Compositional Surface Diversity in the Trans-Neptunian Objects

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  • THE ASTRONOMICAL JOURNAL, 120 :496500, 2000 July2000. The American Astronomical Society. All rights reserved. Printed in U.S.A.(


    Observatoire de Paris, Section de Meudon, 5, Place Jules Janssen, Meudon Cedex, F- 92195, France ;


    D. J. THOLENInstitute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, Hawaii 96822

    Received 2000 January 4 ; accepted 2000 March 15

    ABSTRACTThe knowledge of the physical and chemical properties of trans-Neptunian objects (TNOs) is still

    incomplete and confused. To investigate their physical properties, we are continuing the TNO obser-vational program started in 1997 at ESO in La Silla, Chile with the 3.5 m New Technology Telescope.In February 1999, broadband optical colors were obtained for eight new objects : 1993 FW, 1995 HM5,1997 1997 1997 1997 1998 and 1998 Particular attention hasCQ29, CS29, CT29, CU29, FS144, WH24.been paid to the observations and data reduction of these faint objects. These new data increase theavailable statistical sample and will help us to understand the surface properties and the mechanisms ofthe surface modication of the TNOs. The observed objects present a wide spread of colors. The colordistribution does not show any bimodality. Knowledge of the colors of a large number of these objects isimportant to understand this population, which represents an important reservoir of primordial material.Key words : Kuiper belt, Oort cloud techniques : photometric


    Since the discovery in 1992 (Luu & Jewitt 1993), theknown population of trans-Neptunian objects (TNOs) hasgrown rapidly. More than 2300 TNOs have already beendetected,2 and on the basis of the sky surveys done, Jewitt(2000) hypothesized that there are more than 100,000 TNOswith diameter larger than 100 km in the radial zone extend-ing outward from Neptune between 30 and 50 AU. It is veryimportant to understand their physical characteristics aswell as their dynamical behavior. They are believed to bethe source of short-period comets (Levison & Duncan1997), but, more important still, the knowledge of this newpopulation is related to the study of the solar system forma-tion and evolution. Located so far from the Sun comparedwith the planets and some other small bodies, the TNOshave probably not been thermally processed since their for-mation. They are expected to be well-preserved fossils of theprotoplanetary disk, as they were stored at very low tem-perature and they are believed to be the remnants of solarsystem formation. Exploration of the TNOs is still at thenascent stage, but the knowledge of their physical proper-ties could constrain the formation and evolution models ofour own solar system and other planetary systems.

    Very little is known about the physical and chemicalcharacteristics of the TNOs, and the study of their composi-tion is very difficult. Because of their faintness, spectro-scopic techniques can be applied to only a very few objects.Near-infrared spectra with low signal-to-noise ratios (S/Ns)have been obtained at the Keck observatory for only threeTNOs. The spectrum of 1993 SC was obtained by Brown etal. (1997) for the range 1.42.4 km. Although this spectrumhas been heavily smoothed, it shows absorption features atwavelengths near those of Pluto or Triton, suggesting the

    1 Based on observations carried out at the European Southern Obser-

    vatory, La Silla, Chile (ESO program 62.S-0305).2 See http ://

    presence of hydrocarbon ices. Luu and Jewitt (1998)obtained a spectrum of 1996 for the range 1.02.5 km.TL66It is almost at and very similar to that of Centaur Chiron.In 1999, Brown, Cruikshank, & Pendleton (1999) observed1996 and the spectrum shows strong absorption nearTO66,1.5 and 2.0 km, characteristic of water ice.

    Though a few objects are brighter than 22nd magnitude,the typical apparent magnitude of TNOs is more than 23,so they cannot be observed by spectroscopy. The photo-metric technique is the only way now available to study alarge sample of these objects. Visual photometric obser-vations of TNOs have been carried out by Luu & Jewitt(1996), Green et al. (1997), Tegler & Romanishin (1998), andBarucci et al. (1999). In some cases the reported results seemdiscrepant and the color dierences exceed the quotederrors by a considerable margin. To enlarge the availablesample and to obtain homogeneous data of high quality, weare continuing spectrophotometric observations of TNOs.In this paper we present the observations for eight newobjects, and we carefully explain the method used for thereduction.


    Observations of eight new TNOs have been carried outon 1999 February 1417 at ESO (European SouthernObservatory, La Silla, Chile). The observational character-istics are reported in Table 1. The SUSI2 CCD camera

    at the f/11 Nasmyth focus of the 3.5 m New(5@.5] 5@.5)Technology Telescope (NTT) was used to obtain directimages. The EEV camera (ESO No. 46) has been selectedfor our observations with the Bessel B, V , R, and I lters.The observations were carried out in 2 ] 2 binning mode,yielding a pixel scale of The seeing throughout the run0A.16.was in the range Because of the faintness of these0A.51A.9.objects, careful observations and reductions are necessaryto minimize potential systematic errors due to faintbackground-source contamination. We sequence the obser-vations by repeating measurements through the V lter



    TABLE 1


    Date R.A. Decl. r * PhaseObject (UT) (2000.0) (2000.0) (AU) (AU) (deg)

    1993 FW . . . . . . . . 1999 Feb 16 13 01 35 [05 28 05 41.97 41.32 1.031993 FW . . . . . . . . 1999 Feb 17 13 01 32 [05 27 48 41.97 41.31 1.011995 HM5 . . . . . . . 1999 Feb 14 12 58 34 [05 32 56 32.09 31.45 1.321995 HM5 . . . . . . . 1999 Feb 17 12 58 24 [05 31 48 32.09 31.41 1.311997 CQ29 . . . . . . 1999 Feb 16 10 41 30 ]09 39 33 41.30 40.33 0.281997 CQ29 . . . . . . 1999 Feb 17 10 41 26 ]09 40 01 41.30 40.33 0.251997 CS29 . . . . . . . 1999 Feb 14 07 52 11 ]21 15 09 43.61 42.74 0.621997 CS29 . . . . . . . 1999 Feb 15 07 52 07 ]21 15 20 43.61 42.75 0.641997 CT29 . . . . . . . 1999 Feb 15 09 13 52 ]16 59 32 44.85 43.88 0.221997 CT29 . . . . . . . 1999 Feb 16 09 13 47 ]16 59 51 44.85 43.88 0.241997 CU29 . . . . . . 1999 Feb 16 07 45 20 ]22 28 24 44.75 43.92 0.681997 CU29 . . . . . . 1999 Feb 17 07 45 17 ]22 28 33 44.75 43.93 0.701998 FS144 . . . . . . 1999 Feb 14 11 06 21 [03 47 12 41.86 40.96 0.591998 FS144 . . . . . . 1999 Feb 15 11 06 17 [03 46 50 41.86 40.96 0.571998 WH24 . . . . . . 1999 Feb 15 03 31 25 ]20 34 54 42.79 42.78 1.321998 WH24 . . . . . . 1999 Feb 17 03 31 27 ]20 35 01 42.79 42.82 1.32

    NOTE.Units of right ascension are hours, minutes, and seconds, and units of declination aredegrees, arcminutes, and arcseconds.

    (e.g., V , B, V , R, V , I, V ). Making multiple observationsthrough the same lter allows us to interpolate or toaverage through this lter to minimize the errors in thecolor index caused by the variation in brightness with rota-tion.

    The exposure time ranged between 300 and 900 s for theV , R, and I lters and 600 and 1350 for the B lter. Weavoid longer exposure times, not only because of potentialbrightness variation, but also because of the increasedpossibility of data loss due to cosmic-ray hits on the imageof the object. We repeated the observations by making asecond independent measurement for all the objects. Stan-dard stars in multiple elds (Landolt 1992) have beenobserved each night at dierent air masses to determine theextinction coefficients and to perform a complete photo-metric transformation. The nights were photometric exceptpart of the second night, during which isolated cirri werepresent near the horizon.


    Photometric reduction was performed using specic rou-tines developed with MIDAS. First, bias and at-eld cor-rections were performed. Because of the faintness of theseobjects, a very accurate data reduction method wasrequired. Automatic methods cannot be used in this case.Several observations performed on the same objects by dif-ferent authors give dierent results (Green & McBride2000). To determine the best way to reduce TNO photo-metric data, we studied the error sources in magnitude. Wetook into account the main error sources : (a) the sky back-ground photon noise, (b) the error in the sky backgroundestimator, (c) the object photon noise, and (d) the readoutnoise.

    The classical data reduction method consists of using abig aperture, one large enough to include the majority of theux of the object, as well as a signicant contribution fromthe sky background. For objects as faint as TNOs (i.e.,

    the error from the sky background dominates if weV Z 22),use the classical method. For this reason a small aperture isneeded to reduce the sky background contribution and the

    probability of contamination by a background source. If wechoose a small aperture to perform photometric datareduction, a signicant loss of object ux accompanies thereduction in sky background. To calibrate this eect, weneed to perform an aperture correction. This method con-sists of measuring a bright star3 in the same frame(V [ 19)as the object, both with the small aperture and with a bigone. The comparison of both measurements allows us todetermine the correction to apply (Howell 1989). To esti-mate the error on the correcting value, several bright starsin the frame have been used. For each one, we construct agraph showing the sky-subtracted ux of the source versusaperture size (growth curves). To subtract the sky back-ground, we select six subframes (50] 50 pixels) around theobject. For each one, we compute the mode of the intensitydistribution. The mode corresponds to the most probablevalue of a distribution :

    mode\ 3(median)[ 2(mean)(Stetson 1987 ; Da Costa 1992). Using these six sky back-ground estimators, we compute an average value and therms standard deviation. If the chosen sources are brightenough, the sky background estimate is not critical. Thegrowth curves converge on a value normalized to 1 for largeaperture sizes. We determine growth curves for severalbright stars, then we calculate an average growth curve,which will be used to determine the correcting value foreach aperture size. The shape of the curve depends only onthe seeing prole in the frame. As this prole changes fromone frame to another, such a curve must be produced foreach frame. The average growth curve also provides theerror on the correcting value, which has to be included inthe total error computation.

    The next step consists in choosing the aperture size. Thesignal-to-noise ratio depends on the chosen aperture sizeand the seeing-prole FWHM (through the truncated ux

    3 This upper limit depends on many parameters, such as exposure time

    and sky brightness.

  • 19 20 21 22 23 24 25Magnitude of the source













    Classical method (D=4")Aperture correction (D=1")

    498 BARUCCI ET AL. Vol. 120

    FIG. 1.Theoretical error in magnitude vs. the magnitude of thesource. The parameters used to calculate these analytical curves are thefollowing : exposure time, 300 s ; collecting area, 10 m2 ; spectral bandwidth, 0.09 k ; sky magnitude, 21.8 mag arcsec~2 ; and error on the skybackground estimator, 10 photons pixel~2. It is evident that the aperturecorrection method is better for faint objects. For bright objects, a smallererror is obtained with the classical method.

    contained in an aperture of diameter D). It can be demon-strated that the signal-to-noise ratio is maximized when theaperture size is equal to the seeing-prole FWHM (Romon1999). In general, we use an aperture a few pixels biggerthan the seeing to avoid edge eect.

    If the aperture correction method is used, the total errorin the magnitude includes (a) the error on the correctingvalue, (b) the errors relative to the sky background, (c) theobject photon noise, and (4) the readout noise. If the clas-sical method is used, only the three last error sourcesremain. To compare the error obtained using the classicalmethod and that obtained using the aperture-correctionmethod, the total error is computed analytically. In Figure 1the error (in magnitude) versus the magnitude of the sourcefor each method is shown. The best method, giving thesmallest error, depends on the magnitude of the source : forbright objects, the classical method should be used, whilefaint ones require aperture correction. The analytical com-putation does not allow us to give an accurate limit. Tochoose between one method or the other, growth curves areused. If the average curve converges, the classical methodcan be applied ; otherwise, aperture correction must be used.This method has been applied and validated using synthetic

    objects to test dierent reduction techniques on faintTNOs.4

    The aperture correction method has been used for all theobjects studied here. The aperture size depends on theseeing. Therefore, it could vary from one frame to another.The aperture size used varies from to Because this0A.6 1A.9.method cannot be applied to trailed objects, we checkedthat the proper motion of each object is smaller than theseeing.

    Photometric calibration was performed using the usualcalibration method. We checked the stability of severalcomparison stars for each night, and we used six standardstars, observed at dierent air masses, to compute the atmo-spheric extinction coefficients. We computed the extinctioncoefficient, the color term, and the zero point by using alinear regression method. The errors on these coefficientshave been included in the total error in the magnitude.

    4. RESULTS

    The optical photometry is presented in Table 2. Thereported magnitudes represent the weighted average of dif-ferent measurements, and the error listed is its standarddeviation. In a few cases we were not able to measure themagnitudes, especially in the B and I lters. The B magni-tude was particularly difficult to measure as it is very faintfor most of the objects and the SUSI2 CCD camera sensi-tivity is poor in the B lter. Through the I lter, strongfringes were observed in the images. They are due to theinterference of night-sky lines in the thin CCD. ESO NTTsta provided an efficient method to remove these fringes,5but the high noise level that remained after correction madeit difficult to measure the I magnitude of the faintest objects.We also found that the seeing is a critical parameter : verygood seeing is needed to measure the faintest objects. Themissing measurements in B and I lters for some objects aredue to their faintness as well as poor seeing.

    The resulting color indexes are reported in Table 3 andthe relative spectra, normalized to 1 at the V lter, areshown in Figure 2. The reectivity was computed using thesolar colors (Hardorp 1980 ; Hartmann, Cruikshank, &Degewij 1982). Th...


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