The fast transient sky with Gaia. Issue 3 (9th October 2017)

• Record Type: Journal Article
• Authors: Wevers, Thomas; Jonker, Peter G.; Hodgkin, Simon T.; Kostrzewa-Rutkowska, Zuzanna; Harrison, Diana L.; Rixon, Guy; Nelemans, Gijs; Roelens, Maroussia; Eyer, Laurent; van Leeuwen, Floor; Yoldas, Abdullah
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 473:Issue 3(2018)
• Page Start: 3854
• Page End: 3862
• Publication Date: 2017-10-09
• Subjects: methods: data analysis -- methods: statistical -- surveys -- stars: flare; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stx2625
• Languages: English
• ISSNs: 0035-8711

Abstract

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 charge coupled devices (CCDs) in 45 s and a light curve 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 onboard and data processing artefacts, and present a statistical method to identify sources that show transient brightness variations on ≲2 h time-scales. 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 time-scales ranging from 15 s to several hours. We search an area of ∼23.5 deg 2 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 time-scales 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.