Mind the gap: the power of combining photometric surveys with intensity mapping

Modi, Chirag; White, Martin; Castorina, Emanuele; Slosar, Anže

doi:10.1088/1475-7516/2021/10/056

Title: Mind the gap: the power of combining photometric surveys with intensity mapping

Journal Article · 18 October 2021 · Journal of Cosmology and Astroparticle Physics

DOI: https://doi.org/10.1088/1475-7516/2021/10/056 · OSTI ID:1855750

Modi, Chirag ^[1]; White, Martin ^[2]; Castorina, Emanuele ^[3]; Slosar, Anže ^[4]

Univ. of California, Berkeley, CA (United States); Flatiron Institute, New York, NY (United States)
Univ. of California, Berkeley, CA (United States)
Univ. degli Studi di Milano (Italy); European Organization for Nuclear Research (CERN), Geneva (Switzerland)
Brookhaven National Lab. (BNL), Upton, NY (United States)

The long wavelength modes lost to bright foregrounds in the interferometric 21-cm surveys can partially be recovered using a forward modeling approach that exploits the non-linear coupling between small and large scales induced by gravitational evolution. In this work, we build upon this approach by considering how adding external galaxy distribution data can help to fill in these modes. We consider supplementing the 21-cm data at two different redshifts with a spectroscopic sample (good radial resolution but low number density) loosely modeled on DESI-ELG at z=1 and a photometric sample (high number density but poor radial resolution) similar to LSST sample at z=1 and z=4 respectively. We find that both the galaxy samples are able to reconstruct the largest modes better than only using 21-cm data, with the spectroscopic sample performing significantly better than the photometric sample despite much lower number density. Here, we demonstrate the synergies between surveys by showing that the primordial initial density field is reconstructed better with the combination of surveys than using either of them individually. Methodologically, we also explore the importance of smoothing the density field when using bias models to forward model these tracers for reconstruction.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), High Energy Physics (HEP)

Grant/Contract Number:: SC0012704

OSTI ID:: 1855750

Report Number(s):: BNL-222872-2022-JAAM; TRN: US2305042

Journal Information:: Journal of Cosmology and Astroparticle Physics, Vol. 2021, Issue 10; ISSN 1475-7516

Publisher:: Institute of Physics (IOP)Copyright Statement

Country of Publication:: United States

Language:: English

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