Asteroid phase curves using sparse Gaia DR2 data and differential dense light curves

TL;DR

This paper introduces a new algorithm that merges sparse Gaia data with differential dense light curves to derive asteroid phase curves, enabling analysis of more objects despite diverse data sources and errors.

Contribution

The paper presents a novel method for combining sparse and differential dense photometry data to obtain asteroid phase curves, expanding analysis capabilities.

Findings

Validated on 26 Gaia-observed asteroids

Successfully merged diverse data types for phase curve extraction

Enhanced asteroid characterization from heterogeneous datasets

Abstract

The amount of sparse asteroid photometry being gathered by both space- and ground-based surveys is growing exponentially. This large volume of data poses a computational challenge owing to both the large amount of information to be processed and the new methods needed to combine data from different sources (e.g. obtained by different techniques, in different bands, and having different random and systematic errors). The main goal of this work is to develop an algorithm capable of merging sparse and dense data sets, both relative and differential, in preparation for asteroid observations originating from, for example, Gaia, TESS, ATLAS, LSST, K2, VISTA, and many other sources. We present a novel method to obtain asteroid phase curves by combining sparse photometry and differential ground-based photometry. In the traditional approach, the latter cannot be used for phase curves. Merging those two data types allows for the extraction of phase-curve information for a growing number of objects. Our method is validated for 26 sample asteroids observed by the Gaia mission.