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Revising the Halofit Model for the Nonlinear Matter Power Spectrum

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abstract

Based on a suite of state-of-the-art high-resolution $N$-body simulations, we revisit the so-called halofit model (Smith et al. 2003) as an accurate fitting formula for the nonlinear matter power spectrum. While the halofit model has been frequently used as a standard cosmological tool to predict the nonlinear matter power spectrum in a universe dominated by cold dark matter, its precision has been limited by the low-resolution of $N$-body simulations used to determine the fitting parameters, suggesting the necessity of improved fitting formula at small scales for future cosmological studies. We run high-resolution $N$-body simulations for 16 cosmological models around the Wilkinson Microwave Anisotropy Probe (WMAP) best-fit cosmological parameters (1, 3, 5, and 7 year results), including dark energy models with a constant equation of state. The simulation results are used to re-calibrate the fitting parameters of the halofit model so as to reproduce small-scale power spectra of the $N$-body simulations, while keeping the precision at large scales. The revised fitting formula provides an accurate prediction of the nonlinear matter power spectrum in a wide range of wavenumber ($k \leq 30h$\,Mpc$^{-1}$) at redshifts $0 \leq z \leq 10$, with 5% precision for $k\leq1 h$ Mpc$^{-1}$ at $0 \leq z \leq 10$ and 10% for $1 \leq k\leq 10 h$ Mpc$^{-1} $ at $0 \leq z \leq 3$. We discuss the impact of the improved halofit model on weak lensing power spectra and correlation functions, and show that the improved model better reproduces ray-tracing simulation results.

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A unified harmonic framework for dark siren cosmology

astro-ph.CO · 2026-03-13 · unverdicted · novelty 6.0

The GW-galaxy cross-correlation method, unified with spectral sirens in a harmonic framework, can measure H0 to 1% and Omega_m to 5% precision with 2 years of data from next-generation detectors like Einstein Telescope and Cosmic Explorer.

Machine-learning applications for weak-lensing cosmology

astro-ph.CO · 2026-05-13 · unverdicted · novelty 2.0

Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.

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Showing 4 of 4 citing papers after filters.

  • How to augment cosmic shear measurements with radio polarimetry of galaxies? astro-ph.CO · 2026-05-08 · unverdicted · none · ref 56

    A Gaussian statistical model of galaxy shapes and radio polarizations yields unbiased, minimum-variance estimators for cosmic shear, intrinsic alignment, and line-of-sight rotation that are accurate to first order.

  • A unified harmonic framework for dark siren cosmology astro-ph.CO · 2026-03-13 · unverdicted · none · ref 53 · internal anchor

    The GW-galaxy cross-correlation method, unified with spectral sirens in a harmonic framework, can measure H0 to 1% and Omega_m to 5% precision with 2 years of data from next-generation detectors like Einstein Telescope and Cosmic Explorer.

  • Modeling nonlinear scales for dynamical dark energy cosmologies with COLA astro-ph.CO · 2025-10-16 · unverdicted · none · ref 127 · internal anchor

    COLA-based hybrid emulator reproduces nonlinear power spectrum boosts in w0wa models to <2% error vs EuclidEmulator2 and produces <0.3σ shifts in LSST-like cosmic shear parameter constraints.

  • Machine-learning applications for weak-lensing cosmology astro-ph.CO · 2026-05-13 · unverdicted · none · ref 56 · internal anchor

    Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.