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Probing the Intergalactic Medium with Lyα and 21 cm Fluctuations

2016/11/30 by Caroline Heneka, Asantha Cooray, Chang Feng · 1 citation
Engineering · Physics and Astronomy · #Alpha (finance) #Astrophysics #Astrophysics and Cosmic Phenomena #Galaxy #Intergalactic medium #Ion #Ionization #Optical depth #Physics #Quantum mechanics #Radio Astronomy Observations and Technology #Radio Wave Propagation Studies #Redshift #Reionization #Spectral density #Statistics #astro-ph.CO

paper · pdf · doi:10.3847/1538-4357/aa8eed

published as ApJ, 848 (2017) 52 · 26 pages, 18 figures, 3 tables. Accepted for publication in ApJ

openalex publication_date 2017/10/10 · arxiv created 2017/10/17 · arxiv updated 2017/10/18 · openalex created_date 2017/10/20 · openalex updated_date 2026/08/06

Abstract

Abstract We study 21 cm and Ly α fluctuations, as well as H α , while distinguishing between Ly α emission of galactic, diffuse, and scattered intergalactic medium (IGM) origin. Cross-correlation information about the state of the IGM is obtained, testing neutral versus ionized medium cases with different tracers in a seminumerical simulation setup. In order to pave the way toward constraints on reionization history and modeling beyond power spectrum information, we explore parameter dependencies of the cross-power signal between 21 cm and Ly α , which displays a characteristic morphology and a turnover from negative to positive correlation at scales of a couple Mpc −1 . In a proof of concept for the extraction of further information on the state of the IGM using different tracers, we demonstrate the use of the 21 cm and H α cross-correlation signal to determine the relative strength of galactic and IGM emission in Ly α . We conclude by showing the detectability of the 21 cm and Ly α cross-correlation signal over more than one decade in scale at high signal-to-noise ratio for upcoming probes like SKA and the proposed all-sky intensity mapping satellites SPHEREx and CDIM, while also including the Ly α damping tail and 21 cm foreground avoidance in the modeling.

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