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arXiv · 2405.02206

Impact of Primordial Black Hole Dark Matter on Gas Properties at Very High Redshift: A Semi-Analytical Model

Abstract

Context. Primordial black holes (PBHs) have been proposed as potential candidates for dark matter (DM) and have garnered significant attention in recent years. Aims. Our objective is to delve into the distinct impact of PBHs on gas properties and their potential role in shaping the cosmic structure. Specifically, we aim to analyze the evolving gas properties while considering the presence of accreting PBHs with varying monochromatic masses and in different quantities. By studying the feedback effects produced by this accretion, our final goal is to assess the plausibility of PBHs as candidates for DM. Methods. We develop a semi-analytical model which works on top of the CIELO hydrodynamical simulation around $z\sim23$. This model enables a comprehensive analysis of the evolution of gas properties influenced by PBHs. Our focus lies on the temperature and hydrogen abundances, placing specific emphasis on the region closest to the halo center. We explore PBH masses of $1$, $33$, and $100~\Msun$, located within mass windows where a substantial fraction of DM could exist in the form of PBHs. We investigate various DM fractions composed of these PBHs ($f_{\rm{PBH}}>10^{-4}$). Results. Our findings suggest that the existence of PBHs with masses of $1~\Msun$ and fractions greater than or equal to approximately $10^{-2}$ would be ruled out due to the significant changes induced in gas properties. The same applies to PBHs with a mass of $33~\Msun$ and $100~\Msun$ and fractions greater than approximately $10^{-3}$. These effects are particularly pronounced in the region nearest to the halo center, potentially leading to delayed galaxy formation within haloes.

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BibTeXRIS

C. Casanueva-Villarreal, P. B. Tissera, N. Padilla, B. Liu, V. Bromm, S. Pedrosa, L. Bignone, R. Dominguez-Tenreiro. 2024-05-03. Impact of Primordial Black Hole Dark Matter on Gas Properties at Very High Redshift: A Semi-Analytical Model. https://doi.org/10.1051/0004-6361%2F202449650

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