A. O'Grady | Searcharxiv

arXiv2026

Multiplicity of Massive Stars at Low Metallicity: Early Results from the BLOeM Campaign

Massive stars at low metallicity (Z) play a central role in shaping the high-redshift Universe, yet their multiplicity remains poorly constrained. The Binarity at Low Metallicity (BLOeM) campaign is a two-year survey of 929 stars in the Small Magellanic Cloud with the Fibre Large Array Multi Element Spectrograph (FLAMES) instrument at ESO's Very Large Telescope, providing the first large-scale spectroscopic monitoring of massive stars at low Z (1/5 solar). Analysis of the initial nine epochs reveals high intrinsic binary fractions (>70%) on the main sequence and a steep decline in evolved objects. Analysis of the full dataset will yield orbital solutions, identify black-hole companions, and allow a derivation of the initial mass function for single and binary stars at low Z.

physics.gen-ph↗

arXiv2019

Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)

We describe the simulated data sample for the "Photometric LSST Astronomical Time Series Classification Challenge" (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the Large Synoptic Survey Telescope (LSST), a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to 2018 December 17, and included 1,094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of type Ia supernova used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models.

astro-ph.HE↗