Cosmological parameters from the likelihood analysis of the galaxy power spectrum and bispectrum in real space
Andrea Oddo, Federico Rizzo, Emiliano Sefusatti, Cristiano Porciani,, Pierluigi Monaco

TL;DR
This paper performs a joint likelihood analysis of galaxy power spectrum and bispectrum in real space, using simulations to constrain cosmological and bias parameters effectively up to certain scales.
Contribution
It introduces a robust method combining power spectrum and bispectrum analysis with covariance estimation and bias modeling, improving parameter constraints in cosmology.
Findings
The bias model accurately recovers key cosmological parameters.
Including cross-covariance affects parameter estimation.
Excluding nearly equilateral triangles enhances bispectrum information.
Abstract
We present a joint likelihood analysis of the halo power spectrum and bispectrum in real space. We take advantage of a large set of numerical simulations and of an even larger set of halo mock catalogs to provide a robust estimate of the covariance properties. We derive constraints on bias and cosmological parameters assuming a theoretical model from perturbation theory at one-loop for the power spectrum and tree-level for the bispectrum. By means of the Deviance Information Criterion, we select a reference bias model dependent on seven parameters that can describe the data up to for the power spectrum and for the bispectrum at redshift . This model is able to accurately recover three selected cosmological parameters even for the rather extreme total simulation volume of $1000\, h^{-3} \, {\rm…
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