Presents a general analytic framework based on truncated BBGKY hierarchy solved via Volterra equations for computing power spectra in multi-species dark matter with finite velocity dispersion and Poisson fluctuations.
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Primordial Black Holes as Dark Matter: The Power Spectrum and Evaporation of Early Structures
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abstract
We consider the possibility that massive primordial black holes are the dominant form of dark matter. Black hole formation generates entropy fluctuations that adds a Poisson noise to the matter power spectrum. We use Lyman-alpha forest observations to constrain this Poisson term in matter power spectrum, then we constrain the mass of black holes to be less than few times 10^4 solar mass. We also find that structures with less than ~ 10^3 primordial black holes evaporate by now.
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Dissipation of small-scale primordial perturbations after neutrino decoupling cools relic neutrinos and reduces their abundance, enabling PTOLEMY to constrain the primordial curvature power spectrum to O(0.1) on scales k ≲ 3×10^5 Mpc^{-1}.
First UVLF-based constraints on model-agnostic isocurvature power spectra for CDM, baryon, neutrino, and dark radiation modes yield consistent 95% credible envelopes over k ~ 0.5-10 Mpc^{-1}.
One-loop time dependence in superhorizon curvature perturbations cancels when all-scale contributions and boundary terms are included consistently via the δN formalism.
For ultra-light PBHs with extended mass distributions, new CMB-derived 95% exclusion bounds on f_PBH are obtained by jointly varying ΛCDM parameters, yielding f_PBH < 1.6 × 10^{-5} for a uniform distribution between 10^{15} and 10^{17} g.
Repulsive-like primordial black holes in the Swiss-cheese framework produce quasi-de Sitter expansion, enabling inflation with evaporation reheating and acting as early dark energy for certain masses and densities.
In mixed ULDM-PBH halos the continuum PBH contribution alters soliton structure at the tens-of-percent level while discrete shot noise induces mode transitions too slow to matter on galactic timescales.
Updated compilation shows PBHs are tightly constrained across 55 orders of magnitude in mass, ruling out dominant dark matter contributions except in narrow windows, with many limits carrying observational uncertainties.
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
Stellar microlensing surveys exclude compact objects between 10^{-11} and 10^4 solar masses from making up all dark matter under standard assumptions.
citing papers explorer
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Probing the small-scale primordial power spectrum via relic neutrinos and acoustic reheating
Dissipation of small-scale primordial perturbations after neutrino decoupling cools relic neutrinos and reduces their abundance, enabling PTOLEMY to constrain the primordial curvature power spectrum to O(0.1) on scales k ≲ 3×10^5 Mpc^{-1}.
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New Isocurvature Constraints from JWST UV Luminosity Function
First UVLF-based constraints on model-agnostic isocurvature power spectra for CDM, baryon, neutrino, and dark radiation modes yield consistent 95% credible envelopes over k ~ 0.5-10 Mpc^{-1}.
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Inflation driven by repulsive-like primordial black holes
Repulsive-like primordial black holes in the Swiss-cheese framework produce quasi-de Sitter expansion, enabling inflation with evaporation reheating and acting as early dark energy for certain masses and densities.
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Constraints on Primordial Black Holes
Updated compilation shows PBHs are tightly constrained across 55 orders of magnitude in mass, ruling out dominant dark matter contributions except in narrow windows, with many limits carrying observational uncertainties.
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Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
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Stellar microlensing surveys as a probe of Primordial Black Holes: status and prospects
Stellar microlensing surveys exclude compact objects between 10^{-11} and 10^4 solar masses from making up all dark matter under standard assumptions.