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تسجيل مستخدم جديدAsteroid models reconstructed from the Lowell Photometric Database and WISE data
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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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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 spa
ce 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.
Rotation properties (spin-axis direction and rotation period) and coarse shape models of asteroids can be reconstructed from their disk-integrated brightness when measured from various viewing geometries. These physical properties are essential for c
reating a global picture of structure and dynamical evolution of the main belt. The number of shape and spin models can be increased not only when new data are available, but also by combining independent data sets and inverting them together. Our aim was to derive new asteroid models by processing readily available photometry. We used asteroid photometry compiled in the Lowell Observatory photometry database with photometry from the Gaia Data Release 2. Both data sources are available for about 5400 asteroids. In the framework of the Asteroids@home distributed computing project, we applied the light curve inversion method to each asteroid to find its convex shape model and spin state that fits the observed photometry. Due to the limited number of Gaia DR2 data points and poor photometric accuracy of Lowell data, we were able to derive unique models for only ~1100 asteroids. Nevertheless, 762 of these are new models that significantly enlarge the current database of about 1600 asteroid models. Our results demonstrate the importance of a combined approach to inversion of asteroid photometry. While our models in general agree with those obtained by separate inversion of Lowell and Gaia data, the combined inversion is more robust, model parameters are more constrained, and unique models can be reconstructed in many cases when individual data sets alone are not sufficient.
The Asteroid Terrestrial-impact Last Alert System (ATLAS) is an all-sky survey primarily aimed at detecting potentially hazardous near-Earth asteroids. Apart from the astrometry of asteroids, it also produces their photometric measurements that conta
in information about asteroid rotation and their shape. To increase the current number of asteroids with a known shape and spin state, we reconstructed asteroid models from ATLAS photometry that was available for approximately 180,000 asteroids observed between 2015 and 2018. We made use of the light-curve inversion method implemented in the Asteroid@home project to process ATLAS photometry for roughly 100,000 asteroids with more than a hundred individual brightness measurements. By scanning the period and pole parameter space, we selected those best-fit models that were, according to our setup, a unique solution for the inverse problem. We derived ~2750 unique models, 950 of them were already reconstructed from other data and published. The remaining 1800 models are new. About half of them are only partial models, with an unconstrained pole ecliptic longitude. Together with the shape and spin, we also determined for each modeled asteroid its color index from the cyan and orange filter used by the ATLAS survey. We also show the correlations between the color index, albedo, and slope of the phase-angle function. The current analysis is the first inversion of ATLAS asteroid photometry, and it is the first step in exploiting the huge scientific potential that ATLAS photometry has. ATLAS continues to observe, and in the future, this data, together with other independent photometric measurements, can be inverted to produce more refined asteroid models.
Aims. To derive the thermal inertia of 2008 EV$_5$, the baseline target for the Marco Polo-R mission proposal, and infer information about the size of the particles on its surface. Methods. Values of thermal inertia are obtained by fitting an asteroi
d thermophysical model to NASAs Wide-field Infrared Survey Explorer (WISE) infrared data. From the constrained thermal inertia and a model of heat conductivity that accounts for different values of the packing fraction (a measure of the degree of compaction of the regolith particles), grain size is derived. Results. We obtain an effective diameter $D = 370 pm 6,mathrm{m}$, geometric visible albedo $p_V = 0.13 pm 0.05$ (assuming $H=20.0 pm 0.4$), and thermal inertia $Gamma = 450 pm 60$ J/m2/s(1/2)/K at the 1-$sigma$ level of significance for its retrograde spin pole solution. The regolith particles radius is $r = 6.6^{+1.3}_{-1.3}$ mm for low degrees of compaction, and $r = 12.5^{+2.7}_{-2.6}$ mm for the highest packing densities.
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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