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Constraining $z\lesssim 2$ ultraviolet emission with the upcoming ULTRASAT satellite

Published 22 Jan 2024 in astro-ph.CO and astro-ph.GA | (2401.12285v2)

Abstract: The Extragalactic Background Light (EBL) carries a huge astrophysical and cosmological content: its frequency spectrum and redshift evolution are determined by the integrated emission of unresolved sources, these being galaxies, active galactic nuclei, or more exotic components. The near-UV region of the EBL spectrum is currently not well constrained, yet a significant improvement can be expected thanks to the soon-to-be launched Ultraviolet Transient Astronomy Satellite (ULTRASAT). Intended to study transient events in the $2300-2900\,{\rm \r{A}}$ observed band, this detector will provide wide field maps, tracing the UV intensity fluctuations on the largest scales. In this paper, we suggest how to exploit ULTRASAT to reconstruct the redshift evolution of the UV-EBL volume emissivity. We build upon the work of Chiang et al. (2019), where the Clustering-Based Redshift (CBR) technique was used to study diffuse light maps from GALEX. Their results showed the capability of the cross correlation between GALEX and SDSS spectroscopic catalogs in constraining the UV emissivity, highlighting how CBR is sensitive only to the extragalactic emissions, avoiding foregrounds and Galactic contributions. In our analysis, we introduce a framework to forecast the CBR constraining power when applied to ULTRASAT and GALEX in cross correlation with the 5-year DESI spectroscopic survey. We show that these will yield a strong improvement in the measurement of the UV-EBL volume emissivity. For $\lambda = 1500\,{\rm \r{A}}$,non-ionizing continuum below $z \sim 2$, we forecast a $1\sigma$ uncertainty $\lesssim 26\%\,(9\%)$ with conservative (optimistic) bias priors using ULTRASAT full-sky map; similar constraints can be obtained from its low-cadence survey, which will provide a smaller but deeper map. We finally discuss how these results will foster our understanding of UV-EBL models.

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