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Doressoundiram et al.: Color Properties 91

Color Properties and Trends of the Transneptunian Objects

A. Doressoundiram Observatoire de Paris

Hermann Boehnhardt Max-Planck Institute for Research

Stephen C. Tegler Northern Arizona University

Chad Trujillo Gemini Observatory

The color of transneptunian objects (TNOs) is the first and basic information that can be easily obtained to study the surface properties of these faint and icy primitive bodies of the outer solar system. Multicolor broadband is the only tool at the moment that al- lows characterization of the entire population that is relevant for statistical work. Using the colors available for more than 170 objects it is possible to get a first glance at the color distri- bution in the Edgeworth-. First, results show that a wide color diversity character- izes the outer solar system objects. Transneptunian objects have surfaces showing dramatically different colors and spectral reflectances, from neutral to very red. At least one cluster of ob- jects with similar color and dynamical properties (the red, dynamically cold classical TNOs beyond 40 AU) could be identified. Furthermore, evidence for correlations between colors and orbital parameters for certain objects have been found at a high significance level. Both color diversity and anisotropy are important because they are diagnostic of some physical effects processing the surfaces of TNOs and/or some possible composition diversity. In this paper, we will review the current knowledge of the color properties of TNOs, describe the observed color distribution and trends within the Edgeworth-Kuiper belt, and address the problem of their possible origin.

1. INTRODUCTION (e.g., orbital properties). Such correlations may yield insight into the important formation and evolution processes in the It is now clear that , , and the ≈1200 known outer solar system. (as of January 2007) transneptunian objects (TNOs) are An early expectation was that all TNOs should exhibit what remain of an ancient disk of icy debris that did not the same red surface color. But why were outer-main-belt accrete into a giant, jovian-like beyond the orbit of asteroids and jovian trojans known to exhibit red colors (e.g., . By studying TNOs, it is possible to examine the see Degewij and van Houten, 1979)? In addition, Gradie preserved building blocks of a planet, and thereby shed and Veverka (1980) suggested that organic materials — some light on the process of planet building in our solar molecules defined by C–H bonds — should readily form at system as well as extrasolar planetary systems. large heliocentric distances and cause redder colors at large A photometric survey is a natural first step in the investi- heliocentric distances. Gradie and Tedesco (1982) discov- gation of TNOs because it is the only kind of survey capa- ered a correlation between color and semimajor axis of as- ble of providing a global view of the transneptunian belt. teroids, implying that asteroids preserve a record of solar Specifically, it is possible to obtain accurate magnitudes and system formative and evolutionary processes at various he- colors for all of the known TNOs using 2-m- to 10-m-class liocentric distances, rather than being a chaotic mixture. The telescopes. Accurate magnitudes and colors for a large num- extraordinary red color of the early [5145 Pholus ber of TNOs provide a starting point and context for more (Mueller et al., 1992)] and TNO [1992 QB1 (Jewitt and Luu, in-depth techniques such as and 1993)] discoveries seemed to confirm the idea that objects flybys. It is also possible to look for statistically significant at large heliocentric distances exhibited red surface colors. correlations between colors and other properties of TNOs Transneptunian objects were thought to form over a small

91 92 The Solar System Beyond Neptune range of distance from the Sun where the in ors and orbital elements (section 4), links between colors the young solar nebula was the same. The similar tempera- and chemical and mineralogical properties of TNOs (sec- ture suggested that TNOs formed out of the solar nebula tion 5), and possible processes responsible for the observed with the same mixture of molecular and the same ratio colors of TNOs (section 6). of dust to icy material. In addition, their similar formation distance from the Sun suggested that TNOs experienced a 2. PRINCIPLE AND TOOLS OF similar evolution. For example, the irradiation of surface TRANSNEPTUNIAN OBJECT PHOTOMETRY CH4 by cosmic rays, solar ultraviolet light, and solar wind particles could convert some surface CH4 ice into red, 2.1. Observational Strategy complex, organic molecules. CH4 ice was known to exist on the surface of Pluto (Cruikshank et al., 1976). Labora- Due to the faintness of the TNOs and , it is a tory simulations supported the conversion of CH4 ice into very difficult and telescope-time-consuming task to obtain complex organic material (e.g., Moore et al., 1983; Straz- spectroscopy of a statistically representative sample that zulla et al., 1984; Andronico et al., 1987). By their nature, could be used for in-depth studies of surface properties and the complex organic molecules were expected to absorb their correlations with other physical, dynamical, formation, more incident blue sunlight than red sunlight. Therefore, and evolutionary parameters of the objects. However, a first the light reflected from the surfaces of TNOs, and observed and much faster (in terms of telescope time) assessment on Earth, was expected to consist of a larger ratio of red to of intrinsic surface properties of these objects is possible blue light than the incident sunlight. It was a surprise, there- through photometric characterization of their reflectance fore, to discover that TNOs exhibited a wide range of colors. spectra by determining broadband filter colors and spectral Dynamically, the Edgeworth-Kuiper belt is strongly gradients derived from the filter measurements. It is as- structured, and three main populations are usually distin- sumed that sunlight is reflected at the surfaces of the objects guished within this region. The resonant TNOs are trapped only, and no or dust is present. Activity in mean-motion resonances with Neptune, in particular the induced by intrinsic processes (gas evaporation or cometary 2:3 at 39.4 AU (the so-called “”), and are usually activity) or external processes (impacts) is presumed to play on highly eccentric orbits. The less-excited classical TNOs, a role in the resurfacing of TNOs and Centaurs. In rare also called “classicals,” populate the region between the 2:3 cases, such as Pluto (with a tenuous atmosphere) and Chiron and the 1:2 (say 40 AU < a < 50 AU) resonances. The “scat- (showing episodic cometary activity), the presence of an tered disk objects” (SDOs) make up a less-clearly-defined atmosphere and/or a dust coma may affect the interpretation population and are mainly objects with high eccentricity e of the measured colors of the objects. and perihelion near Neptune that were presumably placed Since they are well characterized and available at many in these extreme orbits by a weak interaction with Neptune. observatories, astronomical broadband filters are used for The “Centaurs,” finally, represent a dynamical family of ob- the photometric measurements of TNOs and Centaurs, i.e., jects in unstable orbits with semimajor axes between Jupiter BVRI for the visible range and JHK for the and Neptune. The classification given here is historically near-IR. Due to the faintness of the objects in the respec- the first one adopted by the community, but the frontiers tive wavelength range, U and L and M filters can only be between each group are not easy to define. Moreover, the used for the very brightest objects (e.g., Pluto-Charon). For classicals are a diverse population consisting of objects the visible, the vast majority of data are available in the ranging from low to very high degrees of dynamical exci- Bessel filter set, while only a few measurements are ob- tation. Obviously this population needs to be dissected care- tained using the Johnson filter set (Sterken and Manfroid, fully. A most complete and rigorous classification is dis- 1992, and references therein), which differs from the former cussed in the chapter by Gladman et al. one in the transmission ranges of the R and I filters. For How do the color properties compare within each dy- the near-IR filter set, the differences in the Js and Ks trans- namical group of TNOs? Answering this question will pro- mission ranges compared to standard J and K filters (Glass, vide important clues to understand how these objects have 1997, and references therein) is of minor importance for been formed and how their surface properties have evolved. color studies of the objects. Indeed the different orbital properties characterizing each Transneptunian objects are challenging to observe be- dynamical family of TNO should have a distinct impact on cause they are faint, move relative to the “fixed” back- the color properties of the surfaces of TNOs. For example, ground of stars and galaxies, and exhibit brightness varia- those objects in extreme orbits (high i and e) experience tions (lightcurves). In this section, we discuss these chal- more energetic collisions than those in circular orbits. Such lenges and techniques to overcome them. Note that these energetic collisions in turn have a significant impact on re- problems are reminiscent of the first works performed on surfacing, thus on the color of the surface. main-belt asteroids in the early 1960s and 1970s when In the sections that follow, we discuss observational strat- available technology at that time did not allow the use of egies, data reduction techniques, and analysis methods of more sophisticated techniques, i.e., spectroscopy (see Mc- TNO photometric surveys (section 2), observed optical and Cord and Chapman, 1975; Bowell and Lumme, 1979, and near- colors (section 3), correlations between col- references therein). Then the same logic was applied as Doressoundiram et al.: Color Properties 93

observers progressed from the main belt to Hildas, Trojans likely rotating body, it is important to measure the object (Hartmann et al., 1982), and finally Centaurs and TNOs flux through the various filters quasi-simultaneously, i.e., (Luu and Jewitt, 1996). within a time interval that is short compared to the rotation 2.1.1. Faintness. First, the most challenging problem period of the object. For instance, for an object with a 10- is that the TNO population represents some of the faintest h , the phase angle of the surface changes by objects in the solar system. The typical apparent visual mag- 10° in 30 min. Hence, very fast rotators can mimic strange nitude of a TNO is about 23 mag, although a few objects surface colors or unexpected color variations [see, e.g., brighter than 20 mag are known. Another criterion is the 1994 EV3 (Boehnhardt et al., 2002)]. Since for many ob- minimum signal-to-noise ratio (SNR) of the photometry: jects the exact rotation period is unknown, it is thus advis- Typically, SNR ~30 (corresponding to an uncertainty of able to monitor changes in the object brightness due to 0.03–0.04 mag) is required to accomplish the spectral clas- rotation by repeated exposures in a single filter (e.g., V fil- sification. Indeed, the differences among the known types ter) intermittent during the complete sequence of filter ex- of minor bodies (which to first order have the color of the posures needed for the color measurement of the object. If Sun) are much more subtle than for stellar types, so con- the rotation period is known, one can phase the filter ex- siderably higher photometric accuracy is necessary. The posures to appropriately image the same surface area un- more limited the range of , the higher the ac- der the same illumination conditions. curacy needed to distinguish objects of different type. How- ever, to reach such a SNR goal, one needs to overcome two 2.2. Data Reduction Techniques problems: (1) the sky contribution, which could be impor- tant and critical for faint objects not only in the infrared, The data reduction consists of the basic reduction steps but also for visible observations; and (2) the contamination applicable for the visible and near-IR photometric datasets, by unseen background sources such as field stars and gal- i.e., bias and flatfield corrections, cosmic-ray removal, axies. For instance, the error introduced by a 26-mag back- alignment and co-addition of the jittered images, and flux ground source superimposed on a 23-mag object is as large calibration through standard stars. as 0.07 mag. One solution to alleviate these problems is the The brightness of the object is frequently measured use of a smaller aperture for the flux measurement of the through the so-called aperture correction technique (Howell, object. This method is described in the next section. 1989; Tegler and Romanishin, 1997; Doressoundiram et al., 2.1.2. Motion relative to background. Transneptunian 2001) as justified by the faintness of the TNOs. The basis objects, while at very remote heliocentric distance, still have of this method is that the photometric measurement is per- noticeable motion that restricts the exposures to relatively formed by using a small aperture on the order of the size of short integration times. At opposition, the motion of TNOs the seeing disk. Consequently, the uncertainty in the meas- at 30, 40, and 50 AU are, respectively, about 4.2, 3.2, and urement is reduced because less noise from the sky back- 2.63/h, thus producing a trail of ~1.03 in 15 min exposure ground is included in the aperture. However, by doing so, time in the worst case. The trailing of an object during an one loses light from the object. Thus, to determine how exposure has devastating effects on the SNR, since the flux much light is thrown away, the so-called “aperture effect” is diluted over a larger area of background sky. This dilu- is calibrated using a large number of nearby field stars. This tion, in turn, introduces higher noise. Thus, increasing ex- is reasonable as long as the motion of TNOs during each posure time will not necessarily improve the SNR for TNO exposure is smaller than the seeing, and hence the TNOs’ photometry. For practical purposes, the exposure time is point-spread functions (PSFs) are comparable to those of chosen such that the trailing due to the object’s motion does field stars. For all the photometry, the sky value can be com- not exceed the size of the seeing disk. The observer then puted as the median of a sky annulus surrounding the ob- takes and combines a number of untrailed exposures to im- ject. The advantages in the use of a small aperture are (1) a prove the SNR. An alternative is to follow the object at its decrease of the contribution of the sky, which could be im- proper motion. In this case, however, one faces another portant and critical for faint objects; and (2) a reduction of problem: The point-spread function of the object (PSF) the risk of contamination of the photometry by unseen back- would be obviously different from that of the field stars. ground sources. Moreover, the so-called aperture correction technique used very frequently for accurate TNO photometry would be- 2.3. Analysis Methods come very difficult since this method requires the PSF cali- bration of nearby field stars (see next section). Many useful physical parameters of TNOs can be de- 2.1.3. Lightcurves. The color of a TNO or Centaur is rived from broadband photometry. These parameters include ideally measured simultaneously for the two or more fil- color, spectral gradient, absolute , and size. ters in order to guarantee that the same surface area of the 2.3.1. Color indices. The color indices used here (such object is imaged at the same time. However, the majority as U–V, B–V, etc.) are the differences between the magni- of color measurements are obtained by exposing the object tudes obtained in two filters. In other words, the F1–F2 color through different filters sequentially. In order to avoid color index (where F1 and F2 are any of the UBV, etc., filters) is changes induced by and/or shape variations of the the ratio of the surface reflectance approximately valid for 94 The Solar System Beyond Neptune

λ λ the central wavelengths 1 and 2 of the corresponding fil- ters. 2.3.2. Reflectance . The information con- tained in the color indices can be converted into a very-low- resolution reflectance spectrum RF using

–0.4 (M – M Sun) RF = 10 F F where MF and MFSun are the magnitudes in filter F of the object and of the Sun, respectively (MVSun = –26.76). Nor- malizing the reflectance to 1 at a given wavelength (conven- tionally, the V central wavelength is used), we have

–0.4 [(M – M ) – (M – M )Sun] RF,V = 10 F V F V

The filter magnitudes and colors of the Sun for the fil- ters commonly used can be found in Hardorp (1980) and Degewij et al. (1980). Values of the main colors for the Sun used here are B–V = 0.67, V–R = 0.36, V–I = 0.69, V–J = 1.03, V–H = 1.36, and V–K = 1.42. Figure 1 illustrates the coarse reflectance spectrum using broadband filter photom- Fig. 1. Reflectance spectrum, broadband filter brightness, and etry compared to spectroscopy of a TNO. spectral gradient of the TNO 2001 KX76 or (28978) . The 2.3.3. Spectral gradient. The spectral gradient S is a reflectance is shown normalized to unity at 550 nm. The BVRI measure of the reddening of the reflectance spectrum be- broadband filter brightness is plotted by “star” symbols (from short tween two wavelengths. It is expressed in percent of red- to long wavelength) over the central wavelength of the respective dening per 100 nm filter bandpass. The spectral gradient fitted to the spectroscopy and photometry of the object is shown as a dotted line. Neutral/ λ λ λ λ solar reflectance is represented by the dashed line. S( 2 > 1) = (RF2,V – RF1,V)/( 2 – 1) λ λ where 1 and 2 are the central wavelengths of the F1 and F2 filters, respectively. S, given in percent of reddening per completely unknown for most of the TNOs. Based on a 100 nm wavelength difference, is intimately related to the first-phase-curve study of a few TNOs, Sheppard and Jewitt constitution of the surface of the object, although at present (2002) have shown almost linear and fairly steep phase it is not possible to draw any detailed conclusions from curves in the range of phase angles from 0.2° to 2°. They spectral gradients (or colors) on specific surface properties. found an average β of 0.15 mag/deg. A similar steep slope By definition, spectral gradient values are a direct measure was found for Centaurs (Bauer et al., 2002). This implies for the intrinsic reddening of the object produced by the a possible considerable error in H calculations disregarding surface properties of the object, i.e., the solar colors are the phase correction. Further studies have also been made “removed”; hence, S = 0 means exactly solar colors. If sev- measuring phase curves in parallel with (Bag- eral filters are measured over a wider wavelength range (e.g., nulo et al., 2006; Boehnhardt et al., 2004). BVRI to cover the ), the spectral gradients 2.3.5. Size. Size is the most basic parameter defining a can be averaged over the main adjacent color indices (e.g., solid body. Unfortunately, sizes (and ) are difficult B–V, V–R, R–I) in order to obtain the overallslope of the to determine as they mostly require thermal measurements. reflectance spectrum between the two limiting wavelengths. Hence objects with accurate size determination are few (see 2.3.4. . The absolute magnitude of chapter by Stansberry et al.). Consequently, for most ob- a TNO is the magnitude at zero phase angle and at unit he- jects, a canonical p is assumed and the liocentric and geocentric distances. Geometrical effects are absolute magnitude MF(1,1,0) can be converted into the removed by reducing the MF visual magnitude (in the F fil- radius R of the object (km) using the formula by Russell ter) to the absolute magnitude MF(1,1,0) using (1916)

Δ αβ 2 16 0.4(M Sun – M (1,1,0)) MF(1,1,0) = MF – 5 log(r ) – pR = 2.235 × 10 10 F F Δ α where r, , and are respectively the heliocentric distance where MFSun is the magnitude of the Sun in the filter F (AU), the geocentric distance (AU), and the phase angle (MVSun = –26.76). Owing to the lack of available albedo (deg). The term αβ is the correction for the phase bright- measurements, it has become the convention to assume an ening effect (Belskaya and Shevchenko, 2000; see also the albedo of 0.04, common for dark objects and cometary nu- chapter by Belskaya et al.). However, the phase function is clei. However, one should be aware of the fact that the sizes Doressoundiram et al.: Color Properties 95

are purely indicative and are largely uncertain. For instance, neous or quasi-simultaneous filter exposures). For Centaurs if we would use, instead, an albedo of 0.14 (i.e., the albedo in eccentric orbits, changes in the aspect angle due to or- of the Centaur ), the results for size estimates bital motion can also result in color variations for objects would have to be divided by a factor of about 2. with nonhomogenous surface colors. (Due to the long or- Having these limitations in mind (unconstrained phase bital periods of TNOs, changes of the aspect angle along the function and albedo), in all the following analysis and fig- orbit may happen over timescales of decades only, a time ures that make use of absolute magnitude and size, we have interval much longer than the time span during which fil- taken the above values for the phase correction and an av- ter observations of TNOs have been performed up to now.) erage albedo of 0.09 for the geometric albedo (R band). Similar statements were also made in the 1960s to 1980s when interpreting rotational effects and albedos and colors 3. COLOR DIVERSITY AND (see, e.g., Bowell and Lumme, 1979; French and Binzel, SPECTRAL GRADIENT 1989). Rotation phase resolved color measurements of only a few objects are published so far (see chapters by Sheppard O. Hainaut from the European Southern Observatory et al. and Belskaya et al.). In order to achieve a complete in Chile has compiled and maintains a database of color characterization of the color properties of a body, full cov- measurements of TNOs, Centaurs, and short-period . erage of the rotation (aspect) phase range is required (but The database can be accessed at www.sc.eso.org/~ohainaut/ rarely done). In cases where several color measurements are MBOSS. As of late September 2006, this MBOSS database available, averaging of the results can be performed to ob- contains values for 209 objects (Plutinos 32; classicals 95; tain a mean value for the colors and spectral gradients. SDOs 32; Centaurs 30, comets 20) at 1077 epochs cover- Color-color diagrams of TNOs (as well as of Centaurs ing the UBVRIJHKLM filter set (not all the objects have and cometary nuclei; see Fig. 2) in the visible show a wide the full filter set). It also provides references to the values distribution from neutral and even slightly “bluish” to very stored. (Note that Tegler and Romanishin have also put red values. Figure 2 also shows the various dynamical colors and magnitudes from their survey for ~120 TNOs classes of the TNOs (i.e., classical objects, Plutinos, scat- and Centaurs on the web at www.physics.nau.edu/~tegler/ tered disk objects) and the Centaurs. All subclasses are color research/survey.htm.) undistinguishable, which is consistent with a common ori- Both colors and spectral gradients are “integral” charac- gin for these objects. terization parameters of surface properties of the objects: For the overall TNO population (of more than 150 “integral” over the illuminated and visible part of the sur- objects with BVRI color measurements) clustering is not face, which for TNOs and distant Centaurs is almost equiva- obvious although originally proposed based upon much lent to a complete hemisphere since the phase angles are smaller samples (Tegler and Romanishin, 1998). However, small, and “integral” over the wavelength range of the fil- clustering in color-color diagrams is found when consider- ters used. ing different populations of TNOs and Centaurs (see dis- cussion below). The trend line overplotted in Fig. 2 repre- 3.1. Color-Color Diagrams of sent the locus of object with a linear reflectance spectrum. Transneptunian Objects The “diagonal orientation” of the TNO cloud in the V–R vs. B–V plot in Fig. 2, following the trend line of increased Color-color diagrams show two measured color indices reddening, suggests constant surface reddening from B to R of the object sample vs. each other, e.g., V–R color vs. B– for the majority of the objects. Instead, the respective R–I V color as measured for TNOs and/or Centaurs. Solar colors vs. B–V color-color plot in Fig. 2 clearly indicates system- provide the reference for zero intrinsic reddening. Objects atic deviations from the trend line toward smaller redden- with “higher” color indices than solar are called “redder” ing at the long wavelength end of the visible spectrum. In than the Sun, those with “smaller” values are “bluer” than near-IR color-color diagrams (H–K vs. J–H in Fig. 3), a the Sun. The “redder”/“bluer” colors are equivalent to a pos- strong clustering of TNOs around solar colors is found that itive/negative spectral gradient compared to the solar spec- clearly indicates flat and close to neutral surface colors for trum. For guidance, the reddening trend line can be drawn in the majority of the objects. Very few objects show signifi- the color-color diagrams: This line connects locations in cant reddish colors (Delsanti et al., 2006). Outliers toward the color-color diagram with increasing values of constant bluer than solar colors exist and may be due to absorption spectral reflectance slope. Deviations from the reddening bands of surface ices (e.g., H2O, CH4) with influence on trend line indicate a nonlinear behavior of the intrinsic red- broadband colors (in particular in H and K filters). In this dening over the spectral range covered by the filters of the respect “bluish” near-IR colors may be used to identify color-color diagram. Examples for color-color diagrams of potential objects with ice absorption spectra — although the TNOs and Centaurs are shown in Fig. 2. photometric indices are certainly not qualified to replace Color changes over the body’s surface combined with spectroscopic analysis of the objects for ice signature de- rotation of the object can result — in principle — in varia- tections. The changeover from the red color in visible to tions of the object’s colors depending on the rotation phase the more neutral near-IR spectrum in the individual objects when the measurements are performed (even for simulta- happens between about 750 and 1400 nm and thus affects 96 The Solar System Beyond Neptune mostly the I and J filter reflectance. However, it also ex- plains the systematic deviations from the trend lines in R–I vs. B–V color-color diagrams. In other words, visible colors are mutually correlated, while they appear to be unrelated to infrared colors (Doressoundiram et al., 2002; Delsanti et al., 2006).

3.2. Spectral Gradient Histograms of Transneptunian Objects and Centaurs

The full range of spectral gradients of the object sample should be covered by a dense set of [Smin, Smax] pairs, the lower and upper limit for the spectral gradient of the ob- jects to be counted in the respective histogram bin. Exam- ples for spectral gradient histograms of TNOs and Centaurs are shown in Fig. 4. In the following analysis spectral gra- dients among TNOs and Centaurs have been obtained from BVRI broadband photometry extracted from the MBOSS database. The surface characterization by spectral gradients some- how implies and is best used for objects with rather fea- tureless reflectance spectra (i.e., no absorption due to sur- face ices). This requirement may reasonably be fulfilled in the visible wavelength range where only weak absorption bands are found in a few TNOs (see chapter by Barucci et al.) without noticeable effects on the filter magnitudes. The near-IR wavelength region contains various strong absorp- tion bands of H2O and CH4 ices, which have been found in some TNOs. Hence, effects on the surface colors are pos- sible and, indeed, the “bluish” colors J–H and/or J–K may be due to these ice absorptions (see below). The range of spectral gradients of TNOs and Centaurs in the visible wavelength region ranges from –5%/100 nm to 45%/100 nm, with the exception of some very red Cen- taurs. The spectral gradient distributions for the four major dynamical classes (classicals, SDOs, Plutinos, and Centaurs) display evident differences (Fig. 4): Classicals cluster be- tween 25 and 35%/100 nm and are abundant also at some- what smaller reddening slopes (i.e., between 15 and 25%/ 100 nm). Plutinos and SDOs peak at moderately red lev- els, while Centaurs show a double peak distribution with a high number at low reddening (5–15%/100 nm, comparable to the range of the distribution maximum for the Plutinos and SDOs) and a shallower peak with very red slopes (35–

Fig. 2. Color-color diagrams of TNOs (Plutinos = open triangles, classicals = filled circles, SDOs = open pentagons, Centaurs = open squares, Trojans = filled triangles, comets = open four-spike star). The diagrams apply for broadband filter results in BVRI. Solar colors are indicated by an open five-spike star symbol. The curve is the locus of object with a linear reflectivity spectrum. The Sun, as a reference, has a linear reflectivity spectrum with a null slope. A tick mark is placed every 10%/100 nm; the curve is grad- uated in units of from 0 (solar) to 70%/100 nm (very red). Plots are from the web page of O. Hainaut (www.ls.eso.org/ ~ohainaut/MBOSS), who compiles photometric results of minor bodies in the outer solar system. Doressoundiram et al.: Color Properties 97

45%/100 nm, similar to the main maximum in the classicals histogram). The structured histograms suggest that further subpopulations exist for classicals and Centaurs, which are described and analyzed by more sophisticated statistical methods below. The overall reddening distributions of the TNOs and Centaurs need an interpretation based upon sur- face processing scenarios and modeling. The spectral gra- dient in the near-IR wavelength region tend to flatten off (close to solar-type colors are mostly measured) and is not very instrumental for population classification except for the identification and analysis of outliers. Such analysis is reminiscent of early work done with asteroids in the 1970s and 1980s. In particular, a relation between color (or spectral gradient) and ice abundance in outer solar system objects, as caused by spectral absorp- tion bands, was the background of Hartmann et al.’s (1982) work and a subsequent series of papers. These authors showed a direct correlation between position in a V–J vs. J–K diagram, and the measured albedos and ice contents of well-observed satellites and asteroids. Fig. 3. J– H vs. H–K color-color diagram of TNOs and Centaurs. Symbols are Plutinos = open triangles, classicals = filled circles, 4. COLOR DISTRIBUTION OF SDOs = open pentagons, Centaurs = open squares, Trojans = filled THE TRANSNEPTUNIAN OBJECTS: triangles, comets = open four-spike star, Sun = open five-spike star, STRONGLY SHAPED trend line of increased reddening = solid line. This line is the lo- cus of objects with a reflectivity spectrum of increasing linear slope (see also Fig. 2). Most of the points lie below the redden- The main purpose is to see if color is a tracer for any ing curve. This is an indication for a change and decrease of the physical process. While any physical processes are of in- spectral slope over the JHK range. The two outliers are (19308) terest, we have very little detailed knowledge of physical

1966 TO66 (top left) and (24835) 1995 SM55 (bottom left). mechanisms. The physical processes that are easiest to test

Fig. 4. Spectral gradient histogram of TNOs and Centaurs (after Doressoundiram and Boehnhardt, 2003). 98 The Solar System Beyond Neptune with such limited knowledge consist of comparisons of 4.2. Correlations color with combinations of orbital physical parameters. The main purpose of collecting a wide range of color 4.1. Database of Colors and Color Indices data is to consider whether TNO surface color is related to dynamical factors and can give an indication of how solar For this analysis, we restrict our sample to those collated system wide factors may impact TNO composition. Plates 1 in the MBOSS database used in the previous section. Here and 2 are an overview of the color distribution of TNOs we focus on the visible colors of the TNO surfaces. The obtained within the Meudon Multicolor Survey (2MS) of analysis is made simpler by the fact that visible colors are Doressoundiram et al. (2005). The advantage of this view mutually correlated throughout the VRI regime (Boehnhardt is that it offers to the eye global patterns between color and et al., 2001; Doressoundiram et al., 2002). orbital elements. Although the search for correlations be- This is the basic premise behind the supposition that the tween colors and dynamical information such as orbital ele- coloring agent could be -like materials (Jewitt and ments is open ended, we here limit the search to basic or- Luu, 2001; Cruikshank et al., 2005), which tend to produce bital element data and a few derived quantities. The most a uniform color gradient throughout the visible region. This basic and robust statistical test searching for correlations is fact allows the transformation of most color values in the the Spearman rank correlation test, which does not presup- MBOSS database to a common reddening scale, the percent pose a functional form for the correlation, as do many other of reddening per 100 nm, S (see section 2.3) implemented statistical tests (Spearman, 1904). for the MBOSS database by Hainaut and Delsanti (2002). 4.2.1. Criteria for statistical significance. We compare For objects with multiple color values, all are combined into our color metric S against the most basic of dynamical pa- this metric with formal error propagation. rameters, orbital elements. Since we are looking for a cor- A plot of true V–R vs. the S metric appears in Fig. 5, il- relation between color and many potential parameters, we lustrating that this transformation is valid for objects with must use a higher criterion for statistical significance than multiple color data. The MBOSS database allows us to look the standard 3σ used throughout astronomy. Indeed, simple at the VRI color characteristics among 176 TNOs and Cen- simulations show that if a set of 176 uniformly distributed taurs listed in the Center database. numbers (representing our 176 color values) are compared against n = 6 other uniformly distributed datasets (e.g., repre- senting the 6 basic orbital parameters), a > 3σ spurious “cor- relation” occurs with the Spearman test 1.35% of the time, a factor (n – 1) = 5 in excess of the 0.27% rate expected and seen for comparison to a single orbital parameter. Therefore, to properly compare color correlations among the orbital parameters, we must raise our threshold to ≈3.5σ for six orbital parameters to realize the 0.27% spurious cor- relation rate for a 3σ event for a single orbital parameter. Since the probability for spurious correlation increases roughly linearly with the number of extra parameters tested, and Gaussian probabilities are a strong function of σ values, even a moderate increase to 3.8σ is appropriate for consid- ering correlations of up to n = 20 parameters as we do here. We adopt this 3.8σ value here for the remainder of our dis- cussion. 4.2.2. Populations considered. It is quite clear that nei- ther the Plutinos (in the 2:3 mean-motion resonance at 39.4 AU) nor the SDOs (q near Neptune) have any signifi- cant correlation between the MBOSS colors and any orbital parameter, and no researchers have reported such correla- tions. For completeness, we do test the Plutinos and SDOs here. It is also quite clear that Centaurs (q > 5.2 AU and a < 30.1 AU) have a bimodal color distribution of a strength not Fig. 5. This plot shows a strong correlation between the redden- seen in any TNO population (Peixinho et al., 2003; Tegler ing factor S (computed in the visible wavelength) and the V–R et al., 2003; chapter by Tegler et al.). Discussion of the color of objects. Thus, our transformation of all color data to the common S scale is consistent with measured values of the most Centaur population is not included in this work as they rep- common color filter difference, V–R. The use of the S reddening resent a population that is much more dynamically unstable factor allows combinations of all visible colors to be used in cor- than the TNOs and is potentially affected by recent com- relation analysis and reduces error bars by significant amounts by etary activity. Thus, there remain only two populations in combining data throughout the VRI wavelength region. the Edgeworth-Kuiper belt that could have any correlation Doressoundiram et al.: Color Properties 99

between color and orbital parameters: the classical TNOs verse colors) at the 99% significance level. This red clus- and the “other TNOs,” TNOs with semimajor axes in the ter is clearly seen in Plate 1, where objects with perihelion range (40 AU < a < 50 AU) but with eccentricities too high distances around and beyond 40 AU are mostly very red. to be considered classicals. We define this population as the The cluster members have similar dynamical and surface “near-scattered TNOs,” since they have similar perihelion properties, and they may represent the first taxonomic fam- properties to the SDOs, but are close enough that the sepa- ily in the Edgeworth-Kuiper belt. ration between them and the classical TNOs is not easily Many studies have been performed to search for corre- defined. lations between color and physical parameters (e.g., size). It is not easy to determine where the classical TNOs end So far, no significant trend has been found between color and the near-scattered TNOs begin. Observers traditionally and size, or absolute magnitude. This points out that the col- arbitrarily choose a minimum perihelion value to distinguish oring process (whatever it is) is not sensitive to size, at least between the classical and near-scattered TNOs somewhere in the size range accessible by groundbased observations. between 36 AU and 41 AU. However, dynamical studies We tested the following four populations: all TNOs (q > have shown that the 40 AU to 50 AU region has many nar- 25 AU), the Plutinos (38.5 AU < a < 40 AU), the SDOs row resonances that can mask objects that are true classi- (q near Neptune), and the classical TNOs (40 AU < a < cal TNOs. The lower limit on the perihelion for discrimi- 50 AU). These were tested against the following orbital pa- nating the classical TNO population from the near-scattered rameters: inclination, eccentricity, perihelion, and the root- TNOs is critical for detecting a color/orbital element corre- mean-square orbit velocity, Vrms, as discussed by Stern lation with either population. Evaluating exactly where the (2002). Indeed, collisional resurfacing could also provide perihelion criterion should be set to define classical TNOs a possible explanation for the orbital element dependency is difficult at best and beyond the scope of this work as it of the color indices: One would naturally expect highly is primarily a dynamical argument (see chapter by Gladman excited objects to suffer more energetic impacts. No other et al.). Instead we treat all these TNOs as one class, included orbital parameters were tested, because no correlations have in the single denomination of classical TNOs, defined as been reported for other parameters. The results of the cor- 40 AU < a < 50 AU whatever their eccentricity. relation tests are shown in Table 1. It is clear that the en- 4.2.3. Summary of significant correlations. A statisti- tire TNO population shows a statistically significant corre- cally significant clustering of very red classical TNOs with lation between color and both rms velocity and inclination, low eccentricity (e < 0.05) and low inclination (i < 5°) or- this trend dominated by the TNOs with 40 AU < a < 50 AU bits beyond ~40 AU from the Sun, as first suggested by Teg- (see Fig. 6), which also show a statistically significant cor- ler and Romanishin (2000) from a much smaller dataset, has relation with inclination and rms velocity. There is a mod- been confirmed by Doressoundiram et al. (2002) and Tru- erate color/perihelion correlation for the entire TNO popu- jillo and Brown (2002). Doressoundiram et al. (2002) have lation, but it is at the threshold of significance considering shown that this cluster of low-i classical TNOs is statisti- the number of orbital parameters we are testing and is not cally distinct from the others classical TNOs (higher i, di- significant for any subpopulation. Thus, we consider both

TABLE 1. Color correlations.

Correlation Significance Significance Population Color vs. . . . N (Gaussian) (1 – Conf.) Significant? All TNOs (q > 25 AU) rms velocity 141 5.7σ 1 × 10–8 Yes All TNOs (q > 25 AU) Inclination 141 5.5σ 4 × 10–8 Yes All TNOs (q > 25 AU) Perihelion 141 3.8σ 2 × 10–4 Maybe All TNOs (q > 25 AU) Eccentricity 141 3.1σ 2 × 10–3 No Classical TNOs (40 < a < 50 AU) rms velocity 78 4.5σ 7 × 10–6 Yes Classical TNOs (40 < a < 50 AU) Inclination 78 4.9σ 8 × 10–7 Yes Classical TNOs (40 < a < 50 AU) Perihelion 78 2.5σ 1 × 10–2 No Classical TNOs (40 < a < 50 AU) Eccentricity 78 1.3σ 0.2 No Scattered (a > 50 AU) rms velocity 26 1.2σ 0.2 No Scattered (a > 50 AU) Inclination 26 1.2σ 0.2 No Scattered (a > 50 AU) Perihelion 26 0.6σ 0.5 No Scattered (a > 50 AU) Eccentricity 26 1.3σ 0.8 No Plutinos (38.5 < a < 40 AU) rms velocity 32 0.0σ 1.0 No Plutinos (38.5 < a < 40 AU) Inclination 32 0.0σ 1.0 No Plutinos (38.5 < a < 40 AU) Perihelion 32 0.2σ 0.8 No Plutinos (38.5 < a < 40 AU) Eccentricity 32 0.1σ 0.9 No The criterion for statistical significance is set to 3.8σ in this investigation as we tested for correlations between color and 16 different parameter/subpopulation combinations, as explained in the text. 100 The Solar System Beyond Neptune

Fig. 6. Color metric S for the classical TNOs vs. inclination and rms orbit velocity Vrms. A least-squares linear slope has been fitted to the data to guide the eye. Both of these correlations are significant at the 4σ level using the Spearman test, which does not assume a functional form to the correlation. the color/inclination and color/rms velocity correlations to shank et al., 1976); Neptune’s satellite , which may be statistically significant. be a captured TNO (Cruikshank et al., 1993); (Brown Although the Spearman rank correlation test excels at et al., 2005); and 2005 FY9 (Licandro et al., 2006). Miner- determining whether a correlation is statistically significant, alogical bands are seen in the spectra of 2003 AZ84 (For- it is not useful as a test to determine which correlation is nasier et al., 2004b), Huya, and 2000 GN171 (Lazzarin et more significant, the inclination or the rms velocity correla- al., 2003). tion. Thus, it remains to be seen whether a specific testable Despite the small sample size, is there any correlation mechanism can be found that produces either an inclina- between the presence of CH4, H2O bands, and surface color? tion/color correlation or a rms velocity/color correlation. The seven TNOs exhibiting H2O bands display colors rang- ing from B–V = 0.63 ± 0.03 for 2003 EL61 (Rabinowitz et 5. COLORS AND SURFACE PROPERTIES al., 2006) to B–V = 0.96 ± 0.08 for Varuna. For reference, Pluto and Charon have B–V = 0.87 ± 0.01 and B–V = 5.1. Colors and Chemical Properties 0.70 ± 0.01 (Binzel, 1988). The four TNOs exhibiting CH4- ice bands and the three TNOs exhibiting mineralogical Is there any correlation between the presence of a par- bands display a similar wide range of B–V colors. So far, ticular ice or mineralogical absorption band in the spectra there is not any obvious correlation between the presence of of TNOs and their colors? For example, do TNOs with CH4- an ice or mineralogical band and the B–V colors of TNOs. ice bands in their spectra display redder surfaces than TNOs However, larger samples may allow a better test. with H2O-ice bands in their spectra? This is a reasonable correlation to study because Pluto exhibits CH4 bands and 5.2. Modeling of Surface Colors it has a redder color than Charon, which exhibits H2O-ice bands. What can modeling tell us about the surface colors? By The difficulty with looking for such a correlation among comparing broadband photometric and spectroscopic obser- TNOs is that there are only a handful of objects that are vations with radiative transfer models (Hapke, 1981; Douté known to exhibit absorption bands in their spectra. In partic- and Schmitt, 1998), it is possible to constrain the chemical ular, H2O-ice bands are seen in spectra of Charon, 1996 composition of TNO surfaces. In particular, radiative trans- TO66 (Brown et al., 1999), Varuna (Licandro et al., 2001), fer models make it possible to transform laboratory optical Quaoar (Jewitt and Luu, 2004), Orcus (Fornasier et al., constants for candidate surface materials such as organic 2004a), and 2003 EL61 and its satellite (Barkume et al., material ( and kerogen), dark material (amorphous 2006). CH4-ice bands are seen in spectra of Pluto (Cruik- carbon), ices, and silicates (tremolite) into reflectance spec- Doressoundiram et al.: Color Properties 101 tra for comparison with observations. By inputting differ- ter of classical TNOs discussed in section 4) remained far ent percentages of candidate materials in a radiative trans- enough away from Neptune that they were never perturbed fer model and finding the best match between the theoreti- much by the planet. Perhaps around 40 AU from the Sun, cal spectra and the observed spectra, it is possible to went from condensing in a water-ice rich clathrate constrain the chemical composition and grain sizes on the to condensing as pure methane (Lewis, 1972). Whereas the surfaces of TNOs. loss of methane from a clathrate surface would result in a What sort of compositions do the models suggest for ob- lag made up of colorless water-ice crust, a pure methane-ice jects at the extreme ends of the TNO color range, i.e., a red crust would provide much material for alteration into red vs. a gray TNO? It appears the observed red colors of TNOs organic compounds, even if there were a substantial amount are consistent with the presence of a tholin-like material of methane sublimation. If the dynamical simulation and (Cruikshank et al., 1998; see also chapter by de Bergh et this idea about methane surface chemistry are correct, SDOs, al.). Tholins are synthetic macromolecular compounds pro- high-i classical TNOs, and high-i Plutinos should exhibit duced from irradiated gaseous or solid mixtures of simple gray surface colors and low-i classical TNOs should exhibit hydrocarbons, water, or (Sagan and Khare, 1979). red surface colors. The SDOs are largely gray and the low-i Although their optical properties depend on the original classical TNOs are red; however, additional observations are mixture and conditions of irradiation, all tholins show a necessary to see if the high-i classical TNOs and the high-i common characteristic, i.e., colors ranging from yellow to Plutinos are largely gray. red. Evidently, the numerous overlapping electronic bands of these complex organic molecules produce a red pseudo- 6.2. Evolutionary Processes continuum at ultraviolet and optical wavelengths. Dores- soundiram et al. (2003) find the red color, V–J = 2.44 ± The red colors of TNOs and Centaurs are usually attrib- 0.06, of 26181 (1996 GQ21) is consistent with a mixture of uted to the effects of surface aging and darkening due to 15% tholin (Khare et al., 1984), 35% ice tholin I high-energy radiation and particle bombardment in inter- (Khare et al., 1993), and 50% amorphous carbon. It is im- planetary space, also called space weathering (see chapters portant to note that such a model is only a suggestion of by Hudson et al. and de Bergh et al.). Blue surface colors can what might be the nature of the surface material. The solu- be produced by major collisions with other objects through tion is not unique, given the many unknown parameters in deposits of fresh icy material from the body interior or from the models. the impactor. Smaller impacts could also refresh the sur- At the other extreme of color, de Bergh et al. (2005) face through so-called impact gardening. Both resurfacing found that the visible and infrared colors and spectra of the processes (irradiations and collisions) have very long time- gray TNO Orcus, V–J = 1.08 ± 0.04, is consistent with a scales (on the order of millions of years). A complicating Hapke-type model that has 5% H2O-ice at 40 K, 42% kero- situation may result from a reduction of the material red- gen, and 53% amorphous carbon. Terrestrial kerogens are dening for very intense and/or very long irradiation times. the product of decay of organic matter, but interstellar dust This is indicated by laboratory experiments performed on and some carbonaceous meteorites contain materials of sim- asphaltite material (Moroz et al., 2003). Resurfacing on a ilar structure of nonbiological origin. Kerogens have been much shorter timescale could happen due to ice reconden- used to model the spectra of some asteroids. All compo- sation and/or dust deposition from a temporary atmosphere nents in the model of Orcus had a grain size of 10 µm. For produced by outgassing due to solar heating, and from dust reference, the Sun has V–J = 1.08. The chapters of de Bergh coma activity. N2 and CO ices may be able to sublimate at et al. and Barucci et al. in this book give a more complete distances of 40 AU and beyond (Delsemme, 1982). This ice overview on spectral modeling and links between color sublimation process works quite efficiently for Pluto, as well properties and composition. as possibly also for Charon (Yelle and Elliot, 1997) and Chi- ron (Meech et al., 1997). 6. ORIGIN OF THE COLOR ANISOTROPY The first numerical simulation results of TNO colors AND PROPOSED RESURFACING SCENARIOS were performed using simplified reddening and impact re- surfacing models (Luu and Jewitt, 1996). The results show 6.1. A Primordial Origin that the range of colors observed in TNOs can be well re- produced. Typically, red objects are exposed to high-energy A dynamical simulation (Gomes, 2003; see also chapter radiation for a long time (on the order of 106 yr) without by Morbidelli et al.) and some thoughts on methane chemis- resurfacing by collision. In turn, resurfacing by collision try in the outer solar system provide a way of interpreting events produces “sharp” short-term color changes to neu- the colors of TNOs. The dynamical simulation predicts that tral or at least less red values in the objects. The modeling, as Neptune migrated outward, it scattered objects originally and more recent work by Delsanti et al. (2004), did not 25 AU from the Sun into the orbits of the present-day SDOs, constrain conclusively the importance of collisions in the high-i classical TNOs (i > 5°), and high-i Plutinos. In con- Edgeworth-Kuiper belt. 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