Gaussian-Process Emulation of the Redshift-Space Halo Power Spectrum Monopole in Cosmologies with Massive Neutrinos

Fuente: arXiv
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Main Authors: Gan, Jixin, Feng, Yonghao, Zhao, Gong-Bo
Format: Preprint
Published: 2026
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author Gan, Jixin
Feng, Yonghao
Zhao, Gong-Bo
author_facet Gan, Jixin
Feng, Yonghao
Zhao, Gong-Bo
contents We present a Gaussian-process (GP) emulator for the monopole of the redshift-space halo power spectrum in $Λ$CDM cosmologies with massive neutrinos. The emulator is trained on 1000 COLA simulations distributed in a Latin-hypercube design over the six-dimensional cosmological parameter space $\{Ω_m h^2,Ω_b h^2,Ω_νh^2,σ_8,h,n_s\}$, with outputs at 11 snapshots spanning $0.5 \le z \le 2.0$. From redshift-space halo catalogues we measure shot-noise-subtracted monopole spectra over $0.01 \le k \le 0.50\,h\,\mathrm{Mpc}^{-1}$. We also generate 1000 fixed-cosmology realizations to estimate the covariance matrix and to construct synthetic data vectors for likelihood tests. On held-out cosmologies, the emulator reproduces the simulated spectra to typically better than $2\%$ across the scales and redshifts considered. Combined with its GP-based estimate of interpolation uncertainty, this speed and accuracy make the emulator well suited to repeated likelihood evaluations in Markov Chain Monte Carlo analyses. The resulting framework provides an efficient route toward neutrino-mass inference from DESI-motivated redshift-space clustering measurements.
format Preprint
id arxiv_https___arxiv_org_abs_2604_04122
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Gaussian-Process Emulation of the Redshift-Space Halo Power Spectrum Monopole in Cosmologies with Massive Neutrinos
Gan, Jixin
Feng, Yonghao
Zhao, Gong-Bo
Cosmology and Nongalactic Astrophysics
We present a Gaussian-process (GP) emulator for the monopole of the redshift-space halo power spectrum in $Λ$CDM cosmologies with massive neutrinos. The emulator is trained on 1000 COLA simulations distributed in a Latin-hypercube design over the six-dimensional cosmological parameter space $\{Ω_m h^2,Ω_b h^2,Ω_νh^2,σ_8,h,n_s\}$, with outputs at 11 snapshots spanning $0.5 \le z \le 2.0$. From redshift-space halo catalogues we measure shot-noise-subtracted monopole spectra over $0.01 \le k \le 0.50\,h\,\mathrm{Mpc}^{-1}$. We also generate 1000 fixed-cosmology realizations to estimate the covariance matrix and to construct synthetic data vectors for likelihood tests. On held-out cosmologies, the emulator reproduces the simulated spectra to typically better than $2\%$ across the scales and redshifts considered. Combined with its GP-based estimate of interpolation uncertainty, this speed and accuracy make the emulator well suited to repeated likelihood evaluations in Markov Chain Monte Carlo analyses. The resulting framework provides an efficient route toward neutrino-mass inference from DESI-motivated redshift-space clustering measurements.
title Gaussian-Process Emulation of the Redshift-Space Halo Power Spectrum Monopole in Cosmologies with Massive Neutrinos
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2604.04122