Color Properties and Trends of the Transneptunian Objects · 2008-01-23 · outer solar system. Multicolor broadband photometry is the only tool at the moment that al-lows characterization

Doressoundiram et al.: Color Properties 91

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Color Properties and Trends of the Transneptunian Objects

A. DoressoundiramObservatoire de Paris

Hermann BoehnhardtMax-Planck Institute for Solar System Research

Stephen C. TeglerNorthern Arizona University

Chad TrujilloGemini Observatory

The color of transneptunian objects (TNOs) is the first and basic information that can beeasily obtained to study the surface properties of these faint and icy primitive bodies of theouter solar system. Multicolor broadband photometry is the only tool at the moment that al-lows characterization of the entire population that is relevant for statistical work. Using thecolors available for more than 170 objects it is possible to get a first glance at the color distri-bution in the Edgeworth-Kuiper belt. First, results show that a wide color diversity character-izes the outer solar system objects. Transneptunian objects have surfaces showing dramaticallydifferent 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 TNOsbeyond 40 AU) could be identified. Furthermore, evidence for correlations between colors andorbital parameters for certain objects have been found at a high significance level. Both colordiversity and anisotropy are important because they are diagnostic of some physical effectsprocessing the surfaces of TNOs and/or some possible composition diversity. In this paper, wewill review the current knowledge of the color properties of TNOs, describe the observed colordistribution and trends within the Edgeworth-Kuiper belt, and address the problem of theirpossible origin.

1. INTRODUCTION

It is now clear that Pluto, Charon, and the ≈1200 known(as of January 2007) transneptunian objects (TNOs) arewhat remain of an ancient disk of icy debris that did notaccrete into a giant, jovian-like planet beyond the orbit ofNeptune. By studying TNOs, it is possible to examine thepreserved building blocks of a planet, and thereby shedsome light on the process of planet building in our solarsystem as well as extrasolar planetary systems.

A photometric survey is a natural first step in the investi-gation of TNOs because it is the only kind of survey capa-ble of providing a global view of the transneptunian belt.Specifically, it is possible to obtain accurate magnitudes andcolors for all of the known TNOs using 2-m- to 10-m-classtelescopes. Accurate magnitudes and colors for a large num-ber of TNOs provide a starting point and context for morein-depth techniques such as spectroscopy and spacecraftflybys. It is also possible to look for statistically significantcorrelations between colors and other properties of TNOs

(e.g., orbital properties). Such correlations may yield insightinto the important formation and evolution processes in theouter solar system.

An early expectation was that all TNOs should exhibitthe same red surface color. But why were outer-main-beltasteroids and jovian trojans known to exhibit red colors (e.g.,see Degewij and van Houten, 1979)? In addition, Gradieand Veverka (1980) suggested that organic materials —molecules defined by C–H bonds — should readily form atlarge heliocentric distances and cause redder colors at largeheliocentric distances. Gradie and Tedesco (1982) discov-ered a correlation between color and semimajor axis of as-teroids, implying that asteroids preserve a record of solarsystem formative and evolutionary processes at various he-liocentric distances, rather than being a chaotic mixture. Theextraordinary red color of the early Centaur [5145 Pholus(Mueller et al., 1992)] and TNO [1992 QB1 (Jewitt and Luu,1993)] discoveries seemed to confirm the idea that objectsat large heliocentric distances exhibited red surface colors.Transneptunian objects were thought to form over a small

92 The Solar System Beyond Neptune

range of distance from the Sun where the temperature inthe young solar nebula was the same. The similar tempera-ture suggested that TNOs formed out of the solar nebulawith the same mixture of molecular ices and the same ratioof dust to icy material. In addition, their similar formationdistance from the Sun suggested that TNOs experienced asimilar evolution. For example, the irradiation of surfaceCH4 ice by cosmic rays, solar ultraviolet light, and solarwind particles could convert some surface CH4 ice into red,complex, organic molecules. CH4 ice was known to existon the surface of Pluto (Cruikshank et al., 1976). Labora-tory simulations supported the conversion of CH4 ice intocomplex organic material (e.g., Moore et al., 1983; Straz-zulla et al., 1984; Andronico et al., 1987). By their nature,the complex organic molecules were expected to absorbmore incident blue sunlight than red sunlight. Therefore,the light reflected from the surfaces of TNOs, and observedon Earth, was expected to consist of a larger ratio of red toblue light than the incident sunlight. It was a surprise, there-fore, to discover that TNOs exhibited a wide range of colors.

Dynamically, the Edgeworth-Kuiper belt is stronglystructured, and three main populations are usually distin-guished within this region. The resonant TNOs are trappedin mean-motion resonances with Neptune, in particular the2:3 at 39.4 AU (the so-called “Plutinos”), and are usuallyon highly eccentric orbits. The less-excited classical TNOs,also called “classicals,” populate the region between the 2:3and the 1:2 (say 40 AU < a < 50 AU) resonances. The “scat-tered disk objects” (SDOs) make up a less-clearly-definedpopulation and are mainly objects with high eccentricity eand perihelion near Neptune that were presumably placedin these extreme orbits by a weak interaction with Neptune.The “Centaurs,” finally, represent a dynamical family of ob-jects in unstable orbits with semimajor axes between Jupiterand Neptune. The classification given here is historicallythe first one adopted by the community, but the frontiersbetween each group are not easy to define. Moreover, theclassicals are a diverse population consisting of objectsranging from low to very high degrees of dynamical exci-tation. Obviously this population needs to be dissected care-fully. A most complete and rigorous classification is dis-cussed in the chapter by Gladman et al.

How do the color properties compare within each dy-namical group of TNOs? Answering this question will pro-vide important clues to understand how these objects havebeen formed and how their surface properties have evolved.Indeed the different orbital properties characterizing eachdynamical family of TNO should have a distinct impact onthe color properties of the surfaces of TNOs. For example,those objects in extreme orbits (high i and e) experiencemore energetic collisions than those in circular orbits. Suchenergetic collisions in turn have a significant impact on re-surfacing, thus on the color of the surface.

In the sections that follow, we discuss observational strat-egies, data reduction techniques, and analysis methods ofTNO photometric surveys (section 2), observed optical andnear-infrared colors (section 3), correlations between col-

ors and orbital elements (section 4), links between colorsand chemical and mineralogical properties of TNOs (sec-tion 5), and possible processes responsible for the observedcolors of TNOs (section 6).

2. PRINCIPLE AND TOOLS OFTRANSNEPTUNIAN OBJECT PHOTOMETRY

2.1. Observational Strategy

Due to the faintness of the TNOs and Centaurs, it is avery difficult and telescope-time-consuming task to obtainspectroscopy of a statistically representative sample thatcould be used for in-depth studies of surface properties andtheir correlations with other physical, dynamical, formation,and evolutionary parameters of the objects. However, a firstand much faster (in terms of telescope time) assessmentof intrinsic surface properties of these objects is possiblethrough photometric characterization of their reflectancespectra by determining broadband filter colors and spectralgradients derived from the filter measurements. It is as-sumed that sunlight is reflected at the surfaces of the objectsonly, and no atmosphere or dust coma is present. Activityinduced by intrinsic processes (gas evaporation or cometaryactivity) or external processes (impacts) is presumed to playa role in the resurfacing of TNOs and Centaurs. In rarecases, such as Pluto (with a tenuous atmosphere) and Chiron(showing episodic cometary activity), the presence of anatmosphere and/or a dust coma may affect the interpretationof the measured colors of the objects.

Since they are well characterized and available at manyobservatories, astronomical broadband filters are used forthe photometric measurements of TNOs and Centaurs, i.e.,BVRI for the visible wavelength range and JHK for thenear-IR. Due to the faintness of the objects in the respec-tive wavelength range, U and L and M filters can only beused for the very brightest objects (e.g., Pluto-Charon). Forthe visible, the vast majority of data are available in theBessel filter set, while only a few measurements are ob-tained using the Johnson filter set (Sterken and Manfroid,1992, and references therein), which differs from the formerone in the transmission ranges of the R and I filters. Forthe near-IR filter set, the differences in the Js and Ks trans-mission ranges compared to standard J and K filters (Glass,1997, and references therein) is of minor importance forcolor studies of the objects.

Transneptunian objects are challenging to observe be-cause they are faint, move relative to the “fixed” back-ground of stars and galaxies, and exhibit brightness varia-tions (lightcurves). In this section, we discuss these chal-lenges and techniques to overcome them. Note that theseproblems are reminiscent of the first works performed onmain-belt asteroids in the early 1960s and 1970s whenavailable technology at that time did not allow the use ofmore sophisticated techniques, i.e., spectroscopy (see Mc-Cord and Chapman, 1975; Bowell and Lumme, 1979, andreferences therein). Then the same logic was applied as


observers progressed from the main belt to Hildas, Trojans(Hartmann et al., 1982), and finally Centaurs and TNOs(Luu and Jewitt, 1996).

2.1.1. Faintness. First, the most challenging problemis that the TNO population represents some of the faintestobjects in the solar system. The typical apparent visual mag-nitude of a TNO is about 23 mag, although a few objectsbrighter than 20 mag are known. Another criterion is theminimum signal-to-noise ratio (SNR) of the photometry:Typically, SNR ~30 (corresponding to an uncertainty of0.03–0.04 mag) is required to accomplish the spectral clas-sification. Indeed, the differences among the known typesof minor bodies (which to first order have the color of theSun) are much more subtle than for stellar types, so con-siderably higher photometric accuracy is necessary. Themore limited the range of wavelengths, the higher the ac-curacy needed to distinguish objects of different type. How-ever, to reach such a SNR goal, one needs to overcome twoproblems: (1) the sky contribution, which could be impor-tant and critical for faint objects not only in the infrared,but also for visible observations; and (2) the contaminationby unseen background sources such as field stars and gal-axies. For instance, the error introduced by a 26-mag back-ground source superimposed on a 23-mag object is as largeas 0.07 mag. One solution to alleviate these problems is theuse of a smaller aperture for the flux measurement of theobject. This method is described in the next section.

2.1.2. Motion relative to background. Transneptunianobjects, while at very remote heliocentric distance, still havenoticeable motion that restricts the exposures to relativelyshort integration times. At opposition, the motion of TNOsat 30, 40, and 50 AU are, respectively, about 4.2, 3.2, and2.63/h, thus producing a trail of ~1.03 in 15 min exposuretime in the worst case. The trailing of an object during anexposure has devastating effects on the SNR, since the fluxis diluted over a larger area of background sky. This dilu-tion, in turn, introduces higher noise. Thus, increasing ex-posure time will not necessarily improve the SNR for TNOphotometry. For practical purposes, the exposure time ischosen such that the trailing due to the object’s motion doesnot exceed the size of the seeing disk. The observer thentakes and combines a number of untrailed exposures to im-prove the SNR. An alternative is to follow the object at itsproper motion. In this case, however, one faces anotherproblem: The point-spread function of the object (PSF)would be obviously different from that of the field stars.Moreover, the so-called aperture correction technique usedvery frequently for accurate TNO photometry would be-come very difficult since this method requires the PSF cali-bration of nearby field stars (see next section).

2.1.3. Lightcurves. The color of a TNO or Centaur isideally measured simultaneously for the two or more fil-ters in order to guarantee that the same surface area of theobject is imaged at the same time. However, the majorityof color measurements are obtained by exposing the objectthrough different filters sequentially. In order to avoid colorchanges induced by albedo and/or shape variations of the

likely rotating body, it is important to measure the objectflux through the various filters quasi-simultaneously, i.e.,within a time interval that is short compared to the rotationperiod of the object. For instance, for an object with a 10-h rotation period, the phase angle of the surface changes by10° in 30 min. Hence, very fast rotators can mimic strangesurface colors or unexpected color variations [see, e.g.,1994 EV3 (Boehnhardt et al., 2002)]. Since for many ob-jects the exact rotation period is unknown, it is thus advis-able to monitor changes in the object brightness due torotation by repeated exposures in a single filter (e.g., V fil-ter) intermittent during the complete sequence of filter ex-posures needed for the color measurement of the object. Ifthe rotation period is known, one can phase the filter ex-posures to appropriately image the same surface area un-der the same illumination conditions.

2.2. Data Reduction Techniques

The data reduction consists of the basic reduction stepsapplicable for the visible and near-IR photometric datasets,i.e., bias and flatfield corrections, cosmic-ray removal,alignment and co-addition of the jittered images, and fluxcalibration through standard stars.

The brightness of the object is frequently measuredthrough the so-called aperture correction technique (Howell,1989; Tegler and Romanishin, 1997; Doressoundiram et al.,2001) as justified by the faintness of the TNOs. The basisof this method is that the photometric measurement is per-formed by using a small aperture on the order of the size ofthe seeing disk. Consequently, the uncertainty in the meas-urement is reduced because less noise from the sky back-ground is included in the aperture. However, by doing so,one loses light from the object. Thus, to determine howmuch light is thrown away, the so-called “aperture effect”is calibrated using a large number of nearby field stars. Thisis reasonable as long as the motion of TNOs during eachexposure is smaller than the seeing, and hence the TNOs’point-spread functions (PSFs) are comparable to those offield stars. For all the photometry, the sky value can be com-puted as the median of a sky annulus surrounding the ob-ject. The advantages in the use of a small aperture are (1) adecrease of the contribution of the sky, which could be im-portant and critical for faint objects; and (2) a reduction ofthe risk of contamination of the photometry by unseen back-ground sources.

2.3. Analysis Methods

Many useful physical parameters of TNOs can be de-rived from broadband photometry. These parameters includecolor, spectral gradient, absolute magnitude, and size.

2.3.1. Color indices. The color indices used here (suchas U–V, B–V, etc.) are the differences between the magni-tudes obtained in two filters. In other words, the F1–F2 colorindex (where F1 and F2 are any of the UBV, etc., filters) isthe ratio of the surface reflectance approximately valid for


the central wavelengths λ1 and λ2 of the corresponding fil-ters.

2.3.2. Reflectance spectrum. The information con-tained in the color indices can be converted into a very-low-resolution reflectance spectrum RF using

RF = 10–0.4 (MF – MFSun)

where MF and MFSun are the magnitudes in filter F of theobject 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

RF,V = 10–0.4 [(MF – MV) – (MF – MV)Sun]

The filter magnitudes and colors of the Sun for the fil-ters commonly used can be found in Hardorp (1980) andDegewij et al. (1980). Values of the main colors for the Sunused 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 thecoarse reflectance spectrum using broadband filter photom-etry compared to spectroscopy of a TNO.

2.3.3. Spectral gradient. The spectral gradient S is ameasure of the reddening of the reflectance spectrum be-tween two wavelengths. It is expressed in percent of red-dening per 100 nm

S(λ2 > λ1) = (RF2,V – RF1,V)/(λ2 – λ1)

where λ1 and λ2 are the central wavelengths of the F1 andF2 filters, respectively. S, given in percent of reddening per100 nm wavelength difference, is intimately related to theconstitution of the surface of the object, although at presentit is not possible to draw any detailed conclusions fromspectral gradients (or colors) on specific surface properties.By definition, spectral gradient values are a direct measurefor the intrinsic reddening of the object produced by thesurface properties of the object, i.e., the solar colors are“removed”; hence, S = 0 means exactly solar colors. If sev-eral filters are measured over a wider wavelength range (e.g.,BVRI to cover the visible spectrum), the spectral gradientscan be averaged over the main adjacent color indices (e.g.,B–V, V–R, R–I) in order to obtain the overallslope of thereflectance spectrum between the two limiting wavelengths.

2.3.4. Absolute magnitude. The absolute magnitude ofa TNO is the magnitude at zero phase angle and at unit he-liocentric and geocentric distances. Geometrical effects areremoved by reducing the MF visual magnitude (in the F fil-ter) to the absolute magnitude MF(1,1,0) using

MF(1,1,0) = MF – 5 log(rΔ) – αβ

where r, Δ, and α are respectively the heliocentric distance(AU), the geocentric distance (AU), and the phase angle(deg). The term αβ is the correction for the phase bright-ening effect (Belskaya and Shevchenko, 2000; see also thechapter by Belskaya et al.). However, the phase function is

completely unknown for most of the TNOs. Based on afirst-phase-curve study of a few TNOs, Sheppard and Jewitt(2002) have shown almost linear and fairly steep phasecurves in the range of phase angles from 0.2° to 2°. Theyfound an average β of 0.15 mag/deg. A similar steep slopewas found for Centaurs (Bauer et al., 2002). This impliesa possible considerable error in H calculations disregardingthe phase correction. Further studies have also been mademeasuring phase curves in parallel with polarimetry (Bag-nulo et al., 2006; Boehnhardt et al., 2004).

2.3.5. Size. Size is the most basic parameter defining asolid body. Unfortunately, sizes (and albedos) are difficultto determine as they mostly require thermal measurements.Hence objects with accurate size determination are few (seechapter by Stansberry et al.). Consequently, for most ob-jects, a canonical geometric albedo p is assumed and theabsolute magnitude MF(1,1,0) can be converted into theradius R of the object (km) using the formula by Russell(1916)

pR2 = 2.235 × 1016 100.4(MFSun – MF(1,1,0))

where MFSun is the magnitude of the Sun in the filter F(MVSun = –26.76). Owing to the lack of available albedomeasurements, it has become the convention to assume analbedo of 0.04, common for dark objects and cometary nu-clei. However, one should be aware of the fact that the sizes

Fig. 1. Reflectance spectrum, broadband filter brightness, andspectral gradient of the TNO 2001 KX76 or (28978) Ixion. Thereflectance is shown normalized to unity at 550 nm. The BVRIbroadband filter brightness is plotted by “star” symbols (from shortto long wavelength) over the central wavelength of the respectivefilter bandpass. The spectral gradient fitted to the spectroscopyand photometry of the object is shown as a dotted line. Neutral/solar reflectance is represented by the dashed line.


are purely indicative and are largely uncertain. For instance,if we would use, instead, an albedo of 0.14 (i.e., the albedoof the Centaur 2060 Chiron), the results for size estimateswould have to be divided by a factor of about 2.

Having these limitations in mind (unconstrained phasefunction and albedo), in all the following analysis and fig-ures that make use of absolute magnitude and size, we havetaken the above values for the phase correction and an av-erage albedo of 0.09 for the geometric albedo (R band).

3. COLOR DIVERSITY ANDSPECTRAL GRADIENT

O. Hainaut from the European Southern Observatoryin Chile has compiled and maintains a database of colormeasurements of TNOs, Centaurs, and short-period comets.The database can be accessed at www.sc.eso.org/~ohainaut/MBOSS. As of late September 2006, this MBOSS databasecontains values for 209 objects (Plutinos 32; classicals 95;SDOs 32; Centaurs 30, comets 20) at 1077 epochs cover-ing the UBVRIJHKLM filter set (not all the objects havethe full filter set). It also provides references to the valuesstored. (Note that Tegler and Romanishin have also putcolors and magnitudes from their survey for ~120 TNOsand Centaurs on the web at www.physics.nau.edu/~tegler/research/survey.htm.)

Both colors and spectral gradients are “integral” charac-terization parameters of surface properties of the objects:“integral” over the illuminated and visible part of the sur-face, which for TNOs and distant Centaurs is almost equiva-lent to a complete hemisphere since the phase angles aresmall, and “integral” over the wavelength range of the fil-ters used.

3.1. Color-Color Diagrams ofTransneptunian Objects

Color-color diagrams show two measured color indicesof the object sample vs. each other, e.g., V–R color vs. B–V color as measured for TNOs and/or Centaurs. Solar colorsprovide the reference for zero intrinsic reddening. Objectswith “higher” color indices than solar are called “redder”than the Sun, those with “smaller” values are “bluer” thanthe Sun. The “redder”/“bluer” colors are equivalent to a pos-itive/negative spectral gradient compared to the solar spec-trum. For guidance, the reddening trend line can be drawn inthe color-color diagrams: This line connects locations inthe color-color diagram with increasing values of constantspectral reflectance slope. Deviations from the reddeningtrend line indicate a nonlinear behavior of the intrinsic red-dening over the spectral range covered by the filters of thecolor-color diagram. Examples for color-color diagrams ofTNOs and Centaurs are shown in Fig. 2.

Color changes over the body’s surface combined withrotation of the object can result — in principle — in varia-tions of the object’s colors depending on the rotation phasewhen the measurements are performed (even for simulta-

neous or quasi-simultaneous filter exposures). For Centaursin eccentric orbits, changes in the aspect angle due to or-bital motion can also result in color variations for objectswith nonhomogenous surface colors. (Due to the long or-bital periods of TNOs, changes of the aspect angle along theorbit may happen over timescales of decades only, a timeinterval much longer than the time span during which fil-ter observations of TNOs have been performed up to now.)Similar statements were also made in the 1960s to 1980swhen interpreting rotational effects and albedos and colors(see, e.g., Bowell and Lumme, 1979; French and Binzel,1989). Rotation phase resolved color measurements of onlya few objects are published so far (see chapters by Sheppardet al. and Belskaya et al.). In order to achieve a completecharacterization of the color properties of a body, full cov-erage of the rotation (aspect) phase range is required (butrarely done). In cases where several color measurements areavailable, averaging of the results can be performed to ob-tain a mean value for the colors and spectral gradients.

Color-color diagrams of TNOs (as well as of Centaursand cometary nuclei; see Fig. 2) in the visible show a widedistribution from neutral and even slightly “bluish” to veryred values. Figure 2 also shows the various dynamicalclasses of the TNOs (i.e., classical objects, Plutinos, scat-tered disk objects) and the Centaurs. All subclasses are colorundistinguishable, which is consistent with a common ori-gin for these objects.

For the overall TNO population (of more than 150objects with BVRI color measurements) clustering is notobvious although originally proposed based upon muchsmaller samples (Tegler and Romanishin, 1998). However,clustering in color-color diagrams is found when consider-ing different populations of TNOs and Centaurs (see dis-cussion below). The trend line overplotted in Fig. 2 repre-sent the locus of object with a linear reflectance spectrum.The “diagonal orientation” of the TNO cloud in the V–Rvs. B–V plot in Fig. 2, following the trend line of increasedreddening, suggests constant surface reddening from B to Rfor the majority of the objects. Instead, the respective R–Ivs. B–V color-color plot in Fig. 2 clearly indicates system-atic deviations from the trend line toward smaller redden-ing at the long wavelength end of the visible spectrum. Innear-IR color-color diagrams (H–K vs. J–H in Fig. 3), astrong clustering of TNOs around solar colors is found thatclearly indicates flat and close to neutral surface colors forthe majority of the objects. Very few objects show signifi-cant reddish colors (Delsanti et al., 2006). Outliers towardbluer than solar colors exist and may be due to absorptionbands of surface ices (e.g., H2O, CH4) with influence onbroadband colors (in particular in H and K filters). In thisrespect “bluish” near-IR colors may be used to identifypotential objects with ice absorption spectra — although thephotometric indices are certainly not qualified to replacespectroscopic analysis of the objects for ice signature de-tections. The changeover from the red color in visible tothe more neutral near-IR spectrum in the individual objectshappens between about 750 and 1400 nm and thus affects


mostly the I and J filter reflectance. However, it also ex-plains the systematic deviations from the trend lines in R–Ivs. B–V color-color diagrams. In other words, visible colorsare mutually correlated, while they appear to be unrelatedto infrared colors (Doressoundiram et al., 2002; Delsantiet al., 2006).

3.2. Spectral Gradient Histograms ofTransneptunian Objects and Centaurs

The full range of spectral gradients of the object sampleshould be covered by a dense set of [Smin, Smax] pairs, thelower 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 Centaursare shown in Fig. 4. In the following analysis spectral gra-dients among TNOs and Centaurs have been obtained fromBVRI broadband photometry extracted from the MBOSSdatabase.

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 inthe visible wavelength range where only weak absorptionbands are found in a few TNOs (see chapter by Barucci etal.) without noticeable effects on the filter magnitudes. Thenear-IR wavelength region contains various strong absorp-tion bands of H2O and CH4 ices, which have been found insome TNOs. Hence, effects on the surface colors are pos-sible and, indeed, the “bluish” colors J–H and/or J–K maybe due to these ice absorptions (see below).

The range of spectral gradients of TNOs and Centaursin the visible wavelength region ranges from –5%/100 nmto 45%/100 nm, with the exception of some very red Cen-taurs. The spectral gradient distributions for the four majordynamical 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 ahigh number at low reddening (5–15%/100 nm, comparableto the range of the distribution maximum for the Plutinosand 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-spikestar). The diagrams apply for broadband filter results in BVRI.Solar colors are indicated by an open five-spike star symbol. Thecurve is the locus of object with a linear reflectivity spectrum. TheSun, as a reference, has a linear reflectivity spectrum with a nullslope. A tick mark is placed every 10%/100 nm; the curve is grad-uated in units of spectral slope from 0 (solar) to 70%/100 nm (veryred). Plots are from the web page of O. Hainaut (www.ls.eso.org/~ohainaut/MBOSS), who compiles photometric results of minorbodies in the outer solar system.


45%/100 nm, similar to the main maximum in the classicalshistogram). The structured histograms suggest that furthersubpopulations exist for classicals and Centaurs, which aredescribed and analyzed by more sophisticated statisticalmethods below. The overall reddening distributions of theTNOs 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 notvery instrumental for population classification except for theidentification and analysis of outliers.

Such analysis is reminiscent of early work done withasteroids in the 1970s and 1980s. In particular, a relationbetween color (or spectral gradient) and ice abundance inouter 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 authorsshowed a direct correlation between position in a V–J vs.J–K diagram, and the measured albedos and ice contentsof well-observed satellites and asteroids.

4. COLOR DISTRIBUTION OFTHE TRANSNEPTUNIAN OBJECTS:

STRONGLY SHAPED

The main purpose is to see if color is a tracer for anyphysical process. While any physical processes are of in-terest, we have very little detailed knowledge of physicalmechanisms. The physical processes that are easiest to test

Fig. 3. J– H vs. H–K color-color diagram of TNOs and Centaurs.Symbols are Plutinos = open triangles, classicals = filled circles,SDOs = open pentagons, Centaurs = open squares, Trojans = filledtriangles, comets = open four-spike star, Sun = open five-spike star,trend line of increased reddening = solid line. This line is the lo-cus of objects with a reflectivity spectrum of increasing linearslope (see also Fig. 2). Most of the points lie below the redden-ing curve. This is an indication for a change and decrease of thespectral slope over the JHK range. The two outliers are (19308)1966 TO66 (top left) and (24835) 1995 SM55 (bottom left).

Fig. 4. Spectral gradient histogram of TNOs and Centaurs (after Doressoundiram and Boehnhardt, 2003).


with such limited knowledge consist of comparisons ofcolor with combinations of orbital physical parameters.

4.1. Database of Colors and Color Indices

For this analysis, we restrict our sample to those collatedin the MBOSS database used in the previous section. Herewe focus on the visible colors of the TNO surfaces. Theanalysis is made simpler by the fact that visible colors aremutually correlated throughout the VRI regime (Boehnhardtet al., 2001; Doressoundiram et al., 2002).

This is the basic premise behind the supposition that thecoloring agent could be tholin-like materials (Jewitt andLuu, 2001; Cruikshank et al., 2005), which tend to producea uniform color gradient throughout the visible region. Thisfact allows the transformation of most color values in theMBOSS database to a common reddening scale, the percentof reddening per 100 nm, S (see section 2.3) implementedfor the MBOSS database by Hainaut and Delsanti (2002).For objects with multiple color values, all are combined intothis metric with formal error propagation.

A plot of true V–R vs. the S metric appears in Fig. 5, il-lustrating that this transformation is valid for objects withmultiple color data. The MBOSS database allows us to lookat the VRI color characteristics among 176 TNOs and Cen-taurs listed in the Minor Planet Center database.

4.2. Correlations

The main purpose of collecting a wide range of colordata is to consider whether TNO surface color is related todynamical factors and can give an indication of how solarsystem wide factors may impact TNO composition. Plates 1and 2 are an overview of the color distribution of TNOsobtained within the Meudon Multicolor Survey (2MS) ofDoressoundiram et al. (2005). The advantage of this viewis that it offers to the eye global patterns between color andorbital elements. Although the search for correlations be-tween colors and dynamical information such as orbital ele-ments is open ended, we here limit the search to basic or-bital element data and a few derived quantities. The mostbasic and robust statistical test searching for correlations isthe Spearman rank correlation test, which does not presup-pose a functional form for the correlation, as do many otherstatistical tests (Spearman, 1904).

4.2.1. Criteria for statistical significance. We compareour color metric S against the most basic of dynamical pa-rameters, orbital elements. Since we are looking for a cor-relation between color and many potential parameters, wemust use a higher criterion for statistical significance thanthe standard 3σ used throughout astronomy. Indeed, simplesimulations show that if a set of 176 uniformly distributednumbers (representing our 176 color values) are comparedagainst 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 andseen for comparison to a single orbital parameter.

Therefore, to properly compare color correlations amongthe orbital parameters, we must raise our threshold to ≈3.5σfor 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 increasesroughly 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 at39.4 AU) nor the SDOs (q near Neptune) have any signifi-cant correlation between the MBOSS colors and any orbitalparameter, and no researchers have reported such correla-tions. For completeness, we do test the Plutinos and SDOshere. It is also quite clear that Centaurs (q > 5.2 AU and a <30.1 AU) have a bimodal color distribution of a strength notseen in any TNO population (Peixinho et al., 2003; Tegleret al., 2003; chapter by Tegler et al.). Discussion of theCentaur population is not included in this work as they rep-resent a population that is much more dynamically unstablethan the TNOs and is potentially affected by recent com-etary activity. Thus, there remain only two populations inthe Edgeworth-Kuiper belt that could have any correlation

Fig. 5. This plot shows a strong correlation between the redden-ing factor S (computed in the visible wavelength) and the V–Rcolor of objects. Thus, our transformation of all color data to thecommon S scale is consistent with measured values of the mostcommon color filter difference, V–R. The use of the S reddeningfactor allows combinations of all visible colors to be used in cor-relation analysis and reduces error bars by significant amounts bycombining data throughout the VRI wavelength region.


between color and orbital parameters: the classical TNOsand the “other TNOs,” TNOs with semimajor axes in therange (40 AU < a < 50 AU) but with eccentricities too highto be considered classicals. We define this population as the“near-scattered TNOs,” since they have similar perihelionproperties to the SDOs, but are close enough that the sepa-ration between them and the classical TNOs is not easilydefined.

It is not easy to determine where the classical TNOs endand the near-scattered TNOs begin. Observers traditionallyarbitrarily choose a minimum perihelion value to distinguishbetween the classical and near-scattered TNOs somewherebetween 36 AU and 41 AU. However, dynamical studieshave shown that the 40 AU to 50 AU region has many nar-row resonances that can mask objects that are true classi-cal TNOs. The lower limit on the perihelion for discrimi-nating the classical TNO population from the near-scatteredTNOs is critical for detecting a color/orbital element corre-lation with either population. Evaluating exactly where theperihelion criterion should be set to define classical TNOsis difficult at best and beyond the scope of this work as itis primarily a dynamical argument (see chapter by Gladmanet al.). Instead we treat all these TNOs as one class, includedin the single denomination of classical TNOs, defined as40 AU < a < 50 AU whatever their eccentricity.

4.2.3. Summary of significant correlations. A statisti-cally significant clustering of very red classical TNOs withlow eccentricity (e < 0.05) and low inclination (i < 5°) or-bits beyond ~40 AU from the Sun, as first suggested by Teg-ler and Romanishin (2000) from a much smaller dataset, hasbeen confirmed by Doressoundiram et al. (2002) and Tru-jillo and Brown (2002). Doressoundiram et al. (2002) haveshown that this cluster of low-i classical TNOs is statisti-cally distinct from the others classical TNOs (higher i, di-

verse colors) at the 99% significance level. This red clus-ter is clearly seen in Plate 1, where objects with periheliondistances around and beyond 40 AU are mostly very red.The cluster members have similar dynamical and surfaceproperties, and they may represent the first taxonomic fam-ily in the Edgeworth-Kuiper belt.

Many studies have been performed to search for corre-lations between color and physical parameters (e.g., size).So far, no significant trend has been found between colorand size, or absolute magnitude. This points out that the col-oring process (whatever it is) is not sensitive to size, at leastin the size range accessible by groundbased observations.

We tested the following four populations: all TNOs (q >25 AU), the Plutinos (38.5 AU < a < 40 AU), the SDOs(q near Neptune), and the classical TNOs (40 AU < a <50 AU). These were tested against the following orbital pa-rameters: inclination, eccentricity, perihelion, and the root-mean-square orbit velocity, Vrms, as discussed by Stern(2002). Indeed, collisional resurfacing could also providea possible explanation for the orbital element dependencyof the color indices: One would naturally expect highlyexcited objects to suffer more energetic impacts. No otherorbital parameters were tested, because no correlations havebeen reported for other parameters. The results of the cor-relation tests are shown in Table 1. It is clear that the en-tire TNO population shows a statistically significant corre-lation between color and both rms velocity and inclination,this trend dominated by the TNOs with 40 AU < a < 50 AU(see Fig. 6), which also show a statistically significant cor-relation with inclination and rms velocity. There is a mod-erate color/perihelion correlation for the entire TNO popu-lation, but it is at the threshold of significance consideringthe number of orbital parameters we are testing and is notsignificant for any subpopulation. Thus, we consider both

TABLE 1. Color correlations.

Correlation Significance SignificancePopulation Color vs. . . . N (Gaussian) (1 – Conf.) Significant?

All TNOs (q > 25 AU) rms velocity 141 5.7σ 1 × 10–8 YesAll TNOs (q > 25 AU) Inclination 141 5.5σ 4 × 10–8 YesAll TNOs (q > 25 AU) Perihelion 141 3.8σ 2 × 10–4 MaybeAll TNOs (q > 25 AU) Eccentricity 141 3.1σ 2 × 10–3 NoClassical TNOs (40 < a < 50 AU) rms velocity 78 4.5σ 7 × 10–6 YesClassical TNOs (40 < a < 50 AU) Inclination 78 4.9σ 8 × 10–7 YesClassical TNOs (40 < a < 50 AU) Perihelion 78 2.5σ 1 × 10–2 NoClassical TNOs (40 < a < 50 AU) Eccentricity 78 1.3σ 0.2 NoScattered (a > 50 AU) rms velocity 26 1.2σ 0.2 NoScattered (a > 50 AU) Inclination 26 1.2σ 0.2 NoScattered (a > 50 AU) Perihelion 26 0.6σ 0.5 NoScattered (a > 50 AU) Eccentricity 26 1.3σ 0.8 NoPlutinos (38.5 < a < 40 AU) rms velocity 32 0.0σ 1.0 NoPlutinos (38.5 < a < 40 AU) Inclination 32 0.0σ 1.0 NoPlutinos (38.5 < a < 40 AU) Perihelion 32 0.2σ 0.8 NoPlutinos (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 differentparameter/subpopulation combinations, as explained in the text.


the color/inclination and color/rms velocity correlations tobe statistically significant.

Although the Spearman rank correlation test excels atdetermining whether a correlation is statistically significant,it is not useful as a test to determine which correlation ismore significant, the inclination or the rms velocity correla-tion. Thus, it remains to be seen whether a specific testablemechanism can be found that produces either an inclina-tion/color correlation or a rms velocity/color correlation.

5. COLORS AND SURFACE PROPERTIES

5.1. Colors and Chemical Properties

Is there any correlation between the presence of a par-ticular ice or mineralogical absorption band in the spectraof TNOs and their colors? For example, do TNOs with CH4-ice bands in their spectra display redder surfaces than TNOswith H2O-ice bands in their spectra? This is a reasonablecorrelation to study because Pluto exhibits CH4 bands andit has a redder color than Charon, which exhibits H2O-icebands.

The difficulty with looking for such a correlation amongTNOs is that there are only a handful of objects that areknown to exhibit absorption bands in their spectra. In partic-ular, H2O-ice bands are seen in spectra of Charon, 1996TO66 (Brown et al., 1999), Varuna (Licandro et al., 2001),Quaoar (Jewitt and Luu, 2004), Orcus (Fornasier et al.,2004a), and 2003 EL61 and its satellite (Barkume et al.,2006). CH4-ice bands are seen in spectra of Pluto (Cruik-

shank et al., 1976); Neptune’s satellite Triton, which maybe a captured TNO (Cruikshank et al., 1993); Eris (Brownet al., 2005); and 2005 FY9 (Licandro et al., 2006). Miner-alogical bands are seen in the spectra of 2003 AZ84 (For-nasier et al., 2004b), Huya, and 2000 GN171 (Lazzarin etal., 2003).

Despite the small sample size, is there any correlationbetween the presence of CH4, H2O bands, and surface color?The seven TNOs exhibiting H2O bands display colors rang-ing from B–V = 0.63 ± 0.03 for 2003 EL61 (Rabinowitz etal., 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 =0.70 ± 0.01 (Binzel, 1988). The four TNOs exhibiting CH4-ice bands and the three TNOs exhibiting mineralogicalbands display a similar wide range of B–V colors. So far,there is not any obvious correlation between the presence ofan ice or mineralogical band and the B–V colors of TNOs.However, larger samples may allow a better test.

5.2. Modeling of Surface Colors

What can modeling tell us about the surface colors? Bycomparing broadband photometric and spectroscopic obser-vations with radiative transfer models (Hapke, 1981; Doutéand Schmitt, 1998), it is possible to constrain the chemicalcomposition of TNO surfaces. In particular, radiative trans-fer models make it possible to transform laboratory opticalconstants for candidate surface materials such as organicmaterial (tholins and kerogen), dark material (amorphouscarbon), ices, and silicates (tremolite) into reflectance spec-

Fig. 6. Color metric S for the classical TNOs vs. inclination and rms orbit velocity Vrms. A least-squares linear slope has been fittedto the data to guide the eye. Both of these correlations are significant at the 4σ level using the Spearman test, which does not assumea functional form to the correlation.


tra for comparison with observations. By inputting differ-ent percentages of candidate materials in a radiative trans-fer model and finding the best match between the theoreti-cal spectra and the observed spectra, it is possible toconstrain the chemical composition and grain sizes on thesurfaces of TNOs.

What sort of compositions do the models suggest for ob-jects at the extreme ends of the TNO color range, i.e., a redvs. a gray TNO? It appears the observed red colors of TNOsare consistent with the presence of a tholin-like material(Cruikshank et al., 1998; see also chapter by de Bergh etal.). Tholins are synthetic macromolecular compounds pro-duced from irradiated gaseous or solid mixtures of simplehydrocarbons, water, or nitrogen (Sagan and Khare, 1979).Although their optical properties depend on the originalmixture and conditions of irradiation, all tholins show acommon characteristic, i.e., colors ranging from yellow tored. Evidently, the numerous overlapping electronic bandsof these complex organic molecules produce a red pseudo-continuum at ultraviolet and optical wavelengths. Dores-soundiram et al. (2003) find the red color, V–J = 2.44 ±0.06, of 26181 (1996 GQ21) is consistent with a mixture of15% Titan tholin (Khare et al., 1984), 35% ice tholin I(Khare et al., 1993), and 50% amorphous carbon. It is im-portant to note that such a model is only a suggestion ofwhat might be the nature of the surface material. The solu-tion is not unique, given the many unknown parameters inthe models.

At the other extreme of color, de Bergh et al. (2005)found that the visible and infrared colors and spectra of thegray TNO Orcus, V–J = 1.08 ± 0.04, is consistent with aHapke-type model that has 5% H2O-ice at 40 K, 42% kero-gen, and 53% amorphous carbon. Terrestrial kerogens arethe product of decay of organic matter, but interstellar dustand some carbonaceous meteorites contain materials of sim-ilar structure of nonbiological origin. Kerogens have beenused to model the spectra of some asteroids. All compo-nents in the model of Orcus had a grain size of 10 µm. Forreference, the Sun has V–J = 1.08. The chapters of de Berghet al. and Barucci et al. in this book give a more completeoverview on spectral modeling and links between colorproperties and composition.

6. ORIGIN OF THE COLOR ANISOTROPYAND PROPOSED RESURFACING SCENARIOS

6.1. A Primordial Origin

A dynamical simulation (Gomes, 2003; see also chapterby Morbidelli et al.) and some thoughts on methane chemis-try in the outer solar system provide a way of interpretingthe colors of TNOs. The dynamical simulation predicts thatas Neptune migrated outward, it scattered objects originally25 AU from the Sun into the orbits of the present-day SDOs,high-i classical TNOs (i > 5°), and high-i Plutinos. In con-trast, classical TNOs in low-e and low-i orbits (the red clus-

ter of classical TNOs discussed in section 4) remained farenough away from Neptune that they were never perturbedmuch by the planet. Perhaps around 40 AU from the Sun,methane went from condensing in a water-ice rich clathrateto condensing as pure methane (Lewis, 1972). Whereas theloss of methane from a clathrate surface would result in alag made up of colorless water-ice crust, a pure methane-icecrust would provide much material for alteration into redorganic compounds, even if there were a substantial amountof methane sublimation. If the dynamical simulation andthis idea about methane surface chemistry are correct, SDOs,high-i classical TNOs, and high-i Plutinos should exhibitgray surface colors and low-i classical TNOs should exhibitred surface colors. The SDOs are largely gray and the low-iclassical TNOs are red; however, additional observations arenecessary to see if the high-i classical TNOs and the high-iPlutinos are largely gray.

6.2. Evolutionary Processes

The red colors of TNOs and Centaurs are usually attrib-uted to the effects of surface aging and darkening due tohigh-energy radiation and particle bombardment in inter-planetary space, also called space weathering (see chaptersby Hudson et al. and de Bergh et al.). Blue surface colors canbe produced by major collisions with other objects throughdeposits of fresh icy material from the body interior or fromthe impactor. Smaller impacts could also refresh the sur-face through so-called impact gardening. Both resurfacingprocesses (irradiations and collisions) have very long time-scales (on the order of millions of years). A complicatingsituation may result from a reduction of the material red-dening for very intense and/or very long irradiation times.This is indicated by laboratory experiments performed onasphaltite material (Moroz et al., 2003). Resurfacing on amuch shorter timescale could happen due to ice reconden-sation and/or dust deposition from a temporary atmosphereproduced by outgassing due to solar heating, and from dustcoma activity. N2 and CO ices may be able to sublimate atdistances of 40 AU and beyond (Delsemme, 1982). This icesublimation process works quite efficiently for Pluto, as wellas possibly also for Charon (Yelle and Elliot, 1997) and Chi-ron (Meech et al., 1997).

The first numerical simulation results of TNO colorswere performed using simplified reddening and impact re-surfacing models (Luu and Jewitt, 1996). The results showthat the range of colors observed in TNOs can be well re-produced. Typically, red objects are exposed to high-energyradiation for a long time (on the order of 106 yr) withoutresurfacing by collision. In turn, resurfacing by collisionevents produces “sharp” short-term color changes to neu-tral or at least less red values in the objects. The modeling,and more recent work by Delsanti et al. (2004), did notconstrain conclusively the importance of collisions in theEdgeworth-Kuiper belt. The resurfacing by ice depositsfrom outgassing and from high-level irradiations is viewed


as an additional “randomizing” complication of the mod-eling. Size- and population-dependent color modeling hasnot yet been performed.

7. CONCLUSION

Broadband photometry represents the simplest observ-ing technique to study physical properties of TNOs andCentaurs. By assuming canonical albedo values togetherwith magnitude estimates in the visible, one can get aninitial idea on the typical sizes of these primitive bodies inthe solar system. Color data and results derived from spec-tral gradient estimations provide an accurate measure of theglobal surface reflectance of the objects. There is no doubtthat a large number of TNOs and Centaurs have very redsurface colors, in fact much redder than other solar systembodies and in particular those in the inner solar system.Nevertheless, objects with neutral colors are also found.

With the large and high-quality color datasets available,strong and significant results have been found. Statisticalanalyses point to correlations between optical colors andorbital inclination and orbital rms velocity for the classicalEdgeworth-Kuiper belt. On the other hand, no clear trend isobvious for Plutinos, scattered objects, or Centaurs, and notrend can be drawn regarding correlation of colors with sizeor heliocentric distance. These strong results can be summa-rized as follows: (1) The classical low-inclination TNOs areredder than the other populations; (2) the colors in the visi-ble appear to be consistent throughout the visible region, butare generally unrelated to the colors in the near-IR; (3) theTNOs show strong color diversity when compared to othersolar system bodies; and (4) there are color-orbital inclina-tion and color-rms velocity correlations for the classicalTNOs (40 < a < 50 AU).

At present, no fully convincing mechanism exists thatexplains the anisotropic color distribution within the Edge-worth-Kuiper disk. We do not know whether the color di-versity is the result of true compositional diversity orwhether it is the result of some evolutionary processes, e.g.,collisions or surface irradiation processes. On the otherhand, with the computational models performed so far cou-pled with the observational facts, we can conclude that colli-sion alone cannot explain all, but it certainly plays a role incolor distribution seen at present time in the TNOs. Not onlycollisions, but other evolutionary processes as well (e.g.,outgassing, complex space weathering, micrometeorites,surface gardening, atmospheric interaction, etc.), have to bemodeled. More observational data, numerical simulations,and overall laboratory experiments are required to unveilthe origin of the color properties and trends in the presentEdgeworth-Kuiper belt.

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Color Properties and Trends of the Transneptunian Objects · 2008-01-23 · outer solar system. Multicolor broadband photometry is the only tool at the moment that al-lows characterization