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We used Gaia Data Release 2 to search for upcoming photometric microlensing events, identifying two candidates with high amplification. In the case of candidate 1, a spectrum of the lens (l1) confirms it is a usdM3 subdwarf with mass $approx 0.11 M_odot$, while the event reaches maximum amplification of $20^{+20}_{-10}$ mmag on November 3rd 2019 ($pm$1d). For candidate 2, the lens (l2) is a metal-poor M dwarf with mass $approx 0.38 M_odot$ derived from spectral energy distribution (SED) fitting, and maximum amplification of $10^{+40}_{-10}$ mmag occurs on June 3rd 2019 ($pm$4d). This permits a new algorithm for mass inference on the microlens. Given the predicted time, the photometric lightcurve of these events can be densely sampled by ground-based telescopes. The lightcurve is a function of the unknown lens mass, together with 8 other parameters for all of which Gaia provides measurements and uncertainties. Leveraging this prior information on the source and lens provided by Gaias astrometric solution, and assuming that a ground-based campaign can provide 50 measurements at mmag precision, we show for example that the mass of l1 can be recovered to within 20 per cent (68 per cent confidence limit).
Microlensing events can be used to directly measure the masses of single field stars to a precision of $sim$1-10%. The majority of direct mass measurements for stellar and sub-stellar objects typically only come from observations of binary systems. H
Stellar variability studies are now reaching a completely new level thanks to ESAs Gaia mission, which enables us to locate many variable stars in the Hertzsprung-Russell diagram and determine the various instability strips/bands. Furthermore, this m
We present an adaptive optics (AO) analysis of images from the Keck-II telescope NIRC2 instrument of the planetary microlensing event MOA-2009-BLG-319. The $sim$10 year baseline between the event and the Keck observations allows the planetary host st
In the coming years, next-generation space-based infrared observatories will significantly increase our samples of rare massive stars, representing a tremendous opportunity to leverage modern statistical tools and methods to test massive stellar evol
New spectroscopic surveys offer the promise of consistent stellar parameters and abundances (stellar labels) for hundreds of thousands of stars in the Milky Way: this poses a formidable spectral modeling challenge. In many cases, there is a sub-set o