The fast transient sky with Gaia

TL;DR

This paper introduces a novel method to detect fast optical transients using Gaia's per CCD photometric data, revealing potential new transient phenomena on timescales of seconds to hours.

Contribution

The study develops a statistical filtering approach to identify fast transients in Gaia data, expanding the observational parameter space for optical time domain astronomy.

Findings

Detected four candidate fast transients in 23.5 sq. degrees

Identified transients as stellar flares on M-dwarfs and giants

Demonstrated Gaia's capability to observe brightness changes down to 0.3 mag in seconds to hours

Abstract

The ESA Gaia satellite scans the whole sky with a temporal sampling ranging from seconds and hours to months. Each time a source passes within the Gaia field of view, it moves over 10 CCDs in 45 s and a lightcurve with 4.5 s sampling (the crossing time per CCD) is registered. Given that the 4.5 s sampling represents a virtually unexplored parameter space in optical time domain astronomy, this data set potentially provides a unique opportunity to open up the fast transient sky. We present a method to start mining the wealth of information in the per CCD Gaia data. We perform extensive data filtering to eliminate known on-board and data processing artefacts, and present a statistical method to identify sources that show transient brightness variations on ~2 hours timescales. We illustrate that by using the Gaia photometric CCD measurements, we can detect transient brightness variations down to an amplitude of 0.3 mag on timescales ranging from 15 seconds to several hours. We search an area of ~23.5 square degrees on the sky, and find four strong candidate fast transients. Two candidates are tentatively classified as flares on M-dwarf stars, while one is probably a flare on a giant star and one potentially a flare on a solar type star. These classifications are based on archival data and the timescales involved. We argue that the method presented here can be added to the existing Gaia Science Alerts infrastructure for the near real-time public dissemination of fast transient events.