The potential of sparse photometric data in asteroid shape modeling

TL;DR

This study explores the use of sparse photometric data from the Catalina Sky Survey for asteroid shape modeling, demonstrating that even lower-quality data can yield reliable models for certain asteroids with high lightcurve amplitudes.

Contribution

It shows that sparse CSS data can be used to derive unique asteroid shape models and validate rotational periods, expanding the potential of existing survey data for asteroid characterization.

Findings

CSS data enabled shape modeling for 13 asteroids with high confidence.

Derived 12 new rotational periods from CSS data, matching previous measurements.

Identified optimal shape resolutions for reliable lightcurve inversion models.

Abstract

We investigate the potential of the sparse data produced by the Catalina Sky Survey astrometric project (CSS for short) in asteroid shape and rotational state determination by the lightcurve inversion method. We show that although the photometric quality of the CSS data, compared to the dense data, is significantly worse, it is in principle possible that these data are for some asteroids with high lightcurve amplitudes sufficient for a unique shape determination. CSS data are available for $\sim$180 asteroids for which shape models were previously derived from different photometric data sets. For 13 asteroids from this sample, we derive their unique shape models based only on CSS data, compare the two independent shape models together and discuss the reliability of models derived from only CSS data. We also use CSS data to determine shape models for asteroids with already known rotational period values, derive 12 unique models and compare previously published periods with periods determined from the full 3D modeling by the lightcurve inversion method. Finally, we test different shape resolutions used in the lightcurve inversion method in order to find reliable asteroid models.