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PBH abundance from random Gaussian curvature perturbations and a local density threshold
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The production rate of primordial black holes is often calculated by considering a nearly Gaussian distribution of cosmological perturbations, and assuming that black holes will form in regions where the amplitude of such perturbations exceeds a certain threshold. A threshold $\zeta_{\rm th}$ for the curvature perturbation is somewhat inappropriate for this purpose, because it depends significantly on environmental effects, not essential to the local dynamics. By contrast, a threshold $\delta_{\rm th}$ for the density perturbation at horizon crossing seems to provide a more robust criterion. On the other hand, the density perturbation is known to be bounded above by a maximum limit $\delta_{\rm max}$, and given that $\delta_{\rm th}$ is comparable to $\delta_{\rm max}$, the density perturbation will be far from Gaussian near or above the threshold. In this paper, we provide a new plausible estimate for the primordial black hole abundance based on peak theory. In our approach, we assume that the curvature perturbation is given as a random Gaussian field with the power spectrum characterized by a single scale, while an optimized criterion for PBH formation is imposed, based on the locally averaged density perturbation. Both variables are related by the full nonlinear expression derived in the long-wavelength approximation of general relativity. We do not introduce a window function, and the scale of the inhomogeneity is introduced as a random variable in the peak theory. We find that the mass spectrum is shifted to larger mass scales by one order of magnitude or so, compared to a conventional calculation. The abundance of PBHs becomes significantly larger than the conventional one, by many orders of magnitude, mainly due to the optimized criterion for PBH formation and the removal of the suppresion associated with a window function.
Forward citations
Cited by 7 Pith papers
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The statistics of curvature-profile dispersion in primordial black hole formation
Rare coherent shape deformations of primordial curvature profiles can dominate primordial black hole abundance by lowering the collapse threshold enough to overcome their Gaussian statistical cost.
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One Feature, Three Clocks: Phase-Locked Gravitational Waves, Primordial Black Holes, and Non-Gaussianity from Periodic Warm Inflation
Periodic warm inflation imprints one log-periodic feature on the curvature spectrum that saturates asteroid-mass PBHs, generates dual-band GW backgrounds, and offsets the bispectrum phase by a quarter cycle fixed by s...
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Memoirs of the curvaton: non-perturbative non-Gaussianity and supermassive primordial black holes
Curvaton self-interactions in non-quadratic potentials produce a local non-Gaussian map that enables supermassive primordial black hole formation at peak amplitudes of order 10^{-5} while remaining consistent with μ-d...
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Primordial Black Hole from Tensor-induced Density Fluctuation: First-order Phase Transitions and Domain Walls
Tensor perturbations from first-order phase transitions and domain wall annihilation induce curvature fluctuations at second order that form primordial black holes, allowing asteroid-mass PBHs to comprise all dark mat...
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Isotropy, anisotropies and non-Gaussianity in the scalar-induced gravitational-wave background: diagrammatic approach for primordial non-Gaussianity up to arbitrary order
Extends diagrammatic approach for scalar-induced gravitational waves to arbitrary-order local PNG, deriving semi-analytic spectra for energy density, anisotropies, bispectrum and trispectrum up to quartic terms.
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Primordial black hole formation in bulk-viscous cosmology
Bulk viscosity raises the critical collapse threshold for primordial black holes by an amount comparable to the viscosity strength and increases the resulting black hole masses.
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Synergy between CSST and future gravitational-wave detectors: Probing primordial black holes by cross-correlating dark sirens with galaxies
Cross-correlating CSST galaxies with mock GW catalogs from ET2CE and BDET2CE networks can detect PBH merger fractions above ~40% and ~20% respectively via clustering bias differences.
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