OUT OF ONE, MANY: DISTINGUISHING TIME DELAYS FROM LENSED SUPERNOVAE

Denissenya, Mikhail; Bag, Satadru; Kim, Alex G; Linder, Eric V; Shafieloo, Arman

dc.contributor.author	Denissenya, Mikhail
dc.contributor.author	Bag, Satadru
dc.contributor.author	Kim, Alex G
dc.contributor.author	Linder, Eric V
dc.contributor.author	Shafieloo, Arman
dc.date.accessioned	2023-03-29T06:03:54Z
dc.date.available	2023-03-29T06:03:54Z
dc.date.issued	2022
dc.identifier.citation	Denissenya, M., Bag, S., Kim, A. G., Linder, E. V., & Shafieloo, A. (2022). Out of one, many: distinguishing time delays from lensed supernovae. Monthly Notices of the Royal Astronomical Society, 511(1), 1210–1217. https://doi.org/10.1093/mnras/stac143	en_US
dc.identifier.uri	http://nur.nu.edu.kz/handle/123456789/6998
dc.description.abstract	Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single light curve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100 per cent success for determining the number of images for time delays greater than ∼10 d.	en_US
dc.language.iso	en	en_US
dc.publisher	Monthly Notices of the Royal Astronomical Society	en_US
dc.rights	Attribution-NonCommercial-ShareAlike 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/3.0/us/	*
dc.subject	Type of access: Open Access	en_US
dc.subject	gravitational lensing: strong	en_US
dc.subject	transients: supernovae	en_US
dc.subject	cosmology: observations	en_US
dc.subject	methods: numerical	en_US
dc.subject	data analysis	en_US
dc.title	OUT OF ONE, MANY: DISTINGUISHING TIME DELAYS FROM LENSED SUPERNOVAE	en_US
dc.type	Article	en_US
workflow.import.source	science