A galaxy-free phenomenological model for the 21-cm power spectrum during reionization. Issue 2 (31st May 2022)

• Record Type: Journal Article
• Authors: Mirocha, Jordan; Muñoz, Julian B; Furlanetto, Steven R; Liu, Adrian; Mesinger, Andrei
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 514:Issue 2(2022)
• Page Start: 2010
• Page End: 2030
• Publication Date: 2022-05-31
• Subjects: galaxies: high-redshift -- intergalactic medium -- dark ages, reionization, first stars -- diffuse radiation; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stac1479
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: Upper limits from the current generation of interferometers targeting the 21-cm signal from high redshifts have recently begun to rule out physically realistic, though still extreme, models of the Epoch of Reionization (EoR). While inferring the detailed properties of the first galaxies is one of the most important motivations for measuring the high- z 21-cm signal, they can also provide useful constraints on the properties of the intergalactic medium (IGM). Motivated by this, we build a simple, phenomenological model for the 21-cm power spectrum that works directly in terms of IGM properties, which bypasses the computationally expensive 3D semi-numerical modeling generally employed in inference pipelines and avoids explicit assumptions about galaxy properties. The key simplifying assumptions are that (i) the ionization field is binary, and composed of spherical bubbles with an abundance described well by a parametric bubble size distribution, and (ii) that the spin temperature of the 'bulk' IGM outside bubbles is uniform. Despite the simplicity of the model, the mean ionized fraction and spin temperature of the IGM recovered from mock 21-cm power spectra generated with 21 cm fast are generally in good agreement with the true input values. This suggests that it is possible to obtain comparable constraints on the IGM using models with very different assumptions, parameters, and priors. Our approach will thus be complementary to semi-numerical models as upper limits continue to improve in the coming years.