Equivalence of the field-level inference and conventional analyses on large scales
We study a simple setup with dark matter halos in real space, with the amplitude of the linear density field <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi>A</a:mi> </a:math> as the only free cosmological parameter. We show that Eulerian perturbation theory is adequate for describing this system on large scales, compute the leading <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"> <c:mi>n</c:mi> </c:math> -point functions and perform a joint power spectrum, bispectrum, and trispectrum analysis. Beyond the bispectrum, which is crucial for breaking the degeneracy between <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"> <e:mi>A</e:mi> </e:math> and the linear bias, we find that addition of the trispectrum reduces the error on <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"> <g:mi>A</g:mi> </g:math> by only 20%–30%. Our results for the joint analysis are in good agreement with recent field-level analyses in the same setup. This implies that the field-level inference on large scales does not get significant information from large displacements beyond those in Eulerian kernels or higher-order <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"> <i:mi>n</i:mi> </i:math> -point functions beyond the trispectrum. We provide further evidence for this showing that the dependence of the error bars on the maximum wave numbers used in the analysis is the same in the two approaches. Our results are in disagreement with some of the recent joint power spectrum and bispectrum analyses using likelihood-free inference based on perturbative forward modeling. We discuss a possible origin of this discrepancy and highlight the importance of resolving it in order to have the optimal results in cosmological analyses based on perturbation theory.
Authors
- Anonymous
Institutions
- University of Padua (IT)
- Istituto Nazionale di Fisica Nucleare, Sezione di Padova (IT)
- Istituto Nazionale di Fisica Nucleare, Sezione di Firenze (IT)
- University of Florence (IT)
Publication Details
- Journal
- Physical review. D/Physical review. D.
- Published
- 2026-02-25
- DOI
- https://doi.org/10.1103/yhg1-c63b
- Primary Topic
- Statistical Methods and Bayesian Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00