A six-parameter function of peak height ν, power spectrum slope n_eff, and growth rate α_eff accurately describes median halo mass accretion rates from simulations in ΛCDM and Einstein-de Sitter cosmologies at z=0-14.
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Introduces reionization relics as a large-scale cosmological probe for warm dark matter, forecasting m_WDM constraints of >5.0 keV (Lyα alone) and >7.1 keV (combined with 21 cm) at 95% CL.
Small-scale power spectrum boosts alter ionization morphology enough that 21 cm power spectra and bubble sizes remain distinguishable from Lambda CDM under current constraints, offering SKA a probe for such deviations.
Review chapter organizing machine learning methods for 21 cm cosmology into observation, theory, and inference domains.
citing papers explorer
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A universal model for the accretion rates and formation times of dark matter halos
A six-parameter function of peak height ν, power spectrum slope n_eff, and growth rate α_eff accurately describes median halo mass accretion rates from simulations in ΛCDM and Einstein-de Sitter cosmologies at z=0-14.
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Unveiling the dark matter nature with reionization relics
Introduces reionization relics as a large-scale cosmological probe for warm dark matter, forecasting m_WDM constraints of >5.0 keV (Lyα alone) and >7.1 keV (combined with 21 cm) at 95% CL.
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Probing power spectrum enhancement at small scales with the SKA
Small-scale power spectrum boosts alter ionization morphology enough that 21 cm power spectra and bubble sizes remain distinguishable from Lambda CDM under current constraints, offering SKA a probe for such deviations.
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Application of Machine Learning to 21 cm Cosmology
Review chapter organizing machine learning methods for 21 cm cosmology into observation, theory, and inference domains.