papers

Publications (43)

astro-ph.IM2025

Learning novel representations of variable sources from multi-modal data via autoencoders

P. Huijse, J. De Ridder, L. Eyer +18

Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sour…

astro-ph.IM2018

Variability search in M 31 using Principal Component Analysis and the Hubble Source Catalog

M. I. Moretti, D. Hatzidimitriou, A. Karampelas +4

Principal Component Analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effe…

astro-ph.SR2017

Gaia Data Release 1. Open cluster astrometry: performance, limitations, and future prospects

Gaia Collaboration, F. van Leeuwen, A. Vallenari +589

Context. The first Gaia Data Release contains the Tycho-Gaia Astrometric Solution (TGAS). This is a subset of about 2 million stars for which, besides the position and photometry,…

astro-ph.GA2024

Discovery of a dormant 33 solar-mass black hole in pre-release Gaia astrometry

Gaia Collaboration, P. Panuzzo, T. Mazeh +412

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected base…

astro-ph.IM2016

Comparative performance of selected variability detection techniques in photometric time series

K. V. Sokolovsky, P. Gavras, A. Karampelas +20

Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection techniq…

astro-ph.IM2022

Gaia Data Release 3: Cross-match of Gaia sources with variable objects from the literature

P. Gavras, L. Rimoldini, K. Nienartowicz +22

Context. In the current ever increasing data volumes of astronomical surveys, automated methods are essential. Objects of known classes from the literature are necessary for traini…