Analytical and fitting formulae for Lyα radiative-transfer spectra under slab, cylindrical and spherical geometries, including recoil and constant velocity gradients, verified against Monte Carlo simulations.
The Coyote Universe I: Precision Determination of the Nonlinear Matter Power Spectrum
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
abstract
Near-future cosmological observations targeted at investigations of dark energy pose stringent requirements on the accuracy of theoretical predictions for the clustering of matter. Currently, N-body simulations comprise the only viable approach to this problem. In this paper we demonstrate that N-body simulations can indeed be sufficiently controlled to fulfill these requirements for the needs of ongoing and near-future weak lensing surveys. By performing a large suite of cosmological simulation comparison and convergence tests we show that results for the nonlinear matter power spectrum can be obtained at 1% accuracy out to k~1 h/Mpc. The key components of these high accuracy simulations are: precise initial conditions, very large simulation volumes, sufficient mass resolution, and accurate time stepping. This paper is the first in a series of three, with the final aim to provide a high-accuracy prediction scheme for the nonlinear matter power spectrum.
citation-role summary
background 1
citation-polarity summary
years
2026 6roles
background 1polarities
background 1representative citing papers
Calibrates a one-parameter semi-analytic damping model for oscillatory primordial power spectrum features using N-body simulations and validates sub-percent accuracy via GPR emulation when modulation frequency is high enough.
The paper develops R^wst, a bias-robust wavelet scattering statistic that delivers unbiased constraints on cosmological parameters and improves degeneracy breaking versus the two-point correlation function via simulation-based inference.
Neighbor-density-weighted marked correlation functions improve FoM for Ω_m–σ_8 by 1.7–2.5× over standard 2PCF using emulators from 129 w0waCDM+∑m_ν simulations.
Bayesian hierarchical modeling of photometric redshifts in KiDS+VIKING-450 raises S8 to 0.756 ± 0.039 and reduces Planck tension to 1.9σ.
Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.
citing papers explorer
-
Analytical and fitting formulae for solutions to Lyman-alpha radiative transfer equations: the effects of geometry, recoil, and velocity gradients
Analytical and fitting formulae for Lyα radiative-transfer spectra under slab, cylindrical and spherical geometries, including recoil and constant velocity gradients, verified against Monte Carlo simulations.
-
(The) Wiggles going non-linear
Calibrates a one-parameter semi-analytic damping model for oscillatory primordial power spectrum features using N-body simulations and validates sub-percent accuracy via GPR emulation when modulation frequency is high enough.
-
Cosmological Constraints from Bias-Robust Wavelet Scattering Statistics for Stage-IV Galaxy Surveys
The paper develops R^wst, a bias-robust wavelet scattering statistic that delivers unbiased constraints on cosmological parameters and improves degeneracy breaking versus the two-point correlation function via simulation-based inference.
-
Cosmological constraints from neighbor-density-weighted marked correlation functions
Neighbor-density-weighted marked correlation functions improve FoM for Ω_m–σ_8 by 1.7–2.5× over standard 2PCF using emulators from 129 w0waCDM+∑m_ν simulations.
-
KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions
Bayesian hierarchical modeling of photometric redshifts in KiDS+VIKING-450 raises S8 to 0.756 ± 0.039 and reduces Planck tension to 1.9σ.
-
Machine-learning applications for weak-lensing cosmology
Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.