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We investigate the capabilities of the ESA Gaia mission for detecting and character- izing short timescale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short timescale variability and estimating the underlying characteristic timescales from Gaia photometry, through extensive light-curve simulations for various periodic and transient short timescale variable types. We show that, with this approach, we can detect fast periodic variabil- ity, with amplitudes down to a few millimagnitudes, as well as some M dwarf flares and supernovae explosions, with limited contamination from longer timescale variables or constant sources. Timescale estimates from the variogram give valuable informa- tion on the rapidity of the underlying variation, which could complement timescale estimates from other methods, like Fourier-based periodograms, and be reinvested in preparation of ground-based photometric follow-up of short timescale candidates evi- denced by Gaia. The next step will be to find new short timescale variable candidates from real Gaia data, and to further characterize them using all the Gaia information, including color and spectrum.
Combined studies of variable stars and stellar clusters open great horizons, and they allow us to improve our understanding of stellar cluster formation and stellar evolution. In that prospect, the Gaia mission will provide astrometric, photometric,
The Gaia DR2 sample of short-timescale variable candidates results from the investigation of the first 22 months of Gaia photometry for a subsample of sources at the Gaia faint end. For this exercise, we limited ourselves to the case of suspected rap
The second Gaia data release (DR2, spring 2018) included a unique all-sky catalogue of large-amplitude long-period variables (LPVs) containing Miras and semi-regular variables. These stars are on the Asymptotic Giant Branch (AGB), and are characteriz
We use methods of differential astrometry to construct a small field inertial reference frame stable at the micro-arcsecond level. Such a high level of astrometric precision can be expected with the end-of-mission standard errors to be achieved with
Over 3 billion astronomical objects have been detected in the more than 22 million orthogonal transfer CCD images obtained as part of the Pan-STARRS1 $3pi$ survey. Over 85 billion instances of those objects have been automatically detected and charac