The large-scale environment of thermonuclear and core-collapse supernovae

The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution...

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Veröffentlicht in:Monthly notices of the Royal Astronomical Society 2021-12, Vol.510 (1)
Hauptverfasser: Tsaprazi, Eleni, Jasche, Jens, Goobar, Ariel, Peiris, Hiranya V., Andreoni, Igor, Coughlin, Michael W., Fremling, Christoffer U., Graham, Matthew J., Kasliwal, Mansi, Kulkarni, Shri R., Mahabal, Ashish A., Riddle, Reed, Sollerman, Jesper, Tzanidakis, Anastasios
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Sprache:eng
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Zusammenfassung:The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution of ~3.8 Mpc, constrained by the 2M+ + galaxy survey. We limit our analysis to redshift z < 0.036, using samples of 498 thermonuclear and 782 core-collapse SNe from the Zwicky Transient Facility’s Bright Transient Survey and Census of the Local Universe catalogues. We detect clustering of SNe with high significance; the observed clustering of the two SNe populations is consistent with each other. Further, the clustering of SN hosts is consistent with that of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey DR12 spectroscopic galaxy sample in the same redshift range. Using a tidal shear classifier, we classify the LSS into voids, sheets, filaments, and knots. We find that both SNe and SDSS galaxies are predominantly found in sheets and filaments. SNe are significantly under-represented in voids and over-represented in knots compared to the volume fraction in these structures. This work opens the potential for using forthcoming wide-field deep SN surveys as a complementary LSS probe.
ISSN:0035-8711
1365-2966