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arXiv · 2610.06082

Spins and shapes of asteroids reconstructed from photometry from surveys

Abstract

Modern asteroid surveys routinely acquire sparse photometric measurements for hundreds of thousands of asteroids. These data can be exploited to reconstruct asteroid spin states and shapes, providing statistical constraints on the rotational evolution of different dynamical populations.Our goal is to derive spin-state and shape models from publicly available survey photometry and use the enlarged sample to investigate the distributions of asteroid physical properties across the Solar System. We combined sparse photometry from Catalina, Mt. Lemmon, Pan-STARRS, ZTF, USNO, ATLAS, ASAS-SN, TESS, and Gaia and applied convex light-curve inversion to determine sidereal rotation periods, spin-axis orientations, convex shapes, phase-function parameters, and colors. The extensive parameter-space search was performed using the distributed-computing project Asteroids@home.We derived approximately 30000 asteroid models, including about 22000 unique spin-state solutions and almost 10000 partial pole solutions, tripling the number of available asteroid models. The enlarged sample confirms the dependence of the rotation-period distribution on taxonomic class, reveals a pronounced lack of elongated asteroids near the spin barrier, and shows that slow rotators exhibit systematically larger photometric residuals, supporting the interpretation that many are in non-principal-axis rotation. We derived spin-state distributions for 47 near-Earth asteroids, 247 Jupiter Trojans, and 157 Hildas. The expanded Trojan sample no longer shows a statistically significant excess of prograde rotators. The combination of modern survey photometry and large-scale light-curve inversion enables population studies based on tens of thousands of asteroid models. The resulting database provides improved constraints on the rotational evolution of asteroids

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BibTeXRIS

Josef Ďurech, Josef Hanuš. 2026-10-05. Spins and shapes of asteroids reconstructed from photometry from surveys. https://doi.org/10.1051/0004-6361%2F202662316

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