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Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation

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arxiv 2511.05484 v2 pith:ERFRFQ4Q submitted 2025-11-07 astro-ph.CO

Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation

classification astro-ph.CO
keywords fieldcontributionsdensityformulationgalaxynoisestochasticfield-level
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We revisit the stochastic, or noise, contributions to the galaxy density field within the effective field theory (EFT) of large-scale structure. Starting from the general, all-order expression of the EFT partition function, we elucidate how the stochastic contributions can be described by local nonlinear couplings of a single Gaussian noise field. We introduce an alternative formulation of the partition function in terms of such a noise field, and derive the corresponding field-level likelihood for biased tracers. This noise-field formulation can capture the complete set of stochastic contributions to the galaxy density at the field level in a normalized, positive-definite probability density which is suitable for numerical sampling. We illustrate this by presenting the first results of EFT-based field-level inference with non-Gaussian and density-dependent stochasticity on dark matter halos using LEFTfield.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Galaxy bias renormalization: Two-loop Power Spectrum, One-loop Trispectrum and Bispectrum

    astro-ph.CO 2026-06 unverdicted novelty 7.0

    Complete fifth-order galaxy bias renormalization in real space enables consistent two-loop power spectrum and one-loop bispectrum/trispectrum calculations for biased tracers with operator-level counterterms.

  2. On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

    astro-ph.CO 2026-04 unverdicted novelty 7.0

    A general non-perturbative field-level posterior is constructed and expanded around its Gaussian limit to express Fisher information in terms of connected correlators, recovering standard results for power spectrum an...

  3. Field-level vs summaries: convergence of information in non-Gaussian density fields

    astro-ph.CO 2026-06 unverdicted novelty 5.0

    In a controlled model with quadratic nonlinearity, field-level inference retains more parameter information than summaries up to 6-point functions as nonlinearity increases.