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Register a new userAsteroid taxonomic signatures from photometric phase curves
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We explore the correlation between an asteroids taxonomy and photometric phase curve using the H, G12 photometric phase function, with the shape of the phase function described by the single parameter G12. We explore the usability of G12 in taxonomic classification for individual objects, asteroid families, and dynamical groups. We conclude that the mean values of G12 for the considered taxonomic complexes are statistically different, and also discuss the overall shape of the G12 distribution for each taxonomic complex. Based on the values of G12 for about half a million asteroids, we compute the probabilities of C, S, and X complex membership for each asteroid. For an individual asteroid, these probabilities are rather evenly distributed over all of the complexes, thus preventing meaningful classification. We then present and discuss the G12 distributions for asteroid families, and predict the taxonomic complex preponderance for asteroid families given the distribution of G12 in each family. For certain asteroid families, the probabilistic prediction of taxonomic complex preponderance can clearly be made. The Nysa-Polana family shows two distinct regions in the proper element space with different G12 values dominating in each region. We conclude that the G12-based probabilistic distribution of taxonomic complexes through the main belt agrees with the general view of C complex asteroid proportion increasing towards the outer belt. We conclude that the G12 photometric parameter cannot be used in determining taxonomic complex for individual asteroids, but it can be utilized in the statistical treatment of asteroid families and different regions of the main asteroid belt.
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Asteroid phase curves are used to derive fundamental physical properties through the determination of the absolute magnitude H. The upcoming visible Legacy Survey of Space and Time (LSST) and mid-infrared Near-Earth Object Surveillance Mission (NEOSM) surveys rely on these absolute magnitudes to derive the colours and albedos of millions of asteroids. Furthermore, the shape of the phase curves reflects their surface compositions, allowing for conclusions on their taxonomy. We derive asteroid phase curves from dual-band photometry acquired by the Asteroid Terrestrial-impact Last Alert System telescopes. Using Bayesian parameter inference, we retrieve the absolute magnitudes and slope parameters of 127,012 phase curves of 94,777 asteroids in the photometric $H, G_1, G_2$- and $H, G^*_{12}$-systems. The taxonomic complexes of asteroids separate in the observed $G_1, G_2$-distributions, correlating with their mean visual albedo. This allows for differentiating the X-complex into the P-, M-, and E-complexes using the slope parameters as alternative to albedo measurements. Further, taxonomic misclassifications from spectrophotometric datasets as well as interlopers in dynamical families of asteroids reveal themselves in $G_1, G_2$-space. The $H, G^*_{12}$-model applied to the serendipitous observations is unable to resolve target taxonomy. The $G_1, G_2$ phase coefficients show wavelength-dependency for the majority of taxonomic complexes. Serendipitous asteroid observations allow for reliable phase curve determination for a large number of asteroids. To ensure that the acquired absolute magnitudes are suited for colour computations, it is imperative that future surveys densely cover the opposition effects of the phase curves, minimizing the uncertainty on H. The phase curve slope parameters offer an accessible dimension for taxonomic classification.
We present here multi-band photometry for over 2000 Main-belt asteroids. For each target we report the probabilistic taxonomy using the measured V-R and V-I colors in combination with a machine-learning generated decision surface in color-color space. Through this method we classify >85% of our targets as one the four main Bus-DeMeo complexes: S-, C-, X-, or D-type. Roughly one third of our targets have a known associated dynamic family with 69 families represented in our data. Within uncertainty our results show no discernible difference in taxonomic distribution between family members and non-family members. Nine of the 69 families represented in our observed sample had 20 or more members present and therefore we investigate the taxonomy of these families in more detail and find excellent agreement with literature. Out of these 9 well-sampled families, our data show that the Themis, Koronis, Hygiea, Massalia, and Eunomia families display a high degree of taxonomic homogeneity and that the Vesta, Flora, Nysa-Polana, and Eos families show a significant level of mixture in taxonomies. Using the taxonomic purity and the degree of dispersion in observed colors for each of the 9 well-sampled collisional families we also speculate which of these families potentially originated from a differentiated parent body and/or is a family with a possible undetermined nested family. Additionally, we obtained sufficient photometric data for 433 of our targets to extract reliable rotation periods and observe no obvious correlation between rotation properties and family membership.
We use the lightcurve inversion method to derive new shape models and spin states of asteroids from the sparse-in-time photometry compiled in the Lowell Photometric Database. To speed up the time-consuming process of scanning the period parameter space through the use of convex shape models, we use the distributed computing project Asteroids@home, running on the Berkeley Open Infrastructure for Network Computing (BOINC) platform. This way, the period-search interval is divided into hundreds of smaller intervals. These intervals are scanned separately by different volunteers and then joined together. We also use an alternative, faster, approach when searching the best-fit period by using a model of triaxial ellipsoid. By this, we can independently confirm periods found with convex models and also find rotation periods for some of those asteroids for which the convex-model approach gives too many solutions. From the analysis of Lowell photometric data of the first 100,000 numbered asteroids, we derived 328 new models. This almost doubles the number of available models. We tested the reliability of our results by comparing models that were derived from purely Lowell data with those based on dense lightcurves, and we found that the rate of false-positive solutions is very low. We also present updated plots of the distribution of spin obliquities and pole ecliptic longitudes that confirm previous findings about a non-uniform distribution of spin axes. However, the models reconstructed from noisy sparse data are heavily biased towards more elongated bodies with high lightcurve amplitudes.
We present here the c-o colors for identified Flora, Vesta, Nysa-Polana, Themis, and Koronis family members within the historic data set (2015-2018) of the Asteroid Terrestrial-impact Last Alert System (ATLAS). The Themis and Koronis families are known to be relatively pure C- and S-type Bus-DeMeo taxonomic families, respectively, and the extracted color data from the ATLAS broadband c- and o-filters of these two families is used to demonstrate that the ATLAS c-o color is a sufficient parameter to distinguish between the C- and S-type taxonomies. The Vesta and Nysa-Polana families are known to display a mixture of taxonomies possibly due to Vestas differentiated parent body origin and Nysa-Polana actually consisting of two nested families with differing taxonomies. Our data show that the Flora family also displays a large degree of taxonomic mixing and the data reveal a substantial H-magnitude dependence on color. We propose and exclude several interpretations for the observed taxonomic mix. Additionally, we extract rotation periods of all of the targets reported here and find good agreement with targets that have previously reported periods.
Information about the spin state of asteroids is important for our understanding of the dynamical processes affecting them. However, spin properties of asteroids are known for only a small fraction of the whole population. To enlarge the sample of asteroids with a known rotation state and basic shape properties, we combined sparse-in-time photometry from the Lowell Observatory Database with flux measurements from NASAs WISE satellite. We applied the light curve inversion method to the combined data. The thermal infrared data from WISE were treated as reflected light because the shapes of thermal and visual light curves are similar enough for our purposes. While sparse data cover a wide range of geometries over many years, WISE data typically cover an interval of tens of hours, which is comparable to the typical rotation period of asteroids. The search for best-fitting models was done in the framework of the Asteroids@home distributed computing project. By processing the data for almost 75,000 asteroids, we derived unique shape models for about 900 of them. Some of them were already available in the DAMIT database and served us as a consistency check of our approach. In total, we derived new models for 662 asteroids, which significantly increased the total number of asteroids for which their rotation state and shape are known. For another 789 asteroids, we were able to determine their sidereal rotation period and estimate the ecliptic latitude of the spin axis direction. We studied the distribution of spins in the asteroid population. We revealed a significant discrepancy between the number of prograde and retrograde rotators for asteroids smaller than about 10 km. Combining optical photometry with thermal infrared light curves is an efficient approach to obtaining new physical models of asteroids.
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