Asteroid models from the Lowell photometric database

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.

[1]  P. Tanga,et al.  Testing the inversion of asteroids’ Gaia photometry combined with ground-based observations , 2015, 1504.02809.

[2]  Mikko Kaasalainen,et al.  Inverse problems of generalized projection operators , 2006 .

[3]  A. La Spina,et al.  Retrograde spins of near-Earth asteroids from the Yarkovsky effect , 2004, Nature.

[4]  J. vDurech,et al.  Sizes of main-belt asteroids by combining shape models and Keck adaptive optics observations , 2013, 1308.0446.

[5]  E. Ofek,et al.  ASTEROID LIGHT CURVES FROM THE PALOMAR TRANSIENT FACTORY SURVEY: ROTATION PERIODS AND PHASE FUNCTIONS FROM SPARSE PHOTOMETRY , 2015, 1504.04041.

[6]  A. Vagnozzi,et al.  Asteroids’ physical models from combined dense and sparse photometry and scaling of the YORP effect by the observed obliquity distribution , 2013 .

[7]  A study of asteroid pole-latitude distribution based on an extended set of shape models derived by the lightcurve inversion method , 2011 .

[8]  Robert Connelly,et al.  Convex profiles from asteroid lightcurves , 1983 .

[9]  K. Muinonen Electromagnetic and light scattering by nonspherical particles XII , 2011 .

[10]  Larry Denneau,et al.  Asteroid Models from the Pan-STARRS Photometry , 2006 .

[11]  D. A. Oszkiewicz,et al.  Asteroid spin‐axis longitudes from the Lowell Observatory database , 2011, 1310.3617.

[12]  Josef Hanus,et al.  Asteroids@home - A BOINC distributed computing project for asteroid shape reconstruction , 2015, Astron. Comput..

[13]  Karri Muinonen,et al.  Optimization Methods for Asteroid Lightcurve Inversion. II. The Complete Inverse Problem , 2001 .

[14]  A. Vagnozzi,et al.  New and updated convex shape models of asteroids based on optical data from a large collaboration network , 2015, 1510.07422.

[15]  M. Kaasalainen,et al.  Optimization Methods for Asteroid Lightcurve Inversion: I. Shape Determination , 2001 .

[16]  Mikko Kaasalainen,et al.  Physical models of large number of asteroids from calibrated photometry sparse in time , 2004 .

[17]  Brian Warner,et al.  Asteroid models from combined sparse and dense photometric data , 2009 .

[18]  Petr Pravec,et al.  The asteroid lightcurve database , 2009 .

[19]  A. Johansen,et al.  Prograde rotation of protoplanets by accretion of pebbles in a gaseous environment , 2009, 0910.1524.

[20]  A. Harris,et al.  PHOTOMETRIC OBSERVATIONS OF 125 ASTEROIDS , 1997 .

[21]  Mikko Kaasalainen,et al.  Shapes and rotational properties of thirty asteroids from photometric data , 2003 .

[22]  David E. Trilling,et al.  Online multi-parameter phase-curve fitting and application to a large corpus of asteroid photometric data , 2011 .

[23]  P. Tanga,et al.  Genetic inversion of sparse disk-integrated photometric data of asteroids: application to Hipparcos data , 2009 .

[24]  Mikko Kaasalainen,et al.  DAMIT: a database of asteroid models , 2010 .

[25]  S. Urakawa,et al.  Against the biases in spins and shapes of asteroids , 2015, 1711.02429.

[26]  R. Koff,et al.  An anisotropic distribution of spin vectors in asteroid families , 2013, 1309.4296.

[27]  Martin G. Cohen,et al.  THE WIDE-FIELD INFRARED SURVEY EXPLORER (WISE): MISSION DESCRIPTION AND INITIAL ON-ORBIT PERFORMANCE , 2010, 1008.0031.

[28]  A. Harris,et al.  New findings on asteroid spin-vector distributions , 2007 .