Context. Many databases on asteroid brightnesses (e.g. ALCDEF, WISE) are potential sources for extensive asteroid shape and spin modelling. Individual lightcurve inversion models require several apparitions and hundreds of data points per target. However, we can analyse the coarse shape and spin distributions over populations of at least thousands of targets even if there are only a few points and one apparition per asteroid. This is done by examining the distribution of the brightness variations observed within the chosen population. Aims. Brightness variation has been proposed as a population-scale rather than individual-target observable in two studies so far. We aim to examine this approach rigorously to establish its theoretical validity, degree of ill-posedness, and practical applicability. Methods. We model the observed brightness variation of a target population by considering its cumulative distribution function (CDF) caused by the joint distribution function of two fundamental shape and spin indicators. These are the shape elongation and the spin latitude of a simple ellipsoidal model. The main advantage of the model is that we can derive analytical basis functions that yield the observed CDF as a function of the shape and spin distribution. The inverse problem can be treated linearly. Even though the inaccuracy of the model is considerable, databases of thousands of targets should yield some information on the distribution. We employ numerical simulations to establish this and analyse photometric databases that provide sufficiently large numbers of data points for reliable brightness variation estimates. Results. We establish the theoretical soundness and the typical accuracy limits of the approach both analytically and numerically. We propose a robust brightness variation observable η based on at least five brightness points per target. We also discuss the weaker reliability and information content of the case of only two points per object. Using simulations, we derive a practical estimate of the model distribution in the (shape, spin)-plane. We show that databases such as Wide-field Infrared Survey Explorer (WISE) yield coarse but robust estimates of this distribution, and as an example compare various asteroid families with each other.
Context. A lot of photometric data is produced by surveys such as Pan-STARRS, LONEOS, WISE or Catalina. These data are a rich source of information about the physical properties of asteroids. There are several possible approaches for utilizing these data. Lightcurve inversion is a typical method that works with individual asteroids. Our approach in this paper is statistical when we focused on large groups of asteroids like dynamical families and taxonomic classes, and the data were not sufficient for individual models. Aims. Our aim was to study the distributions of shape elongation b/a and the spin axis latitude β for various subpopulations of asteroids and to compare our results, based on Pan-STARRS1 survey, with statistics previously done using different photometric data (Lowell database, WISE data). Methods. We use the LEADER algorithm to compare the b/a and β distributions for different subpopulations of asteroids. The algorithm creates a cumulative distributive function (CDF) of observed brightness variations, and computes the b/a and β distributions using analytical basis functions that yield the observed CDF. A variant of LEADER is used to solve the joint distributions for synthetic populations to test the validity of the method. Results. When comparing distributions of shape elongation for groups of asteroids with different diameters D, we found that there are no differences for D < 25 km. We also constructed distributions for asteroids with different rotation periods and revealed that the fastest rotators with P = 0 − 4 h are more spheroidal than the population with P = 4 − 8 h.
We present a concise analytical formulation of the YORP effect, with exact formulae for torques on convex bodies and motionaveraged components applicable to any shapes. We analyze the main features of the secular torques for zero and nonzero thermal inertia that are function series dependent on only a few coefficients. Using these, we investigate the stability of the YORP effect against shape perturbations with analytical and numerical estimates. We define a quantity describing the YORP capacity of any shape, and estimate YORP stability with it.
Context. Many asteroid databases with lightcurve brightness measurements (e.g. WISE, Pan-STARRS1) contain enormous amounts of data for asteroid shape and spin modelling. While lightcurve inversion is not plausible for individual targets with scarce data, it is possible for large populations with thousands of asteroids, where the distributions of the shape and spin characteristics of the populations are obtainable. Aims. We aim to introduce a software implementation of a method that computes the joint shape elongation p and spin latitude β distributions for a population, with the brightness observations given in an asteroid database. Other main goals are to include a method for performing validity checks of the algorithm, and a tool for a statistical comparison of populations. Methods. The LEADER software package read the brightness measurement data for a user-defined subpopulation from a given database. The observations were used to compute estimates of the brightness variations of the population members. A cumulative distribution function (CDF) was constructed of these estimates. A superposition of known analytical basis functions yielded this CDF as a function of the (shape, spin) distribution. The joint distribution can be reconstructed by solving a linear constrained inverse problem. To test the validity of the method, the algorithm can be run with synthetic asteroid models, where the shape and spin characteristics are known, and by using the geometries taken from the examined database. Results. LEADER is a fast and robust software package for solving shape and spin distributions for large populations. There are major differences in the quality and coverage of measurements depending on the database used, so synthetic simulations are always necessary before a database can be reliably used. We show examples of differences in the results when switching to another database.
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