The fast transient sky with Gaia
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...
Gespeichert in:
Veröffentlicht in: | Monthly notices of the Royal Astronomical Society 2018-01, Vol.473 (3), p.3854-3862 |
---|---|
Hauptverfasser: | , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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 deg2 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. |
---|---|
ISSN: | 0035-8711 1365-2966 |
DOI: | 10.1093/mnras/stx2625 |