Constraints on nature of ultra light dark matter particles with 21cm forest
arXiv:1910.06011 · doi:10.1103/PhysRevD.101.043516
Abstract
The ultra-light scalar fields can arise ubiquitously, for instance, as a result of the spontaneous breaking of an approximate symmetry such as the axion and more generally the axion-like particles. In addition to the particle physics motivations, these particles can also play a major role in cosmology by contributing to dark matter abundance and affecting the structure formation at sub-Mpc scales. In this paper, we propose to use the 21cm forest observations to probe the nature of ultra-light dark matter. The 21cm forest can probe much smaller scales than the Lyman- forest, that is, . We explore the range of the ultra-light dark matter mass and , the fraction of ultra-light dark matter with respect to the total matter, which can be probed by the 21cm forest. We find that 21cm forest can potentially put the dark matter mass lower bound eV for , which is 3 orders of magnitude bigger mass scale than those probed by the current Lyman- forest observations.While the effects of the ultra-light particles on the structure formation become smaller when the dominant component of dark matter is composed of the conventional cold dark matter, we find that the 21cm forest is still powerful enough to probe the sub-component ultra-light dark matter mass up to the order of eV. The Fisher matrix analysis shows that is the most optimal parameter set which the 21cm forest can probe with the minimal errors for a sub-component ultra-light dark matter scenario.
13 pages, 9 figures. Published in PRD
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- Probing Oscillons of Ultra-Light Axion-like Particle by 21cm Forest
- Using the redshift evolution of the Lyman- effective opacity as a probe of dark matter models
- Anisotropies in Cosmological 21 cm Background by Oscillons/I-balls of Ultra-light Axion-like Particle
- Deep learning-driven likelihood-free parameter inference for 21-cm forest observations
- Prospects for Observing High-redshift Radio-loud Quasars in the SKA Era: Paving the Way for 21-cm Forest Observations
- Probing Ultra-light Axion Dark Matter from 21cm Tomography using Convolutional Neural Networks
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- Survival of Gas in Subhalos and Its Impact on the 21 cm Forest Signals: Insights from Hydrodynamic Simulations
- Analytical modeling of the one-dimensional power spectrum of 21-cm forest based on a halo model method
- Efficient neutral-IGM inference from noisy 21-cm forest spectra with latent-space U-Net encoding and XGBoost
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