The triaxial ellipsoid dimensions, rotational pole, and bulk density of ESA Rosetta target asteroid (21) Lutetia

We seek the best size estimates of the asteroid (21) Lutetia, the direction of its spin axis, and its bulk density, assuming its shape is well described by a smooth featureless triaxial ellipsoid, and to evaluate the deviations from this assumption. Methods. We derive these quantities from the outlines of the asteroid in 307 images of its resolved apparent disk obtained with adaptive optics (AO) at Keck II and VLT, and combine these with recent mass determinations to estimate a bulk density. Our best triaxial ellipsoid diameters for Lutetia, based on our AO images alone, are a x b x c = 132 x 101 x 93 km, with uncertainties of 4 x 3 x 13 km including estimated systematics, with a rotational pole within 5 deg. of ECJ2000 [long,lat] = [45, -7], or EQJ2000 [RA, DEC] = [44, +9]. The AO model fit itself has internal precisions of 1 x 1 x 8 km, but it is evident, both from this model derived from limited viewing aspects and the radius vector model given in a companion paper, that Lutetia has significant departures from an idealized ellipsoid. In particular, the long axis may be overestimated from the AO images alone by about 10 km. Therefore, we combine the best aspects of the radius vector and ellipsoid model into a hybrid ellipsoid model, as our final result, of 124 +/- 5 x 101 +/- 4 x 93 +/- 13 km that can be used to estimate volumes, sizes, and projected areas. The adopted pole position is within 5 deg. of [long, lat] = [52, -6] or[RA DEC] = [52, +12]. Using two separately determined masses and the volume of our hybrid model, we estimate a density of 3.5 +/- 1.1 or 4.3 +/- 0.8 g cm-3 . From the density evidence alone, we argue that this favors an enstatite-chondrite composition, although other compositions are formally allowed at the extremes (low-porosity CV/CO carbonaceous chondrite or high-porosity metallic). We discuss this in the context of other evidence.Comment: 9 pages, 8 figures, 5 tables, submitted to Astronomy and Astrophysic

The Resolved Asteroid Program - Size, shape, and pole of (52) Europa

With the adaptive optics (AO) system on the 10 m Keck-II telescope, we acquired a high quality set of 84 images at 14 epochs of asteroid (52) Europa on 2005 January 20. The epochs covered its rotation period and, by following its changing shape and orientation on the plane of sky, we obtained its triaxial ellipsoid dimensions and spin pole location. An independent determination from images at three epochs obtained in 2007 is in good agreement with these results. By combining these two data sets, along with a single epoch data set obtained in 2003, we have derived a global fit for (52) Europa of diameters (379x330x249) +/- (16x8x10) km, yielding a volume-equivalent spherical-diameter of 315 +/- 7 km, and a rotational pole within 7 deg of [RA; Dec] = [257,+12] in an Equatorial J2000 reference frame (ECJ2000: 255,+35). Using the average of all mass determinations available forEuropa, we derive a density of 1.5 +/- 0.4, typical of C-type asteroids. Comparing our images with the shape model of Michalowski et al. (A&A 416, 2004), derived from optical lightcurves, illustrates excellent agreement, although several edge features visible in the images are not rendered by the model. We therefore derived a complete 3-D description of Europa's shape using the KOALA algorithm by combining our imaging epochs with 4 stellar occultations and 49 lightcurves. We use this 3-D shape model to assess these departures from ellipsoidal shape. Flat facets (possible giant craters) appear to be less distinct on (52) Europa than on other C-types that have been imaged in detail. We show that fewer giant craters, or smaller craters, is consistent with its expected impact history. Overall, asteroid (52) Europa is still well modeled as a smooth triaxial ellipsoid with dimensions constrained by observations obtained over several apparitions.Comment: Accepted for publication in Icaru

Physical properties of ESA Rosetta target asteroid (21) Lutetia: Shape and flyby geometry

Aims. We determine the physical properties (spin state and shape) of asteroid (21) Lutetia, target of the ESA Rosetta mission, to help in preparing for observations during the flyby on 2010 July 10 by predicting the orientation of Lutetia as seen from Rosetta. Methods. We use our novel KOALA inversion algorithm to determine the physical properties of asteroids from a combination of optical lightcurves, disk-resolved images, and stellar occultations, although the latter are not available for (21) Lutetia. Results. We find the spin axis of (21) Lutetia to lie within 5 degrees of ({\lambda} = 52 deg., {\beta} = -6 deg.) in Ecliptic J2000 reference frame (equatorial {\alpha} = 52 deg., {\delta} = +12 deg.), and determine an improved sidereal period of 8.168 270 \pm 0.000 001 h. This pole solution implies the southern hemisphere of Lutetia will be in "seasonal" shadow at the time of the flyby. The apparent cross-section of Lutetia is triangular as seen "pole-on" and more rectangular as seen "equator-on". The best-fit model suggests the presence of several concavities. The largest of these is close to the north pole and may be associated with large impacts.Comment: 17 pages, 5 figures, 3 tables, submitted to Astronomy and Astrophysic

Near-Infrared Mapping and Physical Properties of the Dwarf-Planet Ceres

We study the physical characteristics (shape, dimensions, spin axis direction, albedo maps, mineralogy) of the dwarf-planet Ceres based on high-angular resolution near-infrared observations. We analyze adaptive optics J/H/K imaging observations of Ceres performed at Keck II Observatory in September 2002 with an equivalent spatial resolution of ~50 km. The spectral behavior of the main geological features present on Ceres is compared with laboratory samples. Ceres' shape can be described by an oblate spheroid (a = b = 479.7 +/- 2.3 km, c = 444.4 +/- 2.1 km) with EQJ2000.0 spin vector coordinates RA = 288 +/- 5 deg. and DEC = +66 +/- 5 deg. Ceres sidereal period is measured to be 9.0741 +/- 0.0001 h. We image surface features with diameters in the 50-180 km range and an albedo contrast of ~6% with respect to the average Ceres albedo. The spectral behavior of the brightest regions on Ceres is consistent with phyllosilicates and carbonate compounds. Darker isolated regions could be related to the presence of frost.Comment: 11 pages, 8 Postscript figures, Accepted for publication in A&

Shape modeling technique KOALA validated by ESA Rosetta at (21) Lutetia

We present a comparison of our results from ground-based observations of asteroid (21) Lutetia with imaging data acquired during the flyby of the asteroid by the ESA Rosetta mission. This flyby provided a unique opportunity to evaluate and calibrate our method of determination of size, 3-D shape, and spin of an asteroid from ground-based observations. We present our 3-D shape-modeling technique KOALA which is based on multi-dataset inversion. We compare the results we obtained with KOALA, prior to the flyby, on asteroid (21) Lutetia with the high-spatial resolution images of the asteroid taken with the OSIRIS camera on-board the ESA Rosetta spacecraft, during its encounter with Lutetia. The spin axis determined with KOALA was found to be accurate to within two degrees, while the KOALA diameter determinations were within 2% of the Rosetta-derived values. The 3-D shape of the KOALA model is also confirmed by the spectacular visual agreement between both 3-D shape models (KOALA pre- and OSIRIS post-flyby). We found a typical deviation of only 2 km at local scales between the profiles from KOALA predictions and OSIRIS images, resulting in a volume uncertainty provided by KOALA better than 10%. Radiometric techniques for the interpretation of thermal infrared data also benefit greatly from the KOALA shape model: the absolute size and geometric albedo can be derived with high accuracy, and thermal properties, for example the thermal inertia, can be determined unambiguously. We consider this to be a validation of the KOALA method. Because space exploration will remain limited to only a few objects, KOALA stands as a powerful technique to study a much larger set of small bodies using Earth-based observations.Comment: 15 pages, 8 figures, 2 tables, accepted for publication in P&S

The astrometric Gaia-FUN-SSO observation campaign of 99 942 Apophis

Astrometric observations performed by the Gaia Follow-Up Network for Solar System Objects (Gaia-FUN-SSO) play a key role in ensuring that moving objects first detected by ESA's Gaia mission remain recoverable after their discovery. An observation campaign on the potentially hazardous asteroid (99 942) Apophis was conducted during the asteroid's latest period of visibility, from 12/21/2012 to 5/2/2013, to test the coordination and evaluate the overall performance of the Gaia-FUN-SSO . The 2732 high quality astrometric observations acquired during the Gaia-FUN-SSO campaign were reduced with the Platform for Reduction of Astronomical Images Automatically (PRAIA), using the USNO CCD Astrograph Catalogue 4 (UCAC4) as a reference. The astrometric reduction process and the precision of the newly obtained measurements are discussed. We compare the residuals of astrometric observations that we obtained using this reduction process to data sets that were individually reduced by observers and accepted by the Minor Planet Center. We obtained 2103 previously unpublished astrometric positions and provide these to the scientific community. Using these data we show that our reduction of this astrometric campaign with a reliable stellar catalog substantially improves the quality of the astrometric results. We present evidence that the new data will help to reduce the orbit uncertainty of Apophis during its close approach in 2029. We show that uncertainties due to geolocations of observing stations, as well as rounding of astrometric data can introduce an unnecessary degradation in the quality of the resulting astrometric positions. Finally, we discuss the impact of our campaign reduction on the recovery process of newly discovered asteroids.Comment: Accepted for publication in A&

Asteroids' physical models from combined dense and sparse photometry and scaling of the YORP effect by the observed obliquity distribution

The larger number of models of asteroid shapes and their rotational states derived by the lightcurve inversion give us better insight into both the nature of individual objects and the whole asteroid population. With a larger statistical sample we can study the physical properties of asteroid populations, such as main-belt asteroids or individual asteroid families, in more detail. Shape models can also be used in combination with other types of observational data (IR, adaptive optics images, stellar occultations), e.g., to determine sizes and thermal properties. We use all available photometric data of asteroids to derive their physical models by the lightcurve inversion method and compare the observed pole latitude distributions of all asteroids with known convex shape models with the simulated pole latitude distributions. We used classical dense photometric lightcurves from several sources and sparse-in-time photometry from the U.S. Naval Observatory in Flagstaff, Catalina Sky Survey, and La Palma surveys (IAU codes 689, 703, 950) in the lightcurve inversion method to determine asteroid convex models and their rotational states. We also extended a simple dynamical model for the spin evolution of asteroids used in our previous paper. We present 119 new asteroid models derived from combined dense and sparse-in-time photometry. We discuss the reliability of asteroid shape models derived only from Catalina Sky Survey data (IAU code 703) and present 20 such models. By using different values for a scaling parameter cYORP (corresponds to the magnitude of the YORP momentum) in the dynamical model for the spin evolution and by comparing synthetics and observed pole-latitude distributions, we were able to constrain the typical values of the cYORP parameter as between 0.05 and 0.6.Comment: Accepted for publication in A&A, January 15, 201

Comparison of machine learning algorithms used to classify the asteroids observed by all-sky surveys

Context. Multifilter photometry from large sky surveys is commonly used to assign asteroid taxonomic types and study various problems in planetary science. To maximize the science output of those surveys, it is important to use methods that best link the spectro-photometric measurements to asteroid taxonomy. Aims. We aim to determine which machine learning methods are the most suitable for the taxonomic classification for various sky surveys. Methods. We utilized five machine learning supervised classifiers: logistic regression, naive Bayes, support vector machines (SVMs), gradient boosting, and MultiLayer Perceptrons (MLPs). Those methods were found to reproduce the Bus-DeMeo taxonomy at various rates depending on the set of filters used by each survey. We report several evaluation metrics for a comprehensive comparison (prediction accuracy, balanced accuracy, F1 score, and the Matthews correlation coefficient) for 11 surveys and space missions. Results. Among the methods analyzed, multilayer perception and gradient boosting achieved the highest accuracy and naive Bayes achieved the lowest accuracy in taxonomic prediction across all surveys. We found that selecting the right machine learning algorithm can improve the success rate by a factor of >2. The best balanced accuracy (similar to 85% for a taxonomic type prediction) was found for the Visible and Infrared Survey telescope for Astronomy (VISTA) and the ESA Euclid mission surveys where broadband filters best map the 1 mu m and 2 mu m olivine and pyroxene absorption bands. Conclusions. To achieve the highest accuracy in the taxonomic type prediction based on multifilter photometric measurements, we recommend the use of gradient boosting and MLP optimized for each survey. This can improve the overall success rate even when compared with naive Bayes. A merger of different datasets can further boost the prediction accuracy. For the combination of the Legacy Survey of Space and Time and VISTA survey, we achieved 90% for the taxonomic type prediction.Peer reviewe