ASTERIA -- Asteroid Thermal Inertia Analyzer

TL;DR

ASTERIA is a new Monte Carlo-based method for estimating asteroid thermal inertia using Yarkovsky drift detection, enabling analysis of smaller NEAs and independent verification from thermophysical modeling.

Contribution

The paper introduces ASTERIA, a novel thermal inertia estimation method that is independent of TPM and effective for small NEAs using Yarkovsky effect measurements.

Findings

ASTERRA provides reliable thermal inertia estimates consistent with literature.

The method is effective for small NEAs, especially sub-km objects.

ASTERA's accuracy is slightly lower than TPM but offers broader applicability.

Abstract

Thermal inertia estimates are available for a limited number of a few hundred objects, and the results are practically solely based on thermophysical modeling (TPM). We present a novel thermal inertia estimation method, Asteroid Thermal Inertia Analyzer (ASTERIA). The core of the ASTERIA model is the Monte Carlo approach, based on the Yarkovsky drift detection. We validate our model on asteroid Bennu plus ten well-characterized near-Earth asteroids (NEAs) for which a good estimation of the thermal inertia from the TPM exists. The tests show that the ASTERIA provides reliable results consistent with the literature values. The new method is independent from the TPM, allowing an independent verification of the results. As the Yarkovsky effect is more pronounced in small asteroids, the noteworthy advantage of the ASTERIA compared to the TPM is the ability to work with smaller asteroids for which TPM typically lacks the input data. We used the ASTERIA to estimate the thermal inertia of 38 NEAs, with 31 of them being sub-km asteroids. Twenty-nine objects in our sample are characterized as Potentially Hazardous Asteroids. On the limitation side, the ASTERIA is somewhat less accurate than the TPM. The applicability of our model is limited to NEAs, as the Yarkovsky effect is yet to be detected in main-belt asteroids. However, we can expect a significant increase in high-quality measurements of the input parameters relevant to the ASTERIA with upcoming surveys. This will surely increase the reliability of the results generated by the ASTERIA and widen the model's applicability.