0.028 σphot = 0.007 0.020 study! Making sense of the conflicting indicators 1.04 0.015 P(1) 0.010 SD = 0.009 1.02 0.005 0.000 we obtain from these three nights will require fur- 1.00 0.005 0.010 0.98 0.015 ther observations. We return to PSO 318 in §6 but 0.020 Relative Flux 0.96 0.025 0.020 for now turn our attention to the other candidates 1.04 0.015 P(2) 0.010 SD = 0.009 1.02 0.005 that show signs of significant variability. 0.000 1.00 0.005 0.010 0.98 0.015 0.020 0.96 0.025 2MASS J00452143+1634446 – This L2 BD was 0.020 1.04 0.015 P(3) 0.010 SD = 0.009 1.02 0.005 the brightest target in our sample and produced 0.000 1.00 0.005 0.010 some excellent data as a result. The only draw- 0.98 0.015 0.020 0.96 0.025 back of the observation was the lack of a good 0.020 1.04 0.015 P(4) 0.010 SD = 0.009 number of RS in the field of view. As a re- 1.02 0.005 0.000 1.00 0.005 sult, the binned light curve seen in Figure (31) 0.010 0.98 0.015 0.020 0.96 0.025 was calibrated using only two RS – the second 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h] Elapsed Time [h] and third brightest objects in the frame. The other RS were significantly fainter with greater Figure 29: Results of the polynomial subtraction amounts of scatter which had some impact on done for the KS observation of PSO 318. The ob- certain parts of the light curve, even if the over- tained SD of the residual is consistent with σphot. all shape remained the same.

PSO 318 JS Oct. - Best Fit Period = 7.6 h PSO 318 JS Nov. - Best Fit Period = 2.9 h PSO 318 KS Nov. - Best Fit Period = 10.5 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4 Lomb-Scargle Power Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 0.2

0.0 0.0 0.0 2 4 6 8 10 1 2 3 4 5 1 2 3 4 5 6 Period [h] Period [h] Period [h]

Figure 30: Lomb-Scargle periodograms for the three PSO 318 observations. The three radically different light curves produced conflicting period estimates and re-observation will be required to obtain a more reliable estimate on the period of PSO 318. The KS observation diverges in the best fit estimate due to only a linear increase in flux being observed. 5 Results - 35 - Section 5.1

1.03 1.03 1.02 2M0045, MAX-MIN=0.011 1.02 RS1, MAX-MIN=0.005 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 1.02 RS2, MAX-MIN=0.005 Elapsed Time [h] 1.01 1.00 0.99 0.98 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h]

Figure 31: Binned light curves and finding chart for the 2M0045 observation, with airmass changing from 1.58 to 1.91 throughout. The target is the brightest object in the field by far, and as such the selection of good RS became somewhat restricted. Photometry was done with a 6.50 pixel aperture as this worked best given that the targets were exceptionally bright, and a possible peak-to-peak amplitude of 1.1 ± 0.3% was obtained from the binned light curve.

To exemplify the choice of quantity vs. quality a few other targets from this data set under the we were often faced with, we have included Figure same programme ID 194.C-0827(A). Regrettably (58) at the end of Appendix A, which illustrates that data is still proprietary and has therefore has how scatter can be induced by other RS in the cal- not been available for use in this work. We look ibration. In the end we opted for using the two forward to their results however, as 2M0045 is a most stable stars in the field, assuming the final great candidate for further observations, given the calibrated light curve would represent the most re- high precision photometry that can be obtained. liable result for this observation. 2M0045, MAX - MIN = 0.011 σphot = 0.003 Photometry using a larger 6.50 pixel aperture 1.03 0.008 1.02 0.006 P(2) 0.004 SD = 0.003 produced a stable light curve with an amplitude 1.01 0.002 1.00 0.000 0.99 0.002 of 1.1 ± 0.3%, with smaller aperture sizes yield- 0.004 0.98 0.006

Relative Flux 0.97 0.008 ing larger amplitudes up to 1.6%. However this 1.03 0.010 0.008 1.02 P(3) 0.006 SD = 0.003 was merely an effect caused by increased scatter 1.01 0.004 0.002 1.00 0.000 in first ∼ 1.5 hours of data. Polynomial subtrac- 0.99 0.002 0.004 0.98 0.006 tion (Figure 32) was consistent with what we have 0.97 0.008 1.03 0.006 seen from the PSO 318 observations, with SD er- 1.02 P(4) 0.004 SD = 0.002 1.01 0.002 1.00 0.000 rors indicating that the noise is largely accounted 0.99 0.002 0.98 0.004 for. The L-S periodogram (Figure 36) indicates a 0.97 0.006 1.03 0.006 moderately strong peak around 4.1 hours for sinu- 1.02 P(5) 0.004 SD = 0.002 1.01 0.002 soidal variability, which is also the length of the 1.00 0.000 0.99 0.002 observation. Airmass increased from 1.58 to 1.91 0.98 0.004 0.97 0.006 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 during the observation and should have a negligible Elapsed Time [h] Elapsed Time [h] effect, if any, on the result. We have not been able to locate any other ob- Figure 32: Results of the polynomial subtraction servations of photometric variability for this tar- done for 2M0045. The obtained SD of the residual get in the literature, but expect that PI Biller, B. is equivalent to or lower than σphot. will include it in a future publication as it was re- observed in August of 2015 for 3 hours, alongside 2MASS J01174748-3403258 – The observation 5 Results - 36 - Section 5.1 of the L1 BD 2M0117, which with regards to is real. Regardless of this fact however, the its properties is very similar to 2M0045, was MAX - MIN amplitude stands up to scrutiny unfortunately affected by bad weather, leaving in our opinion, given the stability of the sec- a 1 hour gap in the data. Despite this, and ond half. The polynomial subtraction (Figure despite that the field was again found lacking 35) gives a similar error estimation for either a in terms of RS, it proved to be an interesting minimum in an effectively longer-period curve target. The final binned light curve (Figure 33) (P(2)) or a minimum for a shorter-period one was obtained with an aperture size of 7.5 pixels, (P(3)). A peak of average power seen in the L- the result of a hard-fought compromise with the S periodogram (Figure 36) indicates a best fit available data. The first half of the light curve period of 4.7 h, and we can definitely say that was extremely sensitive to aperture size, most the period is longer than 4.5 h. likely due to the bad weather, and would pro- As with 2M0045 we have not found any other duce MAX - MIN amplitudes of up to 6% at relevant observations, but the target was re- 3.75 pixels, which were clearly not real and in- observed in 194.C-0827(A) on the same night duced by the RS. On the other hand, the rest as 2M0045 so we hope to see 2M0117 appear of the light curve exhibited the least scatter at in a variability study later this year. 4.50 pixels. It only stabilized past an aperture size of 6.50 pixels, yielding a final amplitude 2MASS J05012406-0010452 – 2M0501 is an- of 1.9 ± 0.6%. From the light curve it appears other early-mid L BD and its observation did that we are in a minimum, but with data from not run into any problems and offered a broad the first half of the observation being badly af- selection of possible RS. The binned light curve fected by weather, it is hard to say for sure that can be seen below in Figure (34) and shows the change in flux observed during this time what could be a maximum at the start of the

1.03 1.03 1.02 2M0117, MAX-MIN=0.019 1.02 RS1, MAX-MIN=0.01 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 1.03 1.02 RS2, MAX-MIN=0.01 Elapsed Time [h] 1.01 1.00 0.99 0.98 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Elapsed Time [h]

Figure 33: Binned light curves and finding chart for the 2M0117 observation, with airmass changing from 1.05 to 1.28 throughout. Photometry was done with a 7.50 pixel aperture as this minimized scatter of the data points in the first half of the observing run, and an amplitude of 1.9 ± 0.6% was obtained from what appears to be a minimum in the binned light curve. Similar to 2M0045 the number of RS available for selection was very limited. 5 Results - 37 - Section 5.1

observation with a minimum towards the end, than ∼ 5 h. For our lower limit estimate we, as yielding a peak-to-peak amplitude of 1.6 ± 0.5% per usual, go with the observation length of 4 h. at 3.75 pixels. Alternatively, if we are not observ- No other relevant observations of 2M0501 were lo- ing a maximum and minimum from a sinusoidal cated, and it had a very brief follow-up of 1 h 36 m modulation, we have a continuous decrease in flux in August 2016 as part of 194.C-0827(A), where it over the course of the observation. The L-S peri- might have presented a target-of-opportunity late odogram (Figure 36) indicates a best-fit period of in the morning. We would still expect it to be ac- 9.1 h, but a more conservative and probable esti- companying e.g. 2M0045 in a publication later this mate based on the periodogram would be greater year.

1.03 1.03 1.02 2M0501, MAX-MIN=0.016 1.02 RS6, MAX-MIN=0.006 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 1.03 1.02 RS9, MAX-MIN=0.005 1.02 RS10, MAX-MIN=0.005 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h]

Figure 34: Binned light curves and finding chart for the 2M0501 observation, with airmass changing from 1.25 to 1.40 throughout, with a low point at 1.14. Photometry was done with a 3.75 pixel aperture and a likely peak-to-peak amplitude of 1.6 ± 0.5% was obtained from the binned light curve.

2M0117, MAX - MIN = 0.019 σphot = 0.006 2M0501, MAX - MIN = 0.016 σphot = 0.005 0.020 1.03 0.015 1.03 0.015 1.02 0.010 SD = 0.004 1.02 P(2) 0.010 SD = 0.007 P(2) 1.01 0.005 1.01 0.005 1.00 0.000 1.00 0.000 0.99 0.005 0.99 0.005 0.98 0.010 0.97 0.015 0.98 0.010 Relative Flux Relative Flux 0.020 0.97 0.015 0.020 1.03 0.015 1.03 0.015 1.02 1.02 P(3) 0.010 SD = 0.007 P(3) 0.010 SD = 0.004 1.01 0.005 1.01 0.005 1.00 0.000 1.00 0.99 0.005 0.99 0.000 0.98 0.010 0.005 0.97 0.015 0.98 0.020 0.97 0.010 0.020 1.03 0.015 1.03 0.015 1.02 1.02 P(4) 0.010 SD = 0.006 P(4) 0.010 SD = 0.004 1.01 0.005 1.01 0.005 1.00 0.000 1.00 0.99 0.005 0.99 0.000 0.98 0.010 0.97 0.015 0.98 0.005 0.020 0.97 0.010 0.020 1.03 0.015 1.03 0.015 1.02 P(5) 0.010 SD = 0.006 1.02 P(5) 0.010 SD = 0.004 1.01 0.005 1.01 0.005 1.00 0.000 1.00 0.99 0.005 0.000 0.98 0.010 0.99 0.97 0.015 0.98 0.005 0.020 0.97 0.010 0.00.51.01.52.02.53.03.54.04.5 0.00.51.01.52.02.53.03.54.04.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

Figure 35: Results of the polynomial subtraction done for 2M0117 and 2M0501. As has been found consistently, the obtained SD of the residuals are similar to σphot. 5 Results - 38 - Section 5.2

2M0045 - Best Fit Period = 4.1 h 2M0117 - Best Fit Period = 4.7 h 2M0501 - Best Fit Period = 9.1 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4 Lomb-Scargle Power Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 0.2

0.0 0.0 0.0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 Period [h] Period [h] Period [h]

Figure 36: Lomb-Scargle periodograms for 2M0045, 2M0117 and 2M0501.

This concludes the presentation of our signifi- ter in the target increased instead. Due to the cantly variable targets, and we move on to the poor weather conditions we have to put a lower more ambiguous and tentatively variable ones. estimate on the period of 2.5 h, as the rest of the curve is ambiguous. 5.2 Tentatively Variable Targets 2MASS J03264225-2102057 – The observation Here we present the 10 targets that show signs of 2M0326 (L4) had no particular issues and of variability, but due to low amplitudes or large provided 3 very stable RS for the final binned errors do not reach a high enough level of sig- light curve (Figure 38) obtained with a 3.75 nificance. The binned light curves and finding pixel aperture. The shape of the light curve charts are displayed at the end of this subsection is very suggestive of sinusoidal variability with in Figures (37) - (46) with detailed captions. In a peak-to-peak amplitude of 1.9 ± 1.2%, and the event a target has been previously surveyed the L-S periodogram (Figure 62) produces the for photometric variability it will be mentioned. strongest peak (0.5) of our tentatively vari- The polynomial subtraction results and L-S peri- able targets, with a best fit period of 6.4 h. odograms can be found in Appendix B & C, and if needed we will refer to them more specifically. The polynomial subtraction (Figure 59) indi- cates that our photometric error may have been overestimated, giving a SD of 0.8% for all fits. 2MASS J03032042-7312300 – The observation While the variability is apparent and seems of this L2 BD was affected by bad weather periodic, given the lower significance we put a which caused the loss of 0.25 h at the start conservative lower limit of the period equal to of the observation, followed by further disrup- the observation length of 4.7 h, but note that tion after 2.7 h causing increased scatter in the it is likely at least 6 - 7 h. If it were possible, data. Using an aperture of 4.00 pixels we ob- we would like to re-observe this target. tain a continuous increase in flux of 2.6 ± 1.4% over the course of the observation (Figure 37). If we treat this as a 2.7 h observation we ob- 2MASS J03421621-6817321 – This L2 BD dis- serve a continuous increase in flux during this played non-sinusoidal variability in its binned stable part of the light curve of ∼ 2.5% which light curve (Figure 39) with a MAX - MIN still ranks as a tentative detection. Many of amplitude of 2.2 ± 1.5% obtained with a 4.25 the RS were affected by the poor weather con- pixel aperture. The RS were stable overall, and ditions and as such few were sufficiently stable none showed this dip in the light curve which for the final light curve. Some of these would seems unlikely to be caused by random noise, stabilize at larger apertures, but then the scat- so we assume it is inherent to our target. As it 5 Results - 39 - Section 5.2 is not clearly periodic and of relatively low sig- Metchev et al. (2015) also observed 2M0421 nificance, we choose not to put any constraints and found it to be non-variable (< 0.34)% at on the period of this target. 3.6 - 4.5 µm.

2MASS J03552337+1133437 – 2M0355 was 2MASS J05361998-1920396 – The observation the second brightest target in this survey and of 2M0536 (L2) presents another borderline provided photometric data with a 5.00 pixel case, where we obtain a possible peak-to-peak aperture of similar quality to 2M0045 (Figure amplitude of 1.0 ± 1.0% from the binned light 40). From the binned light curve we mea- curve (Figure 42). Similar to 2M0536, the poly- sure a MAX - MIN amplitude of 0.6 ± 0.4%, nomial subtraction (Figure 60) suggests a lower caused by the peak observed around 2 h. This error of 0.6 - 0.7%. Given these factors and that feature, which is not clearly sinusoidal, is not the shape remains stable through the iteration reproduced in any of the RS and is persistent process, we consider it to be candidate, albeit a through various iterations. A 5 RS binned fi- weak one, for the tentatively variable category nal light curve was also obtained, but the one with a period of at least 2 h. presented here was deemed to be a little more precise. The polynomial subtraction (Figure 2MASS J22244381-0158521 – 2M2224 (L3.5- 60) indicated a slightly lower error with a SD 4.5), being of similar brightness to 2M0355, of 0.3% but it still remains in the tentatively produced high-quality photometry as shown in variable category. Assuming this peak rep- the binned light curve in Figure 43, using an resents a maximum of a periodic feature, we aperture of 6.50 pixels. A MAX - MIN am- would assign the target a period of 2.9 h as plitude of 0.7 ± 0.4% was obtained from the indicated by the L-S periodogram. However, curve, with the observed peak being persistent we conclude that the observed light curve is through the iterations. The L-S periodogram too inconclusive for a well motivated estimate produces a peak power of 0.4 with a best fit of the rotation period to be made. period of 2.6 h. Assuming this variability to be periodic, we assign a lower limit to the ro- 2MASS J04210718-6306022 – Part of the ob- tation period of 2.5 h. Metchev et al. (2015) servation where we found our strangely variable observed this target and found it to be non- star, 2M0421 (L5) is very much a borderline variable (< 0.15)% at 3.6-4.5 µm. It could be case in this study, with the binned light curve an interesting target to re-observe if no better (Figure 41) providing a MIN - MAX amplitude targets were available. of 0.8 ± 0.7% at an aperture of 4.00 pixels. There are a few motivations as to why we in- GU Psc b – This wide-separation T3.5 com- clude it here rather than as a non-variable or panion has extremely red colours and is of inconclusive target. The shape of the curve is relatively low mass. As such it would be an suggestive of a sinusoidal periodicity, it is also excellent target for this kind of a survey. Un- relatively stable through the iteration of differ- fortunately it is also extremely faint. We were ent RS and apertures and the polynomial sub- hesitant to put it as a tentatively variable tar- traction analysis (Figure 60) suggests a lower get, but as we can not explain away the features error of 0.4%. There is also a weak response in seen in the binned light curve (Figure 44) as be- the L-S power (0.4, Figure 62) for a period of ing due to weather or other anomalies, we put 5.7 h. Assuming this variability to be periodic it in that category at 6.6 ± 4.2%. The aper- we put the lower limit of the period estimate ture size of 3.50 pixels was chosen to minimize at 5.5 h, equivalent to the observing length. the scatter in the target, but the MAX - MIN 5 Results - 40 - Section 5.2 amplitude is stable until 5.00 pixels. Here the very clear period of 18 ± 4 h. Given that 5.1σ error is estimated from the polynomial subtrac- detection we are presented with an interesting tion (4.2%; Figure 61) rather than σphot (3.7%), contradiction, or at least complication, which and we assign it a minimum period of 4 h. Its will be further discussed in §6.3. properties makes it an interesting target for re-observation, but given that a substantially SIMP J215434.5-105530.8 – Our final tenta- longer DIT would be required to obtain higher tively variable target, SIMP2154 (L4), was precision photometry, other targets may be found to have some irregular variability in its preferable. binned light curve (Figure 46). The MAX - MIN amplitude of 2.7±1.4% was obtained at an HN Peg B – Another wide-separation compan- aperture size of 5.00 pixels, and was fairly con- ion (T2.5), HN Peg B is likely the most massive stant at larger apertures. At smaller apertures target in this survey. Looking at the binned the RS, which were not great overall, showed light curve (Figure 45), obtained at an aperture a great deal of variability in the first hour of of 4.00 pixels, there appears to be some very the observation, however this stabilized past an short-period variability with a MAX - MIN am- aperture of 4.50 pixels. Looking at the curve, it plitude of 1.5±1.1%. From this result we would is possible we are in a minimum but it is hard put a lower limit to the period of 2 h. The tar- to say for sure given the gap and sensitivity to get was also re-observed for 2.5 h in August of aperture size in the early parts of the curve, 2016 as part of the same programme (194.C- most likely due to worsening weather. Due to 0827(A)). these factors, using the full observation length We previously showed a light curve of this as a lower estimate of the period does not seem very target, obtained by Metchev et al. (2015), justified. As such we put it at 2.5 h, which cor- in Figure (6). Their result indicated an am- responds to the length of the stable part of the plitude of ∼ 0.77 ± 0.15% at 3.6 µm with a observation.

1.06 1.06 1.04 2M0303, MAX-MIN=0.026 1.04 RS11, MAX-MIN=0.015 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 Relative Flux 1.06 1.06 1.04 RS12, MAX-MIN=0.009 1.04 RS13, MAX-MIN=0.02 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h]

Figure 37: Binned light curves and finding chart for the 2M0303 observation, with airmass changing from 1.41 to 1.81 throughout. This observation was plagued by bad weather, with 5 lost frames in the start, followed by further disruption after ∼ 2.7 hours of on-sky time, with fluctuations in the raw flux of up to 80%. Many RS were badly affected as a result, limiting the selection. Photometry was done with a 4.00 pixel aperture as this worked best given the circumstances, and a possible amplitude increase during the observation of 2.6 ± 1.4% was obtained from the binned light curve. 5 Results - 41 - Section 5.2

1.06 1.06 1.04 2M0326, MAX-MIN=0.019 1.04 RS5, MAX-MIN=0.006 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 Relative Flux 1.06 1.06 1.04 RS7, MAX-MIN=0.007 1.04 RS8, MAX-MIN=0.005 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 0 1 2 3 4 0 1 2 3 4 Elapsed Time [h] Elapsed Time [h]

Figure 38: Binned light curves and finding chart for the 2M0326 observation, with airmass changing from 1.05 to 1.51 throughout. Photometry was done with a 3.75 pixel aperture and a possible peak-to- peak amplitude of 1.9±1.2% was obtained from the binned light curve. The SD of the residual produced by the polynomial subtraction (Figure 60) suggests a lower uncertainty of ∼ 0.8%. The shape of the light curve combined with a L-S power of ∼ 0.5 (Figure 62) is highly suggestive of periodic variability, but given the error limits we obtain for this target it can’t be definitively determined and it remains a 1.6 − 2.4σ variable.

1.06 1.06 1.04 2M0342, MAX-MIN=0.022 1.04 RS9, MAX-MIN=0.007 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96

Relative Flux 0.94 0.94 1.06 1.06 1.04 RS10, MAX-MIN=0.006 1.04 RS11, MAX-MIN=0.007 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h] Elapsed Time [h]

Figure 39: Binned light curves and finding chart for the 2M0342 observation, with airmass changing from 1.29 to 1.55 throughout. Photometry was done with a 4.25 pixel aperture and a MAX - MIN amplitude of 2.2 ± 1.5% was obtained from the binned light curve. The dip in the curve, seemingly non-periodic given its sharp decrease, that is responsible for this amplitude is not present in any of the RS and should be inherent to the target. Given the overall shape, our obtained error estimates and essentially a null response in the L-S analysis (Figure 62), nothing more definitive can be said about this 1.5σ detection. 5 Results - 42 - Section 5.2

1.03 1.03 1.02 2M0355, MAX-MIN=0.006 1.02 RS5, MAX-MIN=0.006 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 1.03 1.02 RS6, MAX-MIN=0.006 1.02 RS9, MAX-MIN=0.004 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0 1 2 3 4 0 1 2 3 4 Elapsed Time [h] Elapsed Time [h]

Figure 40: Binned light curves and finding chart for the 2M0355 observation, with airmass changing from 1.73 to 1.62 throughout, with a low point at 1.33. Photometry was done with a 5.00 pixel aperture and a MAX - MIN amplitude of 0.6±0.4% was obtained from the binned light curve. The peak around 2 h is not reproduced in any of the RS and remains regardless of RS- or aperture-selection. The polynomial subtraction (Figure 60) provides a SD of the residual of ∼ 0.3% which would put this detection at the ∼ 2σ level rather than 1.5σ, but given no clear periodicity or strong response in the L-S analysis (0.35; Figure 62) we keep this as a tentative detection of variability.

1.03 1.03 1.02 2M0421, MAX-MIN=0.008 1.02 RS2, MAX-MIN=0.014 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 1.03 1.02 RS4, MAX-MIN=0.009 1.02 RS8, MAX-MIN=0.012 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h]

Figure 41: Binned light curves and finding chart for the 2M0421 observation, with airmass changing from 1.55 to 1.25 throughout. Photometry was done with a 4.00 pixel aperture and a MAX - MIN amplitude of 0.8 ± 0.7% was obtained from the binned light curve. The shape of the curve is persistent through both aperture and RS selection, even with the unstable RS. Given the lower error estimate of 0.4% obtained from the polynomial subtraction (Figure 60), and the suggestive shape of the curve paired with the L-S power of 0.35 (Figure 62), we put this into the tentative variable category at the 1 − 1.75σ level. 5 Results - 43 - Section 5.2

1.03 1.03 1.02 2M0536, MAX-MIN=0.01 1.02 RS13, MAX-MIN=0.004 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 1.03 1.03 1.02 RS14, MAX-MIN=0.006 1.02 RS15, MAX-MIN=0.007 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 Elapsed Time [h] Elapsed Time [h]

Figure 42: Binned light curves and finding chart for the 2M0536 observation, with airmass changing from 1.19 to 1.02 throughout. Photometry was done with a 4.50 pixel aperture and a possible peak- to-peak amplitude of 1.0 ± 1.0% was obtained from the binned light curve. We consider this a weak candidate (1 − 1.6σ) for the tentatively variable category due to the SD of 0.6 − 0.7% produced by the polynomial subtraction (Figure 61) paired with a weak but uniform response in the L-S analysis (Figure 63) and a suggestive shape of the light curve persistent throughout aperture and RS selection.

1.03 1.03 1.02 2M2224, MAX-MIN=0.007 1.02 RS6, MAX-MIN=0.005 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 1.03 1.02 RS7, MAX-MIN=0.005 1.02 RS8, MAX-MIN=0.005 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h] Elapsed Time [h]

Figure 43: Binned light curves and finding chart for the 2M2224 observation, with airmass changing from 1.13 to 2.01 throughout. Photometry was done with a 6.50 pixel aperture and a MAX - MIN amplitude of 0.7±0.4% was obtained from the binned light curve. The observed peak stands out among all apertures and selection of RS and is unique to the target, producing a L-S peak power of 0.4 for a 2.6 h period (Figure 63). The polynomial subtraction analysis (Figure 61) gives a slightly lower error of 0.3% which would put this as a tentatively variable target at 1.7 − 2.3σ. 5 Results - 44 - Section 5.2

1.2 1.2 GU Psc b, MAX-MIN=0.066 RS8, MAX-MIN=0.014 1.1 1.1 1.0 1.0 0.9 0.9

Relative Flux 0.8 0.8 1.2 1.2 RS11, MAX-MIN=0.023 RS12, MAX-MIN=0.015 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 1.2 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 RS13, MAX-MIN=0.014 1.1 Elapsed Time [h] 1.0 0.9 0.8 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h]

Figure 44: Binned light curves and finding chart for the GU Psc b observation, with airmass changing from 1.77 to 1.70 throughout, with a low point at 1.45. Photometry was done with a 3.50 pixel aperture and a MAX - MIN amplitude of 6.6±3.7% was obtained from the binned light curve, with the polynomial subtraction suggesting a slightly higher error of 4.2% (Figure 61). To remain consistent, we hesitantly categorize this target as tentatively variable at 1.6 − 1.8σ. The corresponding L-S periodogram can be seen in Figure (63).

1.03 1.03 1.02 HN Peg B, MAX-MIN=0.015 1.02 RS8, MAX-MIN=0.006 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 1.03 1.03 1.02 RS10, MAX-MIN=0.004 1.02 RS11, MAX-MIN=0.006 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 1.03 1.03 1.02 RS12, MAX-MIN=0.01 1.02 RS13, MAX-MIN=0.009 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h] Elapsed Time [h]

Figure 45: Binned light curves and finding chart for the HN Peg B observation, with airmass changing from 1.51 to 1.79 throughout. Photometry was done with a 4.00 pixel aperture to minimize the influence of the host star, and a MAX - MIN amplitude of 1.5 ± 1.1% was obtained from the binned light curve. A clearly variable (1.4 − 1.9σ) HN Peg B is intriguing given the results of observations of this target made by Metchev et al. (2015), which indicated a period of at least 18 hours. The L-S analysis (Figure 63) does not yield any strong results but there are clear suggestions of variability, further discussed in §6.3. 5 Results - 45 - Section 5.3

1.06 1.06 1.04 SIMP2154, MAX-MIN=0.027 1.04 RS5, MAX-MIN=0.013 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 Relative Flux 1.06 1.06 1.04 RS6, MAX-MIN=0.007 1.04 RS10, MAX-MIN=0.015 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h] Elapsed Time [h]

Figure 46: Binned light curves and finding chart for the SIMP2154 observation, with airmass changing from 1.07 to 2.06 throughout. Photometry was done with a 5.00 pixel aperture as smaller apertures than this induced strong scatter in the first 1/3 of the observation, and a MAX - MIN amplitude of 2.7±1.4% was obtained from the binned light curve. The shape is not clearly sinusoidal but could indicate that we are looking at a minimum. The polynomial subtraction (Figure 61) gives a SD consistent with σphot and the L-S analysis (Figure 63) gives a weak but fairly uniform response. We consider the target tentatively variable at 1.9σ.

5.3 Non-Variable Targets This gives us an upper limit of 3.0% and we maintain this convention for the other 6 non- This final part of the results section briefly presents variables. the targets that were deemed to be non-variable or inconclusive. The relevant plots for these targets can be found in Appendix A, B & C. 2MASS J02340093-6442068 – This L0 BD shows no clear signs of any sinusoidal variabil- 2MASS J01033203+1935361 – Observation of ity (Figure 52), at a MAX - MIN amplitude of this L6 BD produced a MAX - MIN amplitude 0.5 ± 0.6%. The quality of the RS was poor of 1.1 ± 1.3%, where this < 1σ amplitude is overall, leaving only two for the final curve. By our main reason for declaring in non-variable the same measure as previously, we assign an or inconclusive. We would leave it at that, upper limit of 1.4% to the variability of this had the target not been previously observed target. by Metchev et al. (2015) where they found a variability of 0.6 − 0.9% with an excellent photometric precision of 0.03% that can not 2MASS J03231002-4631237 – This target, our be matched by current ground based surveys. second L0 BD, also shows no signs of variabil- They obtained a period of 2.7 ± 1 h, and know- ity (Figure 53) with a MAX - MIN amplitude ing this, one can perhaps see a sinusoidal vari- of 0.3 ± 0.7% and we assign an upper limit to ability in our light curve with this period, with the variability of 1.4%. minima at 1 h and 3.7 h. However, that is not a valid justification for us to assign this target as 2MASS J03572695-4417305 – We detect no being tentatively variable based on our results. clear variability in this our third and final L0 To estimate an upper limit to the variability BD, with the binned light curve (Figure 54) we could miss in our data at a 3σ level given showing a MAX - MIN amplitude of 0.6±0.5%. its quality, we take the SD of the calibrated It could be considered a borderline case, but light curve of the target and multiply it by 3. past 2.5 h the observation continued under 5 Results - 46 - Section 5.3 what we assume were worsening weather con- servation can be categorized as inconclusive, to ditions and as such the MAX - MIN value is say the least. The binned light curve (Figure unreliable. The first stable 2+ h provide a 57), also displaying the control star ”C” makes corresponding amplitude of 0.3% which we do it clear the data can not be relied upon as both consider to be reliable. As such the target is the target and C show very similar trends. categorized as non-variable, at an upper limit To better illustrate this we also include Fig- 1.1%. ure (47) below, which superimposes the two objects as well as a few RS. From this figure 2MASS J05184616-2756457 – The observation it is very clear that whatever variability we of this L1 BD provided us with some of the are detecting in HD 106906 b is not intrinsic most stable RS in the survey, which combined to this companion, but rather induced by the with the MAX - MIN amplitude of 0.5 ± 0.7% halo that is cast upon the detector by the host obtained from the binned light curve (Figure star. The control star C is less affected, judg- 55) leads to the categorization of this target as ing by the SD of the calibrated curve, but it non-variable at < 1.9%. is also further away and not near any bright rays on the detector. While it in the end is a 2MASS J23225299-6151275 – This was our disappointing result, the exercise of evaluating bad-weather example from Figure (15b), pro- the data to this point proved to be interesting. ducing the fairly poor binned light curve seen The only estimate we can put on this observa- in Figure (56). With a MAX - MIN amplitude tion, is the more or less superfluous upper limit of 0.6 ± 1.1% and no clear indications of vari- of 25% for any possible variability in the target. ability from the more stable second half of the observation, we categorize the L2 BD 2M2322 With an overview of the targets and obtained as non-variable at < 2.7%. amplitudes listed in Table (5) on the following page, this concludes the Results section and we HD 106906 b – As we have indicated so far in move on to Discussion (§6) where the target in this work, the results of the HD 106906 b ob- focus will be PSO 318.

1.3 HD 106906 b, SD = 0.0814 1.2 Control star "C", SD = 0.044 1.1 1.0 0.9 0.8

Relative Flux 0.7 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h]

Figure 47: HD 106906 b and the control star labelled C, shown superimposed along with some reference stars. It is clear that the variability is induced by the halo effect from the host star HD 106906. 5 Results - 47 - Section 5.3

Table 5: Detections of variability reported in this work.

Target name SpT SpT 2MASS Mass Amplitude Period a Opt. NIR J-KS(mag) (MJup) (%)

Significantly variable targets PSO J318.5338-22.8603 . . . L7 1.97 6.5 ± 1.0 < 9.3 ± 2.0 & 5.0 h 2MASS J00452143+1634446 L2β L2 1.69 13 − 14 < 1.1 ± 0.3 & 4.1 h 2MASS J01174748-3403258 . . . L1 1.69 13 − 14 < 1.9 ± 0.6 & 4.5 h 2MASS J05012406-0010452 L4γ L3 2.02 9 − 11 < 1.6 ± 0.5 & 4.0 h

Tentatively variable targets 2MASS J03032042-7312300 L2γ . . . 1.82 12 − 14 < 2.6 ± 1.4 & 2.5 h 2MASS J03264225-2102057 L4 . . . 2.21 13 − 15 < 1.9 ± 1.2 & 4.7 h 2MASS J03421621-6817321 L2 . . . 2.31 11 − 13 < 2.2 ± 1.5 . . . 2MASS J03552337+1133437 L5γ L3 2.52 13 − 14 < 0.6 ± 0.3 . . . c 2MASS J04210718-6306022 L5γ . . . 2.11 10 − 11 < 0.8 ± 0.4 & 5.5 h 2MASS J05361998-1920396 L2γ L2 1.92 12 − 13 < 1.0 ± 0.7 & 2.0 h c 2MASS J22244381-0158521 L4.5 L3.5 2.05 . . . < 0.7 ± 0.4 & 2.5 h d GU Psc b . . . T3.5 ± 1 1.18 9 − 13 < 6.6 ± 4.2 & 4.0 h c HN Peg B . . . T2.5 ± 0.5 1.02 22.0 ± 9.4 < 1.5 ± 1.1 & 2.0 h SIMP J215434.5-105530.8 . . . L4β 2.24 10 − 11 < 2.7 ± 1.4 & 2.5 h

Non-variable – Upper limit estimates b 2MASS J01033203+1935361 L6β L6 2.14 10 − 11 < 3.0c ... 2MASS J02340093-6442068 L0γ . . . 1.47 13 − 14 < 1.4 . . . 2MASS J03231002-4631237 L0γ . . . 1.69 14 − 15 < 1.4 . . . 2MASS J03572695-4417305 L0β . . . 1.46 14 − 15 < 1.1 . . . 2MASS J05184616-2756457 L1γ L1 1.65 14 − 22 < 1.9 . . . 2MASS J23225299-6151275 L2γ . . . 1.69 12 − 13 < 2.7 . . . HD 106906 b . . . L2.5 ± 1 2.14 11.0 ± 2 < 25 . . .

Notes.– a Assuming a single-peaked light curve. b Upper limits on amplitudes are based on 3×SD c d of the calibrated light curves. Observed by Metchev et al. (2015). J-KS estimate derived in §3. References for SpT, J-KS and Mass in Tables (1), (2), (3) & (4). 6 Discussion - 48 - Section 6.1

6 Discussion

Having presented our results, and explained our A0 = (1+100.4∆m)A, where ∆m is the contrast-, or methodology and the execution of it, we move on to flux-, ratio for the binary. This implies that even discuss the various implications of our findings. We in an equal contrast binary, A0 will be ∼ 2.8 times begin with a brief discussion of the possible effects weaker than A. This ratio worsens if the lower flux that can arise from binarity in our targets, followed component is the variable one. Variability in bi- by a closer examination of the PSO 318 (§6.2) and nary systems is therefore harder to detect overall. HN Peg B (§6.3) observations. This is followed by As such, Radigan (2014) exclude known binaries a discussion regarding our chosen means of combin- from the statistical analysis of their sample, with ing the raw jitter frames and possible implications a few exceptions made for targets with large ∆m thereof, as compared to B15 (§6.4). We then look and both of these were late-L or T binaries. closer at what limits we can put on the frequency of variability in BD’s based on our results (§6.5), Both of these studies strongly imply that we and compare the findings from our work in this should examine our sample for possible binarity. variability study with some previous works (§6.6). In the literature we found one confirmed resolved Finally, we conclude this section by taking a brief binary in our sample, 2MASS J03572695-4417305 look at some future prospects for these types of which we found to be non-variable. Discovered and surveys (§6.7). spatially resolved by Bouy et al. (2003) and later spectrographically resolved into a M9 and L1.5 6.1 Implications of Binarity in the Sam- component by Liu et al. (2010), it has a combined ple SpT of L0. From their findings we conclude that the contrast ratio between the dominant M9 and If a target is treated as a single component object, fainter L1.5 component is ∆m ∼ 1.5. As such, any but is in fact part of a tight binary system that variability A in the L1.5 component, which is also when unresolved appears as a single object, this the most likely to be variable, would show up as an has several implications in a study of photometric amplitude of A0 ∼ 0.2A. While it has a negligible variability. Radigan et al. (2014) discuss this as impact on the statistics of our sample, we choose they investigate their sample for possible binaries. to exclude it from the analysis in §6.5. Another By looking at previous studies on the matter, they argument in favour of excluding it could be the conclude that up to 15 - 30% of BD’s in a sam- M9 component, where, as has been previously dis- ple could be unresolved binaries, with the fraction cussed, observed variability in SpT M is thought being possibly higher for the L/T transition. to be caused by an entirely different mechanic, e.g. In the work of Radigan (2014) they list three magnetic activity. primary challenges posed by unresolved binaries. Gagn´eet al. (2014a) attempt to determine the The first is that the SpT obtained for an unre- group association of many of our targets through solved system might not accurately represent the statistical analysis combined with mea- individual components, and they do need to be surements. Through this analysis they also pro- treated separately. Further, if variability is de- duce indications that a certain target is possibly an tected in such a system, there is no way of know- unresolved binary. While they expect a fraction of ing which component it originates with, especially false positives, they do not specify how big a frac- important if their SpT’s are substantially differ- tion or detail this part of the analysis any further ent. Finally, variability in a single component of as far as we can tell. However, it is worth noting an unresolved binary system is harder to detect. that they flagged several of our targets for possi- The amplitude required in one component to pro- ble unresolved binarity, namely 2M0323, 2M0326, duce a combined system variability amplitude A is 2M0342, 2M0355 and 2M0518. The first and last 6 Discussion - 49 - Section 6.2 of these were determined to be non-variable while plitudes of < 0.6% and < 0.7% for the same two the other three were tentatively variable at 1.9%, targets. We believe this is a strong argument in 2.2% and 0.6%. If these were unresolved binaries favour of independent verification, which we have, with one variable component, the actual ampli- as a by-product, performed in this work. As both tude would therefore be larger than the one we we and B15 reach very similar results through two measured. However, as far as we have searched the entirely different methods of reduction, we believe literature, we find no other indications of these be- this is strongly indicative that the variability found ing actual unresolved binaries. With the possible in PSO 318 is both substantial and real. Further- binarity only being indicated through the Bayesian more, as it is of very-low mass, it is one of the analysis of Gagn´eet al. (2014a), we choose not to best available free-floating analogues for GP’s like exclude these targets based on suspicion alone. those found in the HR 8799 system or β Pic b. As such, any properties such as rotation period are Finally, we touch briefly on the effects of eclips- important to accurately estimate. ing binaries, e.g. a binary system similar to the Assuming it is real, it is entirely another matter variable star we located in the 2M0421 data. It to try to determine the underlying cause. Radigan is difficult to exclude eclipsing binaries as a possi- et al. (2012) conclude that magnetic fields could ble cause of variability in a BD based on only one explain some variability in L and T BD’s, but argue observation. Follow up observations are generally it is less likely than other atmospheric sources. In required to confidently exclude it, since one would addition to previous discussions in the theory sec- expect to find a very consistent light curve, within tion about cloud-driven variability, there is also the the limits of photometric precision, when the tar- possibility that hot spots in the upper atmosphere get is re-observed at a later epoch. Furthermore is a driving factor. In this scenario hot parcels of the amplitude of the variability should be more or gas rise up higher into the atmosphere faster than less identical in multiple filters, which as previously the heat can dissipate into the now cooler section discussed should not be the case if the variability of the atmosphere. This would produce variabil- arose from varying conditions in the atmosphere. ity very similar to that of the cloud-driven kind, With PSO 318 being our primary focus when where you either have condensate clouds being re- it comes to further investigating variability in this sponsible for changes in opacity, or patchy clouds section, exploring potential binarity is a necessary where a lower, hotter part of the atmosphere tem- first step. We are however confident in excluding it porarily becomes visible. Morley et al. (2014) as a possible eclipsing binary based on the different review these two different options, and conclude light curves we obtain from three separate nights that the best way to discern between the possible of observation in two filters, and the work of Liu underlying processes is to take multi-wavelength et al. (2013) as well as recent RV measurements of observations that probe both inside and outside PSO 318 by Allers et al. (2016). the wavelength ranges where molecular absorption occurs. For example, methane features at 3.3µm 6.2 PSO 318 would probe the highest parts of the atmosphere, and could indicate heating by hot spots. This detection of variability in PSO 318 is unique for a number of reasons. It represents the largest Given the data we do have, there are a limited detected variability found outside the central parts amount of ways that we can continue with the anal- of the L/T transition, that has also been indepen- ysis. The typical modelling approach (e.g. Radi- dently verified. Wilson et al. (2014) reported am- gan et al. 2012) involves the combination of sev- plitudes of 9.4% and 9.6% in two BD’s, L1 and eral 1D models to represent different types of cloud L5.5, alongside claims of many other similar ampli- cover or hot spot activity. These can then be used tudes. As a result, Radigan (2014) independently to create synthetic spectra that can be compared reduced and analysed the same data, finding am- to spectra obtained from the target. The obser- 6 Discussion - 50 - Section 6.2 vations by Radigan et al. (2012) number nine in at high altitude, with AE in between. By combin- total, three of which were done in multiple wave- ing two A models with different Teff they obtain lengths. Thanks to this wealth of data they are a marginally better fit than the one shown here. able to do extensive modelling for their target, Replicating this modelling from our end would not which they admit is limited in its application due add much to the discussion, as synthetic fluxes to the interdependencies between effective temper- were used and the original spectra was taken more ature, condensate properties, surface gravity and than a year prior to these observations, so we other parameters involved in accurately modelling choose to use the models by Madhusudhan et al. these atmospheres. (2011) with a different goal in mind. B15 opt for using synthetic photon fluxes, pre- sumably because of the limited observations of As our most conclusive result from the first PSO PSO 318, obtained from the cloudy models pro- 318 observation is the amplitude of the variability, vided by Madhusudhan et al. (2011). These mod- we attempt to put some limits on the difference in els can be considered particularly suitable for PSO average Teff that is required to reproduce a differ- 318 as it is similar to the HR 8799 planets, having a ence in flux corresponding to our obtained ampli- low surface-gravity (log(g) = 3.86) and extremely tude, i.e. ∼ 10%. Doing this we are limited by the red colours as determined by Liu et al. (2013). available models, in that some have a finer temper- After correcting for the SOFI filter transmission ature resolution between each step in temperature. efficiency they apply various combinations of the Furthermore each model type (E, A, AE) does not models and compare with the spectra obtained for share the exact same temperature range, with the the discovery of PSO 318, with the result shown A models typically changing in steps of 100 K while below in Figure (48). the AE models are divided into 25 K steps below 1100 K. While log(g) is also a declared parameter for each model, it is also not uniformly applied, where the E models assume log(g) = 4.0 while the A, AE models also have come with log(g) = 3.75 or 3.8, respectively. Nonetheless we can make several observations from the models available to us. +30 As Liu et al. (2013) arrive at Teff = 1160−40 K for PSO 318 and Allers et al. (2016) esti- +24 mate Teff = 1127−26 K, we focus on models in the range 900-1300 K, from where we obtain 5 relevant E models, 17 AE and 9 A. Additionally we use the same grain size (60 µm) as used by B15. Put together, the models are denominated e.g. AE60.1200.cloud.g4.0. In the models, we isolate the wavelength range Figure 48: A plot by Biller et al. (2015) show- corresponding to the SOFI JS filter and sum the ing various 1D model spectra superimposed on flux in this region. As we are comparing the flux the spectra obtained from PSO 318 by Liu et al. between the models in relative terms, we do not (2013). The A60 model represents the atmosphere need to account for the transmission profile, as this with greatest cloud thickness and provides the best would be divided out in any regard. Through this fit. comparison we find that

For these models, the flux in the E model falls off i) at a lower log(g), e.g. 3.8 vs. 4.0, the flux in- sharply with increasing atmospheric altitude while creases more rapidly with Teff for both A and the A model represents maximum cloud thickness AE models. 6 Discussion - 51 - Section 6.3

ii) the relative flux increase for a given tempera- region, could show local differences in temperature ture difference of e.g. 100 K, decreases slowly of & 150 K as found by Radigan et al. (2012). (∼ 2%/100 K) with increasing Teff: Concluding this section, we turn to discussing our estimates of the rotation period of PSO 318. AE60.1200.cloud.g4.0 / AE60.1100.cloud.g4.0 After B15 presented their results, Allers et al. = 1.552 (2016) published their work based on RV measure- AE60.1100.cloud.g4.0 / AE60.1000.cloud.g4.0 ments of PSO 318. In addition to restricting the = 1.588 inclination of PSO 318, they constrain the period to 5-10.2 h which would seem to agree well with iii) the relative difference in flux is greater for A the estimate we get from the first JS observation models than AE, so that a difference of 100 K of PSO 318 in October 2014. It does not match leads to a ∼ 20% greater flux increase in the well with the much shorter period inferred from A models compared to AE. the November observation, which could indicate that the light curve was double peaked during this Now, by using the smallest temperature step of 25 epoch, caused by due to e.g. multiple hot spots or K in the AE models and statements i-iii) above, we patchy cloud covers. Until PSO 318 is re-observed, can estimate that a reasonable upper limit on the preferably for a longer duration, not much more change in average temperature ∆Tavg between the can be said on this matter for now, based on our ”hot” and ”cool” hemisphere of the object is ∼ 25 results. K. AE60.1050.cloud.g4.0 / AE60.1025.cloud.g4.0 = 1.125 would indicate that if ∆Tavg was much 6.3 HN Peg B greater than this, the relative difference in flux would be > 10%. This upper limit decreases fur- This observation merits further discussion given ther for lower log(g) and for the A model. One the extremely precise observations of HN Peg B small caveat to this process is that the E models performed by Metchev et al. (2015). Given such have a lower relative flux difference (iii)) than the a long period as 18 h, and a variability at the per- AE models, and as such a higher ∆Tavg could ap- cent level, one would not expect to observe much ply. However, as we have seen in Figure (48) the of a change, if any, during a mere 3.7 h. Detecting E models do not remotely replicate the observed two possible peaks during this time, assuming they spectrum and can likely be ignored for the pur- are real, would indicate a photosphere that is ei- poses of this argument. ther extremely patchy or the presence of many hot A crude lower limit could be estimated by cal- spots. While we can not argue as to the likelihood culating flux from black body spectra in the same of that occurring, we can consider an alternative wavelength range and determine which ∆Tavg cor- explanation for the shape of the light curve. responds to a difference in flux of < 10%. Doing This observation was, similarly to HD 106906 b, this one arrives at ∆Tavg ∼ 10 K. This estimate affected by the out of field presence of a host star. is of limited use, as the spectra of BD’s are not While the effect was seemingly much lower for HN well reproduced by a black body spectrum primar- Peg B, there were at least two visible rays that ily due to the presence of substantial molecular crossed the area of the detector where the target absorption. However, it can still serve as a lower was located. These can be seen faintly at the bot- estimate, as absorption would reduce the flux fur- tom in the finding chart (Figure 45). While we ther. So to conclude, based on the modelling op- removed the frames that were clearly affected by tions that we can reasonably apply in this work we the rays directly intersecting with the target, it is arrive at a range of 10 K . ∆Tavg . 25 K. Given possible that a lower degree of flux was present on that this is an average across the hemisphere facing either side of the rays, which thus could have im- us, it is not an unreasonable figure, and a hot spot, pacted the observed flux of the target to a lesser or patchy cloud structure showing a warmer lower degree. The fact that we observe two peaks could 6 Discussion - 52 - Section 6.4 be considered consistent with the passing of the two rays across the detector during the observa- tion. Furthermore, both passages happen shortly after each peak, at ∼ 0.8 h and ∼ 3.5 h respec- tively. More frames had to be removed from the second passage (frames #21-23 vs. #78-84), which could indicate a brighter ray, which correlates with the higher peak. At the time of writing we have not been able to fully investigate this hypothesis, therefore it re- mains a possibility for now. It is possible that by examining the stars near HN Peg B more closely, a similar pattern could be observed, even if they Figure 49: The light curve obtained by Biller et al. are located further away from the host star on the (2015) for the November observation of PSO 318 detector. It can also not be excluded that the in JS. Can be compared with our result seen in shape of the light curve is radically different at Figure (26). shorter wavelengths, as variability has been found to be wavelength dependent. Hopefully the re- Secondly, while we obtain a similar shape in observation of HN Peg B that took place in Au- the final light curve, ours shows rather substantial gust 2015 can help shed some light on this matter scatter by comparison, with a photometric error as well. ∼ 50% greater than the one estimated by B15. Af- ter this analysis, we suspect that the underlying 6.4 Photometric Precision and the Re- cause for these discrepancies is likely that whereas duction Process we combine two frames from different nod posi- tions. B15 either combine them from the same nod As we have seen during this work, there might position and do the sky subtraction with a separate be some difference in quality or decrease in preci- process, or treat each raw frame separately, only sion in some of our reduced frames for the PSO binning them as the light curves are constructed. 318 observation, as compared to B15. As such As a result, their raw reduced frames are closer in we feel it is appropriate to discuss some possible time to each other than ours, which are typically causes, and any potential impacts on our results separated by 4 minutes for a DIT of 10 s. Alter- as a whole. For the PSO 318 JS Oct. observation natively, their method of sky-subtraction is more there is a ∼ 30% difference in precision, with B15 precise, and as a result they obtain clearer data. obtaining an error estimate through their polyno- However, as we previously detailed, the issues we mial fitting that is 1/3 lower than what we obtain experienced with quality of the reduction in terms through either aperture photometry or polynomial of 3A+3B vs. A+B, did not affect the obtained fitting. Overall, the shapes of our obtained light light curve from the JS Oct. observation of PSO curve (Figure 25) is very similar to the one from 318 to any great extent, where the amplitude ob- B15 (Figure 4), and their JS Nov. light curve can tained for either option was 9−9.5%. Furthermore, also be seen in Figure (49). When it comes to the the KS Nov. data yielded identical error estimates longer DIT observations in November we can note as compared to B15, so we conclude that the is- some larger differences. sue pertains primarily to fainter objects with DIT’s Firstly, we were unable to obtain anything of use longer than 10 s. If we also look at 2M0342, which for the JS Nov. data during the original reduction has an apparent J magnitude of 16.85, compared using a 3A+3B combination of the jitter frames, to 16.71 mag for PSO 318, it seems to produce while A+B substantially improved the quality of somewhat better photometry (±1.5%) than the JS the photometry. Oct. observation of PSO 318. It is therefore pos- 6 Discussion - 53 - Section 6.6 sible that the atmospheric conditions during the left with 20 targets. For our significant variables +11 first observation of PSO 318 were simply such that we get fmin = 20−6 %, and if we include tentative this longer time between frames had an impact on variables at > 2σ, the minimum fraction becomes +12 the final precision of the photometry. fmin = 35−9 %. Finally, if we assume that all our In conclusion, given that a problem of lower significant and tentative detections are real, we get +8 precision primarily arises under seemingly specific fmin = 70−12%. This is more or less in line with +20 conditions for targets fainter than ∼ 16.7 J mag, Metchev et al. (2015), who find that 80−27% of we are very confident in the overall quality and re- L3-L9.5 BD’s vary with peak-to-peak amplitudes +26 sults of this survey, especially as the majority of > 0.2% and 36−17% of T0-T8 BD’s are variable at the targets were brighter than ∼ 16.1 mag. > 0.4%.

6.5 Frequency of Variability 6.6 Comparisons with Previous Works Out of 21 targets we find significant (> 3σ, p > In this section we put our target sample in a greater 99%) variability in 4 targets, tentative in 10 tar- context, starting with Figure (50) where we have gets (3: > 2σ, p > 95%, 7: > 1σ, p > 68%), as well included samples from three similar surveys. The as 7 non-detections of variability. As is common first, displayed as filled black circles, is R14 (Radi- practice when dealing with fractional occurrence gan 2014). Then follow the targets from Radigan rates, we obtain upper and lower limits to the min- et al. (2014) in empty circles for non-detections and filled ones for significant detections. We then imum variability frequency fmin in our sample by constructing a binomial confidence interval. We include the targets from M15 (Metchev et al. 2015) expect this to be a minimum, due to photomet- in empty and filled green circles. Finally, our own ric errors and limits in observing length, and due non-variable targets are displayed as empty circles, to other factors such as unresolved binarity and tentatively variable as filled red circles and signif- the geometric incompleteness effects described by icantly variable as magenta circles with PSO 318 Metchev et al. (2015). As they point out, the represented by the largest. Further details on how axis inclination of an object is relevant when con- some targets in the other works were distinguished sidering the rotational modulation of hotspots or can be found in the caption. patchy clouds, as it influences which parts of the As can be seen in the SpT vs. J-KS colour dia- atmosphere can be observed. gram, all our L-dwarfs are redder than most other To determine the binomial confidence interval BD’s, which is what one might expect given that at 1σ, we follow the procedure laid out in the ap- they are likely low-mass, many with signs of low- pendix to Burgasser et al. (2003). Using the bino- gravity, and have thick, cloudy atmospheres. GU mial distribution, for n number of occurrences in Psc b is unusually red for a T3.5 BD, while HN a sample of size N with the occurrence fraction f, Peg B is more or less in line with other T2.5 BD’s. The highest amplitude (3.6 ± 0.4%) found outside N! the L/T transition in these works was from the L6, B(n; N, f) = f n(1 − f)N−n n!(N − n)! J-KS ∼ 2, BD 2MASS J10101480-0406499, distin- guished as a slightly larger black circle in the R14 0 they compute B (f; n, N) ∝ B(n; N, f) for 0 ≤ sample. Our survey includes a large number of 0 f ≤ 1, and after normalizing obtain B = (N+1)B. early L0-L3 BD’s, that also shown signs of variabil- This can then be used to derive upper and lower ity, a spectral region where not that many had been U limits for the uncertainty f and fL, by calculat- observed previously. So while we can not further U ing R f B0df = R 1 B0df = 0.84, obtaining limits the statistics much for the important L/T tran- 0 fL equivalent to the 1σ limit for a Gaussian distribu- sition, the target sample is largely unique due to tion. For these limit estimates, f = n/N. its characteristics of low-mass and unusually red If we exclude our known binary, 2M0357, we are colours. 6 Discussion - 54 - Section 6.6

L0 R14 Significant detections L2 R14 et al. Non-detections R14 et al. Significant detections L4 M15 Non-detections M15 Significant detections L6 Non-Variable Tentatively variable L8 Significantly variable

T0

T2 Spectral Type T4

T6

T8

1.0 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 J-KS

Figure 50: Spectral type vs. J-KS colour diagram, showing the results of this work (red empty circles, filled red and magenta circles) as compared to R14 (Radigan 2014), R14 et al. (Radigan et al. 2014) and M15 (Metchev et al. 2015). For M15, the two larger filled circles represent amplitudes of 3% and 4.8%. For R14, the same applies for 4 objects with 2.9 - 5.9% and for R14 et al. 3 objects 4.3 - 9.0%. For this work, the largest magenta circle is PSO 318 and the others are 2M0045, 2M0117 and 2M0501.

+4.4 If we look closer at the previous works, Radi- (T4-T9.5) past the transition it becomes 3.2−2.3%. gan et al. (2014) find large amplitude variability With 17 targets inside the transition (L9-T3.5) the +11 (> 2%) exclusively in early T-dwarfs, with J-KS fraction is 24−9 %, indicating a much greater likeli- colours of 0.8 - 1.3 mag. Similarly, the two targets hood to find large amplitude variables in this spec- with large amplitude variability found by Metchev tral regime. Depending on how the L/T transition et al. (2015) consists of one T2.5 above 1.3 mag is defined, PSO 318 could be considered part of it, and one T6 BD below 0.8 mag. but according to this definition it lies outside the Radigan (2014), as part of their independent re- border and would therefore be unique. duction and investigation of the sample used by We can however note that all our large variables, Wilson et al. (2014), also combine a number of including tentative ones other than GU Psc b, lie different samples from other works and examine well outside the L/T transition, with PSO 318 be- the variability fraction in a total of 82 L, T BD’s. ing the closest at L7. Looking at targets that al- From this they find that large amplitude variabil- most qualify for the > 2% limit, 2M0117 is also +3.2 ity is detected in 7.3−2.5% of all targets (L0-T9.5). very far from the L/T transition, being a L1 with With 34 targets (L0-L8.5) prior to the L/T tran- J-KS of 1.7 mag. If we follow the strict > 2% +4.1 sition the fraction is 2.9−2.1% and with 31 targets limit and calculate the corresponding fraction for 7 Conclusions - 55 - Section 7.0 our sample (n = 5), including the tentative vari- components (Stone et al. 2016), making the sys- +12 ables, we get fmin = 25−7 %. So if the variability tem as a whole also interesting. in our tentative targets is real, it would represent Another is WISEA J114724.10204021.3, discov- a very significant increase in the variability frac- ered by Schneider et al. (2016). It is a free-floating tion for targets outside the L/T regime. Applying L7±1.0 BD with an estimated mass of 5 - 13 MJup, the same to only our one significant large ampli- J-KS colour of 2.57 mag and Teff ∼ 1100 − 1200 K. +9.8 tude variable (PSO 318) we get fmin = 5.0−1.6%, At ∼ 31 pc it is quite faint at 17.5 J mag but which would be more in line with the estimation represents an interesting target nonetheless as it from Radigan (2014). However, the fact remains could be a GP analogue similar to PSO 318. As that the large majority of our targets are outside new targets are continuously discovered, e.g. the the L/T transition as it is regularly defined, and L1 BD WISE J052857.69+090104.2 (Burgasser et several exhibit variability at the > 1.5−2.0% level. al. 2016), the prospects of coming surveys are im- Excluding our one resolved non-variable binary has proved. a negligible impact on these limits. Looking beyond the observation of more unique In regards to rotation periods, Metchev et al. and interesting objects, it is important to also in- (2015) find a broad range of in their sample, from clude long-period simultaneous multi-wavelength 1 to 20 hours. Radigan et al. (2014) obtain periods monitoring of these targets. It is likely only with of 1.4-10 h, so in relation to these our estimates, such combined data sets that we can find answers while limited, are reasonable. to the questions surrounding the underlying causes of variability. 6.7 Future Prospects In addition to further observations of some of 7 Conclusions the targets in our sample and others included in Throughout this work we have performed an in- the continuation of 194.C-0827(A), e.g. 2MASS dependent near-infrared photometric variability J14252798-3650229 (L5, J-KS = 1.94) and 2MASS study of 21 targets, with 20 in this sample being J20113196-5048112 (L3γ, J-KS = 1.84), we would observed in the ESO observing programme 194.C- expect many more surveys in the near future. 0827(A) by PI: Biller, B. These very low-mass As the number discoveries of BD’s in the GP brown dwarfs, many of which could be considered mass-regime continues to rise, we can expect Fig- high-mass giant planet analogues given their un- ure (50) to be populated with an ever increas- usually red J-KS colours and signs of low-gravity, ing number of interesting targets, both inside and were observed with on-sky times of ∼ 3 − 6 h. Out outside the L/T transition regime. Especially so of 19 L- and 2 T-dwarfs, 14 are found to be vari- if there indeed turns out to be a connection be- able at 0.6−9.3% with 12 being new and previously tween low-gravity, unusually red colours and thick unreported variables. We summarize our findings clouds leading to increased variability, as suggested below. by a number of both observational and modelling- focused works discussed previously. • We confirm the significant large amplitude One such interesting object is a newly discov- (> 2%) variability in the giant planet ana- ered and extremely red, J-KS = 2.47, companion to logue PSO J318.5338-22.8603, previously re- the nearby (∼ 12.7 pc) M dwarf VHS J125601.92- ported by Biller et al. (2015). We find peak- 125723.9. Discovered by Gauza et al. (2015), to-peak amplitudes of 9.3 ± 2.0% for the first VHS 1256-1257 b is a L7±1.5 BD with a mass of observation in JS, followed one month later +9.7 +140 11.2−1.8 MJup and model derived Teff = 880−110 by 4.3 ± 1.8% in JS with the night after show- K. It is located at a distance of > 100 AU from ing a continuous flux increase of 2.8 ± 0.7% in the primary, which was recently discovered to be KS. We estimate that the rotation period is at an unresolved 1.3 AU binary with two faint M7.5 least 5 h assuming a single-peaked light curve, 7 Conclusions - 56 - Section 7.0

but likely longer than 7 h, in line with re- analogue. This could be in line with local- cent RV measurements by Allers et al. (2016). ized temperature difference estimates by e.g. Overall, our period estimates of & 2 − 6 h are Radigan et al. (2012). in the 1 − 20 h range found by Metchev et al. (2015). While sometimes considered ”failed stars”, brown dwarfs do represent a bridge in the mass-gap be- • We furthermore find 3 other significantly vari- tween stars and planets and could help reveal able (> 99% confidence) targets with peak- crucial information about the formation of both. to-peak amplitudes of 1.1 − 1.9%, together Studying atmospheric variability in these objects, with 10 tentative variables (p > 68% & p > destined to be forever cooling down, can help re- 95%). The minimum variability fraction esti- veal properties and cloud formation processes that mated from the significantly variable sample +11 +8 influence their evolution down through the spectral is fmin = 20−6 %, with fmin = 70−12% when types. By also focusing on their very low-mass sib- all variable targets are included. When con- lings, like in this work, we could gain insights into sidering only large amplitude variables in our +12 the properties and evolution of giant planets which entire sample, we find that fmin = 25−7 %, are not as easily imaged. Continuing these sur- which when compared to previous works rep- veys with an increasing complexity in the form of resents an unusually high fraction for targets simultaneous multi-wavelength monitoring, along- outside the L/T transition. side the improvement of atmospheric modelling, we • When our sample is put into a larger context can attempt to discern if the underlying mechan- alongside several previous works (Figure 50) ics of variability involves cloud heterogeneities, hot it becomes clear that it is somewhat unique, spots or magnetic fields. Ultimately the methods mainly exploring the early-mid parts of the L- applied here might be useful for studying more gi- branch and containing mostly unusually red ant planets directly, and not only their free-floating objects. Combined with our estimated mini- analogues, with the intriguing possibility of one mum variability fractions our results could in- day applying them to terrestrial-like worlds. dicate that properties such as low-gravity al- lowing the formation of thick clouds that are Acknowledgements believed to be responsible for these unusually A sincere and heartfelt thanks to my supervi- red colours, also could promote higher ampli- sor Markus Janson, who always provided invalu- tudes or frequency of variability. able discussion and advice throughout this project. • Using the cloudy atmosphere models from With his help I was able to gain a burgeoning in- Madhusudhan et al. (2011) we attempt to sight into this complex field which has interesting put limits on the maximum average tempera- prospects for the future. I would also like to ac- ture difference, between the hemisphere with knowledge some of the excellent resources used in heterogeneous cloud cover and the one with this work. Among them the ESO archive for ob- homogeneous cloud cover, required to pro- taining observational data, the SAO/NASA ADS duce peak-to-peak amplitudes as those ob- publication query service and the SIMBAD as- served in PSO 318. Doing so we roughly es- tronomical database which all saw exhaustive use timate 10 K . ∆Tavg . 25 K for an atmo- throughout the project. Also included is the reduc- sphere with thick clouds, which is expected tion software and information made available by from planets like the ones in the HR 8799 sys- ESO through the SOFI and HAWK-I web pages, tem of which PSO 318 could be considered an and finally the 2MASS catalogue service. References - 57 -

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A Binned light curves & finding charts of non-variable targets

1.06 1.06 1.04 2M0103, MAX-MIN=0.011 1.04 RS4, MAX-MIN=0.014 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96

Relative Flux 0.94 0.94 1.06 1.06 1.04 RS5, MAX-MIN=0.008 1.04 RS6, MAX-MIN=0.01 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.94 0.94 1.06 0 1 2 3 4 5 1.04 RS8, MAX-MIN=0.006 Elapsed Time [h] 1.02 1.00 0.98 0.96 0.94 0 1 2 3 4 5 Elapsed Time [h]

Figure 51: Binned light curves and finding chart for the 2M0103 observation, with airmass changing from 2.22 to 2.18 throughout, with a low point at 1.52. Photometry was done with a 4.75 pixel aperture and a MAX - MIN amplitude of 1.1 ± 1.3% was obtained from the binned light curve. With the knowledge that Metchev et al. (2015) detected 0.6 − 0.9% variability with a 2.7 h period, one can perhaps see this shape in the light curve, but that is not enough for us to categorize this as tentatively variable based on our results.

1.02 1.02 2M0234, MAX-MIN=0.005 RS10, MAX-MIN=0.006 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 Relative Flux 0 1 2 3 4 5 1.02 RS12, MAX-MIN=0.006 Elapsed Time [h] 1.01 1.00 0.99 0.98 0 1 2 3 4 5 Elapsed Time [h]

Figure 52: Binned light curves and finding chart for the 2M0234 observation, with airmass changing from 1.23 to 1.97 throughout. Photometry was done with a 5.50 pixel aperture and a MAX - MIN amplitude of 0.5±0.6% was obtained from the binned light curve. No aperture or RS selection indicates any clear trends in potential and the L-S periodogram gives the weakest response of all targets, and it is therefore categorized as non-variable. Appendix - 62 -

1.03 1.03 1.02 2M0323, MAX-MIN=0.003 1.02 RS9, MAX-MIN=0.01 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 1.03 1.03 1.02 RS10, MAX-MIN=0.004 1.02 RS11, MAX-MIN=0.01 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h]

Figure 53: Binned light curves and finding chart for the 2M0323 observation, with airmass changing from 1.08 to 1.62 throughout. Photometry was done with a 6.00 pixel aperture and a MAX - MIN amplitude of 0.3 ± 0.7% was obtained from the binned light curve. It is possible to see a shape of what could be sinusoidal variability in this target, but given that the amplitude is extremely low and well below any error estimate, we clearly categorize this as a non-variable.

1.03 1.03 1.02 2M0357, MAX-MIN=0.006 1.02 RS6, MAX-MIN=0.008 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98

Relative Flux 0.97 0.97 1.03 1.03 1.02 RS7, MAX-MIN=0.007 1.02 RS8, MAX-MIN=0.003 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h]

Figure 54: Binned light curves and finding chart for the 2M0357 observation, with airmass changing from 1.14 to 1.14 throughout, with a low point at 1.04. Photometry was done with a 6.00 pixel aperture and a MAX - MIN amplitude of 0.6 ± 0.5% was obtained from the binned light curve. This places it on the edge between non-variable and tentatively variable according to our definition. We categorize it as non-variable as it has a MAX - MIN value of 0.3% for 2.5 hours and due to the fact that the observation suffered from weather effects following this point in the time-series. There is no consistent overall shape that can be obtained for any particular aperture or RS configuration. Appendix - 63 -

1.03 1.03 1.02 2M0518, MAX-MIN=0.005 1.02 RS8, MAX-MIN=0.002 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 1.03 1.03 1.02 RS9, MAX-MIN=0.002 1.02 RS10, MAX-MIN=0.003 1.01 1.01 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h]

Figure 55: Binned light curves and finding chart for the 2M0518 observation, with airmass changing from 1.19 to 1.06 throughout. Photometry was done with a 6.50 pixel aperture and a MAX - MIN amplitude of 0.5 ± 0.7% was obtained from the binned light curve. There are some hints of possible sinusoidal variability in the curve, but they are very faint. Given the extremely stable reference stars and lack of indications to the contrary, we consider this target to be non-variable.

1.04 1.04 2M2322, MAX-MIN=0.006 RS2, MAX-MIN=0.011 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 Relative Flux 1.04 1.04 RS4, MAX-MIN=0.014 RS5, MAX-MIN=0.014 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96

1.04 1.04 RS7, MAX-MIN=0.01 RS8, MAX-MIN=0.011 1.02 1.02 1.00 1.00 0.98 0.98 0.96 0.96 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Elapsed Time [h] Elapsed Time [h]

Figure 56: Binned light curves and finding chart for the 2M2322 observation, with airmass changing from 1.27 to 1.31 throughout, with a low point at 1.18. Photometry was done with a 5.00 pixel aperture and a MAX - MIN amplitude of 0.6 ± 1.1% was obtained from the binned light curve. As has been previously discussed, this observation suffered from exceedingly poor weather and based on the data we do have, we see no indications of any variability that we can detect under these circumstances and classify it as a non-variable. Appendix - 64 -

1.3 1.3 1.2 HD 106906 b, MAX-MIN=0.159 1.2 Ctrl. Star "C", MAX-MIN=0.081 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8

Relative Flux 0.7 0.7 1.3 1.3 1.2 RS1, MAX-MIN=0.012 1.2 RS17, MAX-MIN=0.009 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 1.3 1.3 1.2 RS18, MAX-MIN=0.009 1.2 RS19, MAX-MIN=0.012 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h] Elapsed Time [h]

Figure 57: Binned light curves and finding chart for the HD 106906 observation in J, including the control star C, with airmass changing from 1.41 to 1.19 throughout. Photometry was done with a 4.00 pixel aperture, limited by the reduction process, and a MAX - MIN amplitude of 15.9 ± 1.3% was obtained from the binned light curve. Despite this ”variability”, we have no choice but to classify it as a non-variable due to the poor quality of the data. A more in-depth discussion behind our reasoning can be found in §5.3.

1.03 1.03 1.02 1.02 1.01 2M0045, MAX-MIN=0.011 1.01 RS1, MAX-MIN=0.006 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 Relative Flux 1.03 1.03 1.02 1.02 1.01 RS2, MAX-MIN=0.006 1.01 RS3, MAX-MIN=0.022 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 1.03 1.03 1.02 1.02 1.01 RS4, MAX-MIN=0.01 1.01 RS5, MAX-MIN=0.009 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 1.03 1.03 1.02 1.02 1.01 RS6, MAX-MIN=0.016 1.01 RS7, MAX-MIN=0.021 1.00 1.00 0.99 0.99 0.98 0.98 0.97 0.97 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h]

Figure 58: Binned light curves of the significantly variable 2M0045 with all RS included, exemplifying the choice between quantity and quality. The top left data-point, and the ones near 1.7 h, in the target and RS1 & RS2 shows the effect of scatter induced by other RS. Appendix - 65 -

B Polynomial subtraction results for tentative & non-variable tar- gets

2M0103, MAX - MIN = 0.011 σphot = 0.013 2M0234, MAX - MIN = 0.005 σphot = 0.006 1.06 0.03 0.015 1.02 1.04 P(2) 0.02 SD = 0.010 P(2) 0.010 SD = 0.004 1.02 0.01 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.01 0.99 0.005 0.96 0.02 0.98 0.010 Relative Flux 0.94 0.03 Relative Flux 0.015 1.06 0.03 0.015 1.02 1.04 P(3) 0.02 SD = 0.010 P(3) 0.010 SD = 0.004 1.02 0.01 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.01 0.99 0.005 0.96 0.02 0.98 0.010 0.94 0.03 0.015 1.06 0.03 0.015 1.02 1.04 P(4) 0.02 SD = 0.010 P(4) 0.010 SD = 0.004 1.02 0.01 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.01 0.99 0.005 0.96 0.02 0.98 0.010 0.94 0.03 0.015 1.06 0.03 0.015 1.02 1.04 P(5) 0.02 SD = 0.010 P(5) 0.010 SD = 0.004 1.02 0.01 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.01 0.99 0.005 0.96 0.02 0.98 0.010 0.94 0.03 0.015 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

2M0303, MAX - MIN = 0.026 σphot = 0.014 2M0323, MAX - MIN = 0.003 σphot = 0.007 0.06 1.03 0.015 1.06 0.010 1.04 P(2) 0.04 SD = 0.014 1.02 P(2) SD = 0.005 1.02 0.02 1.01 0.005 1.00 1.00 0.000 0.98 0.00 0.99 0.005 0.96 0.02 0.98 0.010 0.94 0.97 Relative Flux 0.04 Relative Flux 0.015 0.06 1.03 0.015 1.06 0.010 1.04 P(3) 0.04 SD = 0.014 1.02 P(3) SD = 0.005 1.02 0.02 1.01 0.005 1.00 1.00 0.000 0.98 0.00 0.99 0.005 0.96 0.02 0.98 0.94 0.010 0.04 0.97 0.015 1.03 0.015 1.06 0.04 0.010 1.04 P(4) SD = 0.014 1.02 P(4) SD = 0.005 1.02 0.02 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.02 0.99 0.005 0.96 0.98 0.94 0.04 0.010 0.97 0.015 1.03 0.015 1.06 0.04 0.010 1.04 P(5) SD = 0.013 1.02 P(5) SD = 0.005 1.02 0.02 1.01 0.005 1.00 0.00 1.00 0.000 0.98 0.02 0.99 0.005 0.96 0.98 0.94 0.04 0.010 0.97 0.015 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

2M0326, MAX - MIN = 0.019 σphot = 0.012 2M0342, MAX - MIN = 0.022 σphot = 0.015 1.06 0.020 1.06 0.04 0.015 1.04 0.03 1.04 P(2) 0.010 SD = 0.008 P(2) 0.02 SD = 0.015 1.02 0.005 1.02 0.01 1.00 0.000 1.00 0.00 0.98 0.005 0.98 0.01 0.010 0.02 0.96 0.96 0.94 0.015 0.03 Relative Flux 0.020 Relative Flux 0.94 0.04 1.06 0.020 1.06 0.05 0.015 1.04 0.04 1.04 P(3) 0.010 SD = 0.008 P(5) 0.03 SD = 0.015 1.02 1.02 0.02 0.005 0.01 1.00 0.000 1.00 0.00 0.98 0.005 0.98 0.01 0.96 0.010 0.02 0.015 0.96 0.03 0.94 0.020 0.94 0.04 1.06 0.020 1.06 0.04 0.015 1.04 0.03 1.04 P(4) 0.010 SD = 0.008 P(7) 0.02 SD = 0.015 1.02 0.005 1.02 0.01 1.00 0.000 1.00 0.00 0.98 0.005 0.98 0.01 0.96 0.010 0.02 0.015 0.96 0.03 0.94 0.020 0.94 0.04 1.06 0.020 1.06 0.04 0.015 1.04 0.03 1.04 P(5) 0.010 SD = 0.008 P(8) 0.02 SD = 0.015 1.02 0.005 1.02 0.01 1.00 0.000 1.00 0.00 0.98 0.005 0.98 0.01 0.96 0.010 0.02 0.015 0.96 0.03 0.94 0.020 0.94 0.04 0 1 2 3 4 0 1 2 3 4 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

Figure 59: Polynomial subtraction plots part I. Appendix - 66 -

2M0355, MAX - MIN = 0.006 σphot = 0.004 2M0357, MAX - MIN = 0.006 σphot = 0.005 1.03 0.010 1.03 0.010 1.02 P(2) 0.005 SD = 0.003 1.02 P(2) 0.005 SD = 0.003 1.01 1.01 0.000 1.00 0.000 1.00 0.99 0.005 0.005 0.99 0.98 0.98 0.010 Relative Flux 0.97 0.010 Relative Flux 0.97 0.015 1.03 0.008 1.03 0.010 1.02 0.006 1.02 P(4) 0.004 SD = 0.003 P(3) 0.005 SD = 0.003 1.01 0.002 1.01 1.00 0.000 1.00 0.000 0.99 0.002 0.99 0.004 0.005 0.98 0.006 0.98 0.97 0.008 0.97 0.010 1.03 0.008 1.03 0.010 1.02 0.006 1.02 P(5) 0.004 SD = 0.003 P(4) 0.005 SD = 0.003 1.01 0.002 1.01 1.00 0.000 1.00 0.000 0.99 0.002 0.99 0.004 0.005 0.98 0.006 0.98 0.97 0.008 0.97 0.010 1.03 0.008 1.03 0.010 1.02 0.006 1.02 P(6) SD = 0.002 P(5) 0.005 SD = 0.003 1.01 0.004 1.01 0.002 1.00 0.000 1.00 0.000 0.99 0.99 0.002 0.005 0.98 0.004 0.98 0.97 0.006 0.97 0.010 0 1 2 3 4 0 1 2 3 4 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] σ 2M0421, MAX - MIN = 0.008 phot = 0.007 2M0518, MAX - MIN = 0.005 σphot = 0.007 1.03 0.010 0.025 1.02 1.03 0.020 P(2) 0.005 SD = 0.004 1.02 P(2) 0.015 SD = 0.006 1.01 0.000 1.01 0.010 1.00 0.005 0.005 1.00 0.000 0.99 0.99 0.005 0.98 0.010 0.98 0.010 0.015

Relative Flux 0.97 0.97 0.015 Relative Flux 0.020 1.03 0.010 1.03 0.020 1.02 P(3) SD = 0.004 0.015 0.005 1.02 P(3) 0.010 SD = 0.006 1.01 0.000 1.01 0.005 1.00 1.00 0.000 0.99 0.005 0.99 0.005 0.010 0.98 0.010 0.98 0.015 0.97 0.015 0.97 0.020 1.03 0.010 1.03 0.020 1.02 0.015 P(4) 0.005 SD = 0.004 1.02 P(4) 0.010 SD = 0.006 1.01 0.000 1.01 0.005 1.00 1.00 0.000 0.99 0.005 0.99 0.005 0.010 0.98 0.010 0.98 0.97 0.015 0.97 0.015 0.020 1.03 0.010 1.03 0.020 1.02 P(5) 0.015 SD = 0.006 P(5) 0.005 SD = 0.004 1.02 0.010 1.01 1.01 0.005 1.00 0.000 1.00 0.000 0.99 0.99 0.005 0.98 0.005 0.98 0.97 0.010 0.97 0.010 0.015 0 1 2 3 4 5 0 1 2 3 4 5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

2M0536, MAX - MIN = 0.01 σphot = 0.010 2M2224, MAX - MIN = 0.007 σphot = 0.004 1.03 0.025 1.03 0.008 0.020 1.02 0.006 1.02 P(2) 0.015 SD = 0.007 P(2) 0.004 SD = 0.003 1.01 0.010 1.01 0.002 1.00 0.005 1.00 0.000 0.99 0.000 0.99 0.002 0.005 0.004 0.98 0.98 0.97 0.010 0.006 Relative Flux 0.015 Relative Flux 0.97 0.008 1.03 0.025 1.03 0.008 0.020 1.02 0.006 1.02 P(3) 0.015 SD = 0.007 P(3) 0.004 SD = 0.003 1.01 0.010 1.01 0.005 0.002 1.00 0.000 1.00 0.000 0.99 0.005 0.99 0.002 0.98 0.010 0.004 0.015 0.98 0.006 0.97 0.020 0.97 0.008 1.03 0.025 1.03 0.008 0.020 1.02 0.006 1.02 P(4) 0.015 SD = 0.007 P(4) 0.004 SD = 0.003 1.01 0.010 1.01 0.002 1.00 0.005 1.00 0.000 0.99 0.000 0.99 0.002 0.98 0.005 0.004 0.010 0.98 0.006 0.97 0.015 0.97 0.008 1.03 0.025 1.03 0.008 0.020 1.02 0.006 1.02 P(5) 0.015 SD = 0.006 P(5) 0.004 SD = 0.003 1.01 0.010 1.01 0.002 1.00 0.005 1.00 0.000 0.99 0.000 0.99 0.002 0.98 0.005 0.004 0.010 0.98 0.006 0.97 0.015 0.97 0.008 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

Figure 60: Polynomial subtraction plots part II. Appendix - 67 -

GU Psc b, MAX - MIN = 0.066 σphot = 0.037 2M2322, MAX - MIN = 0.006 σphot = 0.011 0.03 1.2 0.15 1.04 P(2) SD = 0.042 P(2) 0.02 SD = 0.009 1.1 0.10 1.02 0.01 0.05 1.0 1.00 0.00 0.00 0.01 0.98 0.9 0.05 0.02

0.96 Relative Flux 0.8 Relative Flux 0.03 0.10 0.025 1.2 0.15 1.04 0.020 P(3) 0.10 SD = 0.042 P(3) 0.015 SD = 0.009 1.1 1.02 0.010 0.05 0.005 1.00 0.000 1.0 0.00 0.005 0.05 0.98 0.010 0.9 0.96 0.015 0.10 0.020 0.8 0.15 0.03 0.15 1.04 1.2 P(4) 0.02 SD = 0.009 P(4) 0.10 SD = 0.042 1.02 1.1 0.01 0.05 1.00 0.00 1.0 0.01 0.00 0.98 0.9 0.96 0.02 0.05 0.03 0.8 0.10 0.025 1.04 0.020 1.2 0.15 P(5) 0.015 SD = 0.009 P(5) 0.10 SD = 0.041 1.02 0.010 1.1 0.005 0.05 1.00 0.000 1.0 0.98 0.005 0.00 0.010 0.9 0.96 0.015 0.05 0.020 0.8 0.10 0.00.51.01.52.02.53.03.54.04.5 0.00.51.01.52.02.53.03.54.04.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

HD 106906 b, MAX - MIN = 0.159 σphot = 0.013 HN Peg B, MAX - MIN = 0.015 σphot = 0.011 1.3 0.20 0.03 1.2 0.15 1.03 P(2) SD = 0.069 1.02 P(2) 0.02 SD = 0.008 1.1 0.10 0.05 1.01 0.01 1.0 0.00 1.00 0.00 0.9 0.05 0.99 0.01 0.8 0.10 0.98 0.02

Relative Flux 0.97 0.7 0.15 Relative Flux 0.03 1.3 0.20 0.025 1.03 0.020 1.2 P(3) 0.15 SD = 0.069 P(3) SD = 0.008 0.10 1.02 0.015 1.1 1.01 0.010 0.05 0.005 1.0 0.00 1.00 0.000 0.9 0.99 0.005 0.05 0.98 0.010 0.8 0.10 0.015 0.7 0.15 0.97 0.020 1.3 0.15 0.025 1.03 0.020 1.2 P(4) 0.10 SD = 0.059 1.02 P(4) 0.015 SD = 0.008 1.1 0.05 1.01 0.010 0.005 1.0 0.00 1.00 0.000 0.9 0.05 0.99 0.005 0.8 0.10 0.98 0.010 0.97 0.015 0.7 0.15 0.020 1.3 0.15 0.025 1.03 0.020 1.2 P(5) 0.10 SD = 0.058 1.02 P(5) 0.015 SD = 0.008 1.1 0.05 1.01 0.010 0.005 1.0 0.00 1.00 0.000 0.9 0.05 0.99 0.005 0.98 0.010 0.8 0.10 0.97 0.015 0.7 0.15 0.020 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Elapsed Time [h] Elapsed Time [h] Elapsed Time [h] Elapsed Time [h]

SIMP2154, MAX - MIN = 0.027 σphot = 0.014 0.04 1.06 0.03 1.04 P(2) 0.02 SD = 0.014 1.02 0.01 1.00 0.00 0.98 0.01 0.96 0.02 0.94 0.03 Relative Flux 0.04 0.04 1.06 0.03 1.04 P(3) 0.02 SD = 0.014 1.02 0.01 1.00 0.00 0.98 0.01 0.96 0.02 0.03 0.94 0.04 0.04 1.06 0.03 1.04 P(4) 0.02 SD = 0.013 1.02 0.01 1.00 0.00 0.98 0.01 0.96 0.02 0.03 0.94 0.04 0.04 1.06 0.03 1.04 P(5) 0.02 SD = 0.013 1.02 0.01 1.00 0.00 0.98 0.01 0.96 0.02 0.03 0.94 0.04 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Elapsed Time [h] Elapsed Time [h]

Figure 61: Polynomial subtraction plots part III. Appendix - 68 -

C L-S periodograms for tentative & non-variable targets

2M0103 - Best Fit Period = 1.0 h 2M0234 - Best Fit Period = 8.1 h 2M0303 - Best Fit Period = 18.5 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 2 4 6 8 10 2 4 6 8 10 2 4 6 8 10 Period [h] Period [h] Period [h] 2M0323 - Best Fit Period = 1.1 h 2M0326 - Best Fit Period = 6.4 h 2M0342 - Best Fit Period = 3.1 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 2 4 6 8 10 2 4 6 8 1 2 3 4 5 6 Period [h] Period [h] Period [h] 2M0355 - Best Fit Period = 2.9 h 2M0357 - Best Fit Period = 1.7 h 2M0421 - Best Fit Period = 5.7 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 2 4 6 8 10 Period [h] Period [h] Period [h] 2M0518 - Best Fit Period = 0.6 h 2M0536 - Best Fit Period = 2.4 h 2M2224 - Best Fit Period = 2.6 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 1 2 3 4 5 6 7 1 2 3 4 5 1 2 3 4 5 6 7 Period [h] Period [h] Period [h]

Figure 62: Lomb-Scargle periodograms part I. Appendix - 69 -

2M2322 - Best Fit Period = 0.6 h GU Psc b - Best Fit Period = 13.8 h HD 106906 b - Best Fit Period = 0.5 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 Period [h] Period [h] Period [h] Control star "C" - Best Fit Period = 5.2 h HN Peg B - Best Fit Period = 3.3 h SIMP2154 - Best Fit Period = 8.6 h 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4 Lomb-Scargle Power Lomb-Scargle Power 0.2 0.2 Lomb-Scargle Power 0.2

0.0 0.0 0.0 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 Period [h] Period [h] Period [h]

Figure 63: Lomb-Scargle periodograms part II.