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LISA and the LISA Science Team
Anna Heffernan, Chiara Caprini, Neil Cornish +19
LISA, the Laser Interferometer Space Antenna, due to launch mid-2035, is a large class space mission by the European Space Agency (ESA). In partnership with NASA and ESA-member sta…
The BlackGEM telescope array I: Overview
Paul J. Groot, S. Bloemen, P. Vreeswijk +75
The main science aim of the BlackGEM array is to detect optical counterparts to gravitational wave mergers. Additionally, the array will perform a set of synoptic surveys to detect…
FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series
F. Stoppa, C. Johnston, E. Cator +2
Optimal frequency identification in astronomical datasets is crucial for variable star studies, exoplanet detection, and asteroseismology. Traditional period-finding methods often…
AutoSourceID-Classifier. Star-Galaxy Classification using a Convolutional Neural Network with Spatial Information
F. Stoppa, S. Bhattacharyya, R. Ruiz de Austri +10
Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogues, a process susceptible to introducing inaccuracies, thereby potentially jeo…
The continuous cadence Roman Galactic Bulge survey
Thomas Kupfer, Camilla Danielski, Poshak Gandhi +4
Galactic binaries with orbital periods less than 1 hour are strong gravitational wave sources in the mHz regime, ideal for the Laser Interferometer Space Antenna (LISA). At least s…
AutoSourceID-FeatureExtractor. Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation
F. Stoppa, R. Ruiz de Austri, P. Vreeswijk +9
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regress…