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  The EFT likelihood for large-scale structure

Cabass, G., & Schmidt, F. (2020). The EFT likelihood for large-scale structure. Journal of Cosmology and Astroparticle Physics, 2020(4): 042. doi:10.1088/1475-7516/2020/04/042.

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 Creators:
Cabass, Giovanni1, Author              
Schmidt, Fabian1, Author              
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1Physical Cosmology, MPI for Astrophysics, Max Planck Society, ou_2205644              

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 Abstract: We derive, using functional methods and the bias expansion, the conditional likelihood for observing a specific tracer field given an underlying matter field. This likelihood is necessary for Bayesian-inference methods. If we neglect all stochastic terms apart from the ones appearing in the auto two-point function of tracers, we recover the result of Schmidt et al., 2018 [1]. We then rigorously derive the corrections to this result, such as those coming from a non-Gaussian stochasticity (which include the stochastic corrections to the tracer bispectrum) and higher-derivative terms. We discuss how these corrections can affect current applications of Bayesian inference. We comment on possible extensions to our result, with a particular eye towards primordial non-Gaussianity. This work puts on solid theoretical grounds the effective-field-theory-(EFT-)based approach to Bayesian forward modeling.

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Language(s): eng - English
 Dates: 2020-04-24
 Publication Status: Published online
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1475-7516/2020/04/042
Other: LOCALID: 3243915
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Title: Journal of Cosmology and Astroparticle Physics
  Abbreviation : J. Cosmol. Astropart. Phys.
  Abbreviation : JCAP
Source Genre: Journal
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Pages: - Volume / Issue: 2020 (4) Sequence Number: 042 Start / End Page: - Identifier: ISSN: 1475-7516