Enabling discovery of gravitationally lensed explosive transients: a new method to build an all-sky watch list of groups and clusters of galaxies. Issue 2 (25th January 2023)

• Record Type: Journal Article
• Authors: Ryczanowski, Dan; Smith, Graham P; Bianconi, Matteo; McGee, Sean; Robertson, Andrew; Massey, Richard; Jauzac, Mathilde
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 520:Issue 2(2023)
• Page Start: 2547
• Page End: 2557
• Publication Date: 2023-01-25
• Subjects: gravitational lensing: strong -- galaxies: clusters: general -- transients: supernovae -- transients: gamma-ray bursts -- gravitational waves; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stad231
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: Cross-referencing a watch list of galaxy groups and clusters with transient detections from real-time streams of wide-field survey data is a promising method for discovering gravitationally lensed explosive transients, including supernovae, kilonovae, gravitational waves, and gamma-ray bursts in the next 10 yr. However, currently there exists no catalogue of objects with both sufficient angular extent and depth to adequately perform such a search. In this study, we develop a cluster-finding method capable of creating an all-sky list of galaxy group- and cluster-scale objects out to z ≃ 1 based on their lens-plane properties and using only existing data from wide-field infrared surveys such as VISTA Hemisphere Survey and UKIRT Hemisphere Survey, and all-sky WISE ( Wide-field Infrared Survey Explorer ) data. In testing this method, we recover 91 per cent of a sample containing known and candidate lensing objects with Einstein radii of θE ≥ 5 arcsec. We also search the surrounding regions of this test sample for other groups and clusters using our method and verify the existence of any significant findings by visual inspection, deriving estimates of the false positive rate that are as low as 6 per cent. The method is also tested on simulated Rubin data from their Data Preview 0 programme, which yields complementary results of a good recovery rate of ≳80 per cent for M 200 ≥ 7 × 10 13 M⊙ clusters and with no false positives produced in our test region. Importantly, our method is positioned to create a watch list in advance of Rubin's LSST, as it utilizes only existing data, therefore enabling the discovery of lensed transients early within the survey's lifetime.