SAFARI: Searching Asteroids For Activity Revealing Indicators

TL;DR

This study presents SAFARI, a novel method using DECam data to systematically identify active asteroids, confirming its effectiveness with a low occurrence rate consistent with previous estimates.

Contribution

The paper introduces a new informatics approach for detecting active asteroids using deep DECam images, demonstrating its capability and efficiency.

Findings

Detected one active asteroid among 11,703 objects

Confirmed the activity occurrence rate aligns with previous estimates

Validated DECam data as suitable for asteroid activity searches

Abstract

Active asteroids behave dynamically like asteroids but display comet-like comae. These objects are poorly understood, with only about 30 identified to date. We have conducted one of the deepest systematic searches for asteroid activity by making use of deep images from the Dark Energy Camera (DECam) ideally suited to the task. We looked for activity indicators amongst 11,703 unique asteroids extracted from 35,640 images. We detected three previously-identified active asteroids ((62412), (1) Ceres and (779) Nina), though only (62412) showed signs of activity. Our activity occurrence rate of 1 in 11,703 is consistent with the prevailing 1 in 10,000 activity occurrence rate estimate. Our proof of concept demonstrates 1) our novel informatics approach can locate active asteroids and 2) DECam data are well-suited to the search for active asteroids.