Asteroid models reconstructed from the Lowell Photometric Database and WISE data

Context. 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. Aims. 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 NASA’s WISE satellite. Methods. 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. Results. 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. Apart from updating the statistics for the dependence of the distribution on asteroid size, we revealed a significant discrepancy between the number of prograde and retrograde rotators for asteroids smaller than about 10 km. Conclusions. Combining optical photometry with thermal infrared light curves is an efficient approach to obtaining new physical models of asteroids. The amount of asteroid photometry is continuously growing and joint inversion of data from different surveys could lead to thousands of new models in the near future.

[1]  R. Roy,et al.  Spin states of asteroids in the Eos collisional family , 2017, 1707.05507.

[2]  Fernando Roig,et al.  Reanalysis of asteroid families structure through visible spectroscopy , 2005 .

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

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

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

[6]  Dominic J. Benford,et al.  Explanatory Supplement to the WISE All-Sky Data Release Products , 2012, WISE 2012.

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

[8]  S. Mottola,et al.  ROTATIONAL PROPERTIES OF THE MARIA ASTEROID FAMILY , 2013, 1311.5318.

[9]  D. Oszkiewicz,et al.  Asteroid models from the Lowell photometric database , 2016, 1601.02909.

[10]  L. Lebofsky,et al.  Systematic biases in radiometric diameter determinations , 1989 .

[11]  J. Ďurech,et al.  Thermophysical modeling of main-belt asteroids from WISE thermal data , 2018, Icarus.

[12]  Munetaka Ueno,et al.  Asteroid Catalog Using AKARI: AKARI/IRC Mid-Infrared Asteroid Survey , 2011 .

[13]  T. Santana-Ros,et al.  Photometric survey, modelling, and scaling of long-period and low-amplitude asteroids , 2017, 1711.01893.

[14]  E. L. Wright,et al.  PRELIMINARY RESULTS FROM NEOWISE: AN ENHANCEMENT TO THE WIDE-FIELD INFRARED SURVEY EXPLORER FOR SOLAR SYSTEM SCIENCE , 2011, 1102.1996.

[15]  William F. Bottke,et al.  An asteroid breakup 160 Myr ago as the probable source of the K/T impactor , 2007, Nature.

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

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

[18]  G. Neukum,et al.  Spectral study of the Eunomia asteroid family-I. Eunomia , 2005 .

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

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

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

[22]  S. Debei,et al.  E-Type Asteroid (2867) Steins as Imaged by OSIRIS on Board Rosetta , 2010, Science.

[23]  V. Al'i-Lagoa,et al.  Thermophysical modeling of asteroids from WISE thermal infrared data – Significance of the shape model and the pole orientation uncertainties , 2015, 1504.04199.

[24]  Stefano Mottola,et al.  Thermal inertia of near-Earth asteroids and implications for the magnitude of the Yarkovsky effect , 2007, 0704.1915.

[25]  J Berthier,et al.  Shape, size and multiplicity of main-belt asteroids I. Keck Adaptive Optics survey. , 2006, Icarus.

[26]  V. Al'i-Lagoa,et al.  Physical properties of B-type asteroids from WISE data , 2013, 1303.5487.

[27]  J. Spencer.  A rough-surface thermophysical model for airless planets , 1990 .

[28]  M. Kaasalainen,et al.  Spin vectors in the Koronis family: II. Additional clustered spins, and one stray , 2009 .

[29]  B. Carry,et al.  Asteroid shapes and thermal properties from combined optical and mid-infrared photometry inversion , 2017, 1706.01232.

[30]  Fred C. Witteborn,et al.  Mercury: Thermal Modeling and Mid-infrared (5–12 μm) Observations☆ , 1998 .

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

[32]  M. Kaasalainen,et al.  Combining asteroid models derived by lightcurve inversion with asteroidal occultation silhouettes , 2011, 1104.4227.

[33]  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 .

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

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

[36]  M. Delbo,et al.  Sizes and albedos of Mars-crossing asteroids from WISE/NEOWISE data , 2017, 1705.10263.

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

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