Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses

Fuente: arXiv
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Auteurs principaux: Akitsu, Kazuyuki, Simonović, Marko, Chen, Shi-Fan, Cabass, Giovanni, Zaldarriaga, Matias
Format: Preprint
Publié: 2025
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author Akitsu, Kazuyuki
Simonović, Marko
Chen, Shi-Fan
Cabass, Giovanni
Zaldarriaga, Matias
author_facet Akitsu, Kazuyuki
Simonović, Marko
Chen, Shi-Fan
Cabass, Giovanni
Zaldarriaga, Matias
contents We extend field-level inference to jointly constrain the cosmological parameters $\{A,ω_{\rm cdm},H_0\}$, in both real and redshift space. Our analyses are based on mock data generated using a perturbative forward model, with noise drawn from a Gaussian distribution with a constant power spectrum. This idealized setting, where the field-level likelihood is exactly Gaussian, allows us to precisely quantify the information content in the nonlinear field on large scales. We find that field-level inference accurately recovers all cosmological parameters in both real and redshift space, with uncertainties consistent with perturbation theory expectations. We show that these error bars are comparable to those obtained from a joint power spectrum and bispectrum analysis using the same perturbative model. Finally, we perform several tests using the Gaussian field-level likelihood to fit the mock data where the true noise model is non-Gaussian, and find significant biases in the inferred cosmological parameters. These results highlight that the success of field-level inference critically depends on using the correct likelihood, which may be the primary challenge for applying this method to smaller scales even in the perturbative regime.
format Preprint
id arxiv_https___arxiv_org_abs_2509_09673
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses
Akitsu, Kazuyuki
Simonović, Marko
Chen, Shi-Fan
Cabass, Giovanni
Zaldarriaga, Matias
Cosmology and Nongalactic Astrophysics
We extend field-level inference to jointly constrain the cosmological parameters $\{A,ω_{\rm cdm},H_0\}$, in both real and redshift space. Our analyses are based on mock data generated using a perturbative forward model, with noise drawn from a Gaussian distribution with a constant power spectrum. This idealized setting, where the field-level likelihood is exactly Gaussian, allows us to precisely quantify the information content in the nonlinear field on large scales. We find that field-level inference accurately recovers all cosmological parameters in both real and redshift space, with uncertainties consistent with perturbation theory expectations. We show that these error bars are comparable to those obtained from a joint power spectrum and bispectrum analysis using the same perturbative model. Finally, we perform several tests using the Gaussian field-level likelihood to fit the mock data where the true noise model is non-Gaussian, and find significant biases in the inferred cosmological parameters. These results highlight that the success of field-level inference critically depends on using the correct likelihood, which may be the primary challenge for applying this method to smaller scales even in the perturbative regime.
title Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2509.09673