arXiv:1603.03274v2 [astro-ph.EP] 15 Mar 2016 aih15 eecp tteEOL il observatory. Silla La ESO the at telescope m 1.54 Danish D i nnmu t ocsr.-tab.r(130.79.128. cdsarc.u-strasbg.fr to ftp http: anonymous via CDS h odnaino csi h ici - ufrSlrtp s Solar-type for au 4-5 is lim disc inner the The in 1996). ices al. of et condensation (Pollack the formation their volatil to in frozen with vital form disc, should protoplanetary a giants of gas regions outer that the muc states orbi by which predicted Their au, distances model, System. formation an accretion Solar planet with of own in our fractions fit in not at do giants gas stars the Jupiter host than to their closer similar orbiting masses with found giants intens are gas of are subject planets the these been – has planets many Jupiters, of posed hot group One the has formed. particular, are exoplanets planets how of about observation questions and discovery The Introduction 1. .F Evans F. D. ⋆⋆ etme 0 2018 10, September Astronomy ⋆ .Lcyiaigosrain f11ssesi h southern the in systems 101 of observations imaging Lucky I. Jaimes ae ndt olce yteMNSE osrimuigthe using consortium MiNDSTEp the by collected data on Based als1 ,ad8aeol vial neetoi oma the at form electronic in available only are 8 and 4, 1, Tables // Alsubai cdsweb.u-strasbg.fr esrd o 2cniaecmain o1 otsas prev stars, associated. host physically 10 be to to are companions companions candidate 12 For measured. e words. Key unconstra is companions stellar close-in of population the o h omto fhtJupiters. hot of in We formation companions. the for stellar for searched st systematically background been contaminating and stars companion bound both o h lt cl n oorpromneo h w oorI Colour Two the of performance colour and an star, scale host plate a the of for arcseconds 5 within located are candidates Conclusions. Results. Methods. Aims. a significantly exoplanets. can stars theori unresolved formation from competing between discriminator portant Context. eouin–bnre:visual binaries: – resolution erhfrpeiul neovdsasa ml nua sep angular small at stars unresolved previously for search apeo edsas ogpro tla opnos( companions stellar period do Long stars. formation field planet of that sample suggesting range, sensitivity our Ku Snodgrass ihrslto mgn fTastn xrslrPlaneta Extrasolar Transiting of Imaging High-resolution 4 ff , eosre 0 rniigeolnths ytm nteSou the in systems host exoplanet transiting 101 observed We meier 12 1 & 5 .Southworth J. , .H Gu S.-H. , epoiemaueet f49cniaecmain within companions candidate 499 of measurements provide We iebnre r oeta aha o h omto fho of formation the for pathway potential a are binaries Wide .I Andersen I. M. , uk mgn bevtosfo h w oorIsrmn o Instrument Colour Two the from observations imaging Lucky Astrophysics 3 lnt n aelts yaia vlto n stability and evolution dynamical satellites: and planets efidta h vrl utpiiyrt ftehs tr is stars host the of rate multiplicity overall the that find We 24 .Mancini L. , .Starkey D. , / cgi-bin 13 , 14 aucitn.hitepAccepted_20160309 no. manuscript / .Haugbølle T. , 1 qcat?J .F .Maxted L. F. P. , 6 10 .Bozza V. , 4 .Peixinho N. , .Surdej J. , / A + A / ff c h cuayo htmti n pcrsoi measurem spectroscopic and photometric of accuracy the ect (A 7 3 , 25 8 ffi .C Hinse C. T. , .M Bramich M. D. , .Tronsgaard R. , itoscnb on fe h references) the after found be can liations ytm (HITEP). systems 19 1 .Skottfelt J. , , 20 .Popovas A. , P eevd- cetd- accepted -; Received )o via or 5) sbeing es study e > ndb u study. our by ined rtos h eaain n eaiemgiue falde all of magnitudes relative and separations The arations. sntpeeetal cu nln eidbnre compare binaries period long in occur preferentially not es epoietefis ulse esrmnsfr2 fthese. of 27 for measurements published first the provide we d s u a o enwl hrceie.Adtoal,cont Additionally, characterised. well been not has but es, tfor it etgt h iayfato mn h otsasi re t order in stars host the among fraction binary the vestigate 0y)apa oocridpnetyo hr eidcompani period short of independently occur to appear yr) 10 ABSTRACT but , core tars 15 the r,i nae ftesyweetastn xpaeaysyst exoplanetary transiting where sky the of area an in ars, srmn r presented. are nstrument in ts osatoercmaueet eeue oeaut o lik how evaluate to used were measurements astrometric ious h .Juncher D. , 2 , 26 3 5 .Hundertmark M. , .J Burgdorf J. M. , eti ris(u&Mra 03,o hs ihobt hta that orbits with in those Jupiters or hot 2003), mi- of Murray disc & number (Wu simple the orbits the period explain centric However, to a 1996). fails al. with theory et orbit (Lin gration days well-circularised few Thi a a star. alternatively in only host or the result its disc, and by would the planet cess stopped the of to- be between edge inwards interactions then inner tidal spiral would the migration and reaching This momentum planet caus star. angular disc, the lose protoplanetary wards to wo the planet Initial with (2014). the l interactions al. on et on on Davies reviews and focused by recent (2014), processes the al. dynamical et see Baruteau term mod – by accretion inwards interactions core migrated the planet-disc by since predicted have as and stars, host their from ov ictmeaue vr150 Lne l 96,toho too exist. 1996), to al. material et solid (Lin any 1,500K almost for over woul temperatures Jupiters hot disc of volve formation in-situ whereas 1995), (Boss hr eipeei re ocet ooeeu catalogue homogeneous a create to order in hemisphere thern .vnEssen von C. , 3 .Rabus M. , lnt n aelts omto ehius ihangu high techniques: – formation satellites: and planets – ti o ieyblee hthtJptr ntal formed initially Jupiters hot that believed widely now is It uies h iayfato mn otsasi nim- an is stars host among fraction binary The Jupiters. t 38 0aceod forsml f11pae otsas 51 stars. host planet 101 of sample our of arcseconds 20 h aih15mtlsoea aSlawr sdto used were Silla La at telescope 1.54m Danish the n − + 13 17 3 .Kains N. , ,cnitn ihtert mn oa-yesasin stars solar-type among rate the with consistent %, 21 26 , 10 9 iB Wang Yi-Bo , .Ciceri S. , .Rahvar S. , 3 .G Jørgensen G. U. , 16 .Kerins E. , 10 22 .D’Ago G. , 13 nsi tde ftransiting of studies in ents .W Schmidt W. R. , 17 , hemisphere 14 .Korhonen H. , ril ubr ae1o 20 of 1 page number, Article n .Wertz O. and , 3 .Dominik M. , etdsaswere stars tected 11 mntn light aminating oarandom a to d ettheories test o .Figuera R. , m aenot have ems Calibrations n,adso and ons,
23 c ry l the ely 18 S 2018 ESO C. , 25 , ⋆⋆ ⋆ 4 3 lar of .A. K. , M. , pro- s in- d ong ing ec- far by el, of rk re t A&A proofs: manuscript no. hitepAccepted_20160309 retrograde or misaligned compared to the rotation of their host nating stars using various forms high resolution imaging, which stars (Wu & Murray 2003; Fabrycky & Tremaine 2007). Whilst were compared to one another by Lillo-Box et al. (2014). misaligned protoplanetary discs provide a possible pathway for If a planet does indeed exist, blended light can still cause this (e.g. Bate et al. 2010), observational studies have found that problems, due to diluted transits leading to incorrect determina- discs are generallywell aligned to their host stars, as are the plan- tions of planetary properties. An extreme case is that of Kepler- ets within the discs (Watson et al. 2011; Greaves et al. 2014). 14b, where both photometric and spectroscopic measurements ′′ Gravitational interactions with a third body can also cause were affected by a companion star at 0.3 separation, causing changes in a planet’s orbit. Outer planets can cause planet-planet the planetary mass and radius to be underestimated by 10% and scattering events (Rasio & Ford 1996; Chatterjee et al. 2008), 60% respectively if the companion was not taken into account whilst inclined planetary or stellar companions can force the in- (Buchhave et al. 2011). A similar analysis was performed by ner planet to undergo Kozai-Lidov oscillations, in which it is Daemgen et al. (2009) for the WASP-2, TrES-2 and TrES-4 sys- forced through alternating phases of high eccentricity and high tems, with the planetary parameters changing by up to 2σ when inclination (Wu & Murray 2003; Fabrycky & Tremaine 2007; contaminating light from nearby stars was taken into account. Naoz et al. 2011). These pathways are able to explain eccen- In this paper, we present high resolution observations of 101 tric and misaligned hot Jupiters, but require a population of southern hemisphere systems containing transiting hot Jupiters. outer companions. Hot Jupiters rarely have nearby planetary These were used to search for nearby stars, either those phys- companions (Steffen et al. 2012), and so if gravitational inter- ically associated with the systems, or background objects that actions are the main origin of such planets, many systems would contribute contaminating light. We also present follow-up obser- have to be wide stellar binaries. The host stars are generally vations of several previously discovered binary candidates, in- Sun-like FGK dwarfs, which have a multiplicity rate of 44±2% cluding analyses of the common proper motion of the candidates (Raghavan et al. 2010), but the binary distribution among known where sufficient data are available. The distribution of stars de- hot Jupiter host stars is very likely to be different. Close bi- tected in our survey are compared to a statistical model in order naries are selected against in planet-hunting surveys, due to to estimate the multiplicity rate among our targets, and this is the difficulty of detecting and characterising a planet in such a compared to the rate among solar-type stars, and previous esti- system. Additionally, there is evidence that close binaries in- mations of the multiplicity rate among planet host stars. hibit planet formation (Fragner et al. 2011; Roell et al. 2012; Wang et al. 2014). However, if gravitational interactions with a 2. Observations distant binary companion are a common migration pathway it would be expected that the binary fraction would be significantly The observations were carried out between April and Septem- enhanced. ber 2014 using the Two Colour Instrument (TCI) at the Danish To date, several studies have attempted to estimate the multi- 1.54m telescope, La Silla, Chile. The TCI is a lucky imager de- plicity rate among exoplanet host stars, but the results have been signed for simultaneous two-colour photometry, using Electron wildly disparate. At the low end, Roell et al. (2012) reported that Multiplying CCD (EMCCD) detectors. We give a brief summary as few as 12% of hot Jupitersmay be in multiplesystems; in con- of the instrument, with a more detailed description available in trast, Ngo et al. (2015) estimate a binary rate of 51% from direct Skottfelt et al. (2015b). The light arriving at the instrument is imaging alone, which is raised even higher when combined with split between the two cameras using a dichroic with a cut-off radial velocity results from Knutson et al. (2014). However, it is wavelength of 655nm. A second dichroic sends blue light short- difficult to compare direct imaging surveys, due to differences in ward of 466nm towards a focus system. The TCI is not equipped sensitivity to companions and the area of the sky searched – it with filters, and so the light received by each camera is deter- would therefore be advantageous to survey or re-analyse a large mined solely by the dichroics. The ‘visual’ camera receives light number of systems in a homogeneous manner, in order to create between 466nm and 655nm, and the ’red’ camera receives all a large sample of systems from which patterns and trends can be light redward of 655nm, with the EMCCD detectors able to de- easily identified. tect light out to approximately 1050nm. We denote the two pass- bands v TCI and r TCI for the visual and red cameras respectively. ff Transit searches su er from a high rate of astrophysical false As shown in Fig. 1, r TCI is comparable to the combination of the positives (Brown 2003), and eclipsing binary (EB) systems have SDSS i′ and z′ filters, or a Cousins I filter with a wider passband, proved to be a troublesome source of transit-like events, with pe- whilst v TCI has a similar central wavelength to the Johnson V riods and eclipse durations similar to those of hot Jupiters. The filter but with a significantly different response curve. For both depths of the eclipses in these systems are generally much larger cameras, the detector consists of a 512×512 pixel array with a than would be expected by a planetary transit, but the observed pixel scale of ∼0.09 arcsec/pixel, giving a 45′′ × 45′′ field of depth is often reduced due to blends with nearby stars – if an view. eclipsing binary is blended with another star of equal brightness, All target stars were observed using the red camera on the the eclipse depths will appear halved. A chance alignment of a TCI. When possible, targets were also observed simultaneously bright foreground star and a dim background EB can cause the with the visual camera, which was undergoing commissioning observed eclipses to be almost impossible to distinguish from during the 2014 season. The two detectors were operated at a real planetary transits, a problem that has plagued many surveys. frame rate of 10 Hz for all observations. The use of a higher Blending is especially problematic for surveys looking in the frame rate of 30 Hz was investigated,but this resulted in a poorer crowded galactic plane, such as the Lupus (Bayliss et al. 2009) seeing correction. This was likely caused by the lower signal-to- and OGLE (Torres et al. 2004) collaborations, but the problem noise ratio (SNR) for the shorter exposures, which resulted in the still exists in more sparsely populated fields, with the WASP- reduction pipeline being less able to select good quality frames. South survey finding that for every 14 candidates sent for follow- Our targets were taken from the TEPCat1 database of well- up, 13 are astrophysical mimics or blends (Hellier et al. 2011). studied transiting extrasolar planets (TEPs) as of April 2014. The large number of planet candidates provided by the Kepler mission has resulted in several systematic searches for contami- 1 http://www.astro.keele.ac.uk/jkt/tepcat/
Article number, page 2 of 20 D. F. Evans et al.: High-resolution Imaging of Transiting Extrasolar Planetary systems (HITEP).
1.0
Visible Red
0.5 Sensitivity
0.0
1.0 UBVRI r' 0.5 g' i' u' Sensitivity z'
0.0 300 400 500 600 700 800 900 1000 1100 Wavelength (nm)
Fig. 1. Top panel: The theoretical response curves of the two TCI cameras, based on the properties of the dichroics, the quantum efficiencies of the cameras, and an assumed telescope transmission efficiency of 65%. Bottom panel: For comparison, the normalised response curves of the standard Johnson-Cousins UBVRI, and the measured sensitivity of the SDSS u′g′r′i′z′ cameras. Atmospheric effects are not included. This figure is adapted from Fig. 4 of Skottfelt et al. (2015b), with the permission of the author. The SDSS curves are based on a sensitivity determination made by J. Gunn in June 2001, available at http://www.sdss3.org/instruments/camera.php
All TEP systems observable from La Silla between April and Table 1. Summary of the observations of transiting exoplanet host stars September 2014 with brightnesses in the range 9 ≤ V ≤ 15 carried out. Where no exposure time is given in the ‘Vis.’ column, the were selected – at the time of observing, this brightness range observation was carried out with in the Red band only. Variations in exposure times are mainly due to the rejection of bad frames by the TCI included all published HAT, HAT-South and WASP systems in pipeline. This table is available in full at the CDS. the Southern hemisphere. We did not specifically include or ex- clude any systems based on the existence, or lack of, previously Exposure Time (s) known companions. Target Obs. Date (BJD ) Red Vis. For most targets, the default electron multiplication gain of TDB CoRoT-1 2456768.9897 600 300 e−/photon was used but targets brighter than V = 10.5 re- CoRoT-2 2456772.4179 440 quired a lower gain of 100 e−/photon, with no changes in gain CoRoT-2 2456783.4108 440 being made during the observing season for a given star. A typ- CoRoT-3 2456787.4274 890 ical planetary transit results in a flux change of 1%, which can . only be mimicked by a blended eclipsing binary less than 5 mag- . nitudes fainter than the foreground star – a system fainter than CoRoT-18 2456924.4054 900 899 this cannot produce an overall flux change of 1%, even if it is CoRoT-19 2456927.3924 900 899 completely eclipsed. To allow for such contaminating binaries to CoRoT-20 2456924.3918 900 900 be reliably detected, the total exposure time for each target was CoRoT-20 2456927.4096 898 899 chosen to give an SNR of 500 for a star 5 magnitudes fainter . than the target in the V band, assuming that no contaminating . light was diluting the signal from this star (i.e. the fainter star was well separated brighter star). The high target SNR included allowances for the rejection of a high fraction of frames in the lucky imaging process, and for shallower transit depths. In a few (2015b). The reduction pipeline performs the standard steps of cases it was necessary to adjust the exposure time after an ini- bias frame removal and flat field correction, and identifies and tial observation to reach the required sensitivity, with the obser- corrects for cosmic rays. The individual exposures are then re- vations being repeated – however, the initial shorter exposures centred to remove shifts in the target on the detector, and ranked were still used in our data analysis. Variations in the total ex- by quality, determined by the intensity of the central pixel rel- posure time also occurred due to the automatic rejection of bad ative to those surrounding it. Ten cuts in quality are made, and frames by the TCI pipeline. A summary of observations is given the exposures in each cut are stacked together and output as a in Table 1, available electronically at the CDS. ten-layer FITS cube. This allows a user to select only the best exposures for a high quality image, or instead to use more ex- posures and hence increase the effective exposure time. The cuts 3. Data reduction and analysis are concentrated towards the extremes of quality, and the per- 3.1. TCI pipeline centage boundaries between them are: 1, 2, 5, 10, 20, 50, 90, 98, 99, 100. Therefore, the first cut contains the top 1% of im- Raw lucky imaging data from the TCI are reduced automatically ages ranked by quality, the second cut contains the next 1% of by the Odin pipeline, which is described fully in Skottfelt et al. images, and so on.
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3.2. Smearing with a Gaussian, due to effects such as seeing and diffraction. As the product of two Gaussians is another Gaussian, the sec- In images taken with the TCI, bright stars show an apparent ond convolved image can be generated from the first seeing- smearing along the image rows in the opposite direction to the convolved image. EMCCD readout.It is thoughtthat this is caused by chargetrans- For each image cube from the TCI’s red camera, the first 7 ffi fer ine ciency (Skottfelt et al. 2015b), in which a small number quality cuts were loaded as separate images, meaning that the of electrons can become trapped at the edges of the EMCCD best 90% of exposures were used. The 6th and 7th cuts contain chip during the electron multiplication phase (Bush et al. 2014). the largest number of exposures, 30% and 40% respectively, al- These electrons are released during the readout of later pixels lowing the detection of very faint stars despite the lower image in the same row, artificially increasing the signal in those pix- quality.The final 3 cuts coverthe worst 10% of images, and have els. Despite the smears being only a small fraction (1%) of the neither high resolutions nor long exposure times, and so these total signal of their origin pixel, they are still bright enough to cuts were not used. ff wash out dim stars. To correct for this e ect, we assume that the Each of the seven images was convolved with a Gaussian of smear-corrected signal Ix, y at column x and row y is related from ′ standard deviation 4 pixels (FWHM 11.7 pixels) which was then the measured intensity Ix, y as: subtracted from the original image, giving a set of difference im- y−1 ages. In order to remove the signal from the target star, the im- I = I′ − k I (1) ages were divided into a series of annuli with a width of 0.5 pix- x, y x, y X x, i els, centred on the target star – the sub-pixel width was required = i 1 to handle the steep gradient in signal around the target. Within where k is the fraction of the charge that is trapped from one each annulus, the mean and standard deviation of the counts per pixel and later released into another pixel. It is therefore as- pixel were calculated. A sigma clipping algorithm was used to sumed that the fraction of charge that becomes trapped per pixel iteratively discount pixels with counts more than 3σ from the is fixed, and that this charge is released at a constant rate as each mean, to avoid the mean and standard deviation becoming bi- subsequent pixel is read out. We also do not attempt to reassign ased when a bright star was present. Finally, any pixels with a the trapped signal back to its origin pixel, as this would have signal more than 1.7σ from the annulus mean were flagged as no effect on the relative brightness of stars if the same fraction candidate detections, with all candidates from each of the 7 cuts of charge is lost per pixel. As the north/south diffraction spikes being compiled into a single detection list. The cut-off value of from the Danish telescope’s secondary mirror supports are par- 1.7σ was found to be the best compromise between reducing the allel to the detector readout direction, the north diffraction spike number of real stars (as determined by eye) that were incorrectly is significantly brighter than the south spike due to smearing. k rejected, and the increasing rate of false positives with lower cut- was determined by assuming the north/south diffraction spikes offs. visible on the TCI images should be of equal intensity after cor- The combined detections for each observation were checked rection, and this constraint was best satisfied by k = 0.0000177. by eye, mainly to exclude spurious detections caused by the non- circular shape of the PSF. The results from each of our observa- tions of a target were combined, creating a single verified list 3.3. Detection Method of candidate companions for each object. Measurements of the Faint stars located close to the target star run the risk of being properties of the stars were done using a single stacked image lost in the wings of the bright target star’s point spread func- using the 7 best quality cuts. Magnitudes relative to the target tion (PSF). Previous high resolution imaging surveys have of- star were calculated using aperture photometry. ten used some variation on PSF fitting to detect such stars (e.g. The separations and position angles for each candidate were Daemgen et al. 2009; Ngo et al. 2015), but this was not effec- measured by selecting a 9x9 pixel array centred on the both tive when applied to the TCI data. The Danish 1.54m Telescope the target star and the companion stars, which were then super- suffers from triangular coma below 1′′, resulting in an asym- sampled by a factor of 10. To calculate the position of a star’s metric PSF that is not well matched by analytical models, and centre along one axis, the super-sampled image was summed the changing observing conditions and stochastic nature of the parallel to the other axis, and the peak was chosen as the centre speckles caused by seeing result in significant variations between of the star. The accuracy of the position determination was tested the PSFs of stars observed even on the same night. Algorithms using simulated stars, with no improvement being found beyond such as Starfinder (Diolaiti et al. 2000), which derive an empiri- a super-sampling factor of 10, and was found to be accurate to cal PSF for the image, have been successfully applied to analyse within 0.5 pixels (0.044′′) for SNRs as low as 5. TCI observations of crowded fields without requiring an input For 11 candidate companions, accurate aperture photome- PSF model (Skottfelt et al. 2013, 2015a). However, many of our try was not possible due to their small separation from the target observations have only a single bright star visible, and so there star, usually combined with bad seeing conditions. Luckily, these is a potential degeneracy between the case of a bright PSF witha cases all occurred on images with other well-separated stars suit- nearby dim PSF, and a single bright PSF with a small aberration. able for use as PSF references, and the positions and magni- Ginski et al. (2012) suggested a method involving the convo- tudes were measured using the PSF-fitting DAOPHOT routines lution of each image with a Gaussian of a width larger than the in IRAF. It was assumed that the PSF shape was constant across FWHM and then subtracting the “blurred” image from the orig- the image, as the field of view was small enough to minimise inal image. This is similar to the Difference of Gaussians (DoG) atmospheric effects, and no variation in PSF shape was visible technique, in which an image is convolved with two Gaussians when images were inspected by eye. of differing widths that are then subtracted from one another, this technique having been used for purposes such as high-pass 3.4. Astrometric calibration filtering and edge detection (Gonzalez & Woods 2002). To im- plement this, the astronomical images were treated as an ideal The pixel scale and detector rotation of the red camera were cal- image of a set of point-like stars that has already been convolved ibrated using observations of eight globular clusters. Using the
Article number, page 4 of 20 D. F. Evans et al.: High-resolution Imaging of Transiting Extrasolar Planetary systems (HITEP). stellar positions published in the USNO NOMAD-1 catalogue, Table 2. List of spectrophotometric stars observed. an automatic fit to the detector scale and rotation was performed using the Starlink AST package and the GAIA image analysis Target SpT Vmagnitude Ref. tool2. The uncertainties in the NOMAD-1 catalogue varied de- CD-34241 F 11.2 1 pending on the brightness of the cluster and sources used for the Feige-110 DO 11.8 2 data, typically being in the rangeof 60 to 200 mas for each star– G158-100 dG 14.9 3 however, as several dozen stars were used in each fit, the effects LTT7987 DA 12.2 2 of random errors were reduced. Our uncertainties were derived LTT9239 F 12.1 1 from the scatter between the different fits generated. In order to LTT9491 DB 14.1 1 check for any variations in scale or rotation with sky position or NGC7293 DA 13.5 3 date, the images used for calibration were chosen to cover vir- tually the entire range of sky positions, and covered a range of References. (1) Hamuy et al. (1992, 1994); (2) Moehler et al. (2014); dates from 2014-05-07 to 2014-09-21. Additionally, an earlier (3) Oke (1990). image from the 2013 season was used as a further check for long term consistency. 2.0 The +y axis was found to be rotated from North by 1.1±0.2◦ 1.8 with a scale of 88.7±0.4 mas/pixel, and the −x axis rotated from ◦ East by 1.1 ± 0.3 at a scale of 88.9 ± 0.5 mas/pixel. From these 1.6 results, it was assumed that any difference in scale and rotation between the two directions was negligible, and the values were 1.4 ◦ combined to give a rotation of 1.1 ± 0.2 at a scale of 88.8 ± 0.3 1.2 mas/pixel. This was not found to vary with the pointing of the telescope, and no evidence of variation with time was found. 1.0 Astrometric calibration was not performed for the visual 0.8 camera, as the detector was being commissioned during the sum- flux Normalised mer 2014 observingseason (Skottfelt et al. 2015b). This resulted 0.6 in the orientation of the camera changing several times. In gen- eral, the visual camera images were rotated by approximately 0.4 ◦ +2 comparedto the red camera, and were offset slightly towards 0.2 the south west. 400 500 600 700 800 900 1000 Wavelength (nm)
3.5. Colour calibration Fig. 2. The spectra of G158-100. The top green line is the measured spectrum (Oke 1990), the bottom blue line the model, and the central In September 2014, we observed the seven spectrophotometric red line the combined spectrum. All curves are scaled to a peak flux of standard stars listed in Table 2 taken from the ESO Optical and 1.0, and are offset for clarity. UV Spectrophotometric Standard Stars catalogue3 in order to test the colour response of the TCI. Theoretical predictionsofthe TCI’s colour response curves were presented in Skottfelt et al. (Boesgaardet al. 2005). To extend the data from 900nm on- (2015b), which were combined with the spectra of the standard wards, we used a PHOENIX model spectrum (Husser et al. 2013), stars to give an estimated Vis-Red colour index, abbreviated as with Teff = 5300K, log g = 4.00,and [Fe/H] = −3.0, the temper- (v − r) TCI. The fluxes were measured using aperture photometry, ature being varied to best fit the measured spectrum. The result and a (v − r) TCI colour index was generated for each observation. is shown in Fig. 2. We modelled atmospheric extinction using a linear relation- A similar problem with cut-off spectra occurred in the cases ship, with the corrected colour (v − r) TCI being related to the ′ of NGC 7293 and LTT 9491. Due to their high temperatures and measured colour (v − r) TCI as follows: relatively featureless spectra, both were fitted as black bodies. ′ NGC 7293 was extended from 900nm onwards with a black (v − r) TCI = (v − r) TCI − kZ (2) body temperature of 110,000K, and LTT 9491 was extended from 970nm onwards with a temperature of 12,500K. where Z is the airmass and k isacoefficient fitted to the data, with Upon analysis of the extinction-corrected colour indices, it a value of +0.08 ± 0.03 mag/airmass being chosen as the best- became apparent that all stars were systematically offset by fit value. However, there was significant scatter in the data, and −0.46 in the (v − r) colour index compared to the predicted improved observations would be useful in verifying and further TCI values, indicating that the stars appear significantly bluer than constraining this value and its dependence on stellar colour. This expected. This is much larger than the atmospheric extinction agrees fairly well with the measurementsof Tüg (1977) at the La correction, and it is not currently clear what the cause of the Silla site, which predicts that the relative extinction coefficient offset is. There is some evidence that the colour offset is temper- of filters centred at 560nm and 860nm would be approximately ature related, with cooler stars generally showing a lower offset, +0.1 mag/airmass. as shown in Fig. 3. The spectrum used for the standard star G158-100 in Oke (1990) is cut off redwards of 920nm, causing the flux in the red filter to be underestimated. The star is a G-type subd- 3.6. Stellar colour indices warf, with Teff = 4981K, log g = 4.16, and [Fe/H] = −2.52 It is possible to measure the colour of objects by using the flux 2 Starlink is available at http://starlink.eao.hawaii.edu/starlink/ in the visual and red cameras of the TCI, and hence to estimate 3 Available at http://www.eso.org/sci/observing/tools/standards.html the effective temperature of the object. This can then be used to
Article number, page 5 of 20 A&A proofs: manuscript no. hitepAccepted_20160309