A rigorous EFT-based forward model for large-scale structure

Abstract

Conventional approaches to cosmology inference from galaxy redshift surveys are based on n-point functions, which are under rigorous perturbative control on sufficiently large scales. Here, we present an alternative approach, which employs a likelihood at the level of the galaxy density field. By integrating out small-scale modes based on effective-field theory arguments, we prove that this likelihood is under perturbative control if certain specific conditions are met. We further show that the information captured by this likelihood is equivalent to the combination of the next-to-leading order galaxy power spectrum, leading-order bispectrum, and BAO reconstruction. Combined with MCMC sampling and MAP optimization techniques, our results allow for fully Bayesian cosmology inference from large-scale structure that is under perturbative control. We illustrate this via a first demonstration of unbiased cosmology inference from nonlinear large-scale structure using this likelihood. In particular, we show unbiased estimates of the power spectrum normalization ${\sigma }_8$ from a catalog of simulated dark matter halos, where nonlinear information is crucial in breaking the $b_1-{\sigma }_8$ degeneracy.

arXiv comment38 pages, 1 figure; v2: numerous clarifications, matches JCAP accepted version

References in corpus (40)

• The cosmological simulation code GADGET-2
• Baryonic Features in the Matter Transfer Function
• Large-Scale Structure of the Universe and Cosmological Perturbation Theory
• Large-Scale Galaxy Bias
• Cosmological Non-Linearities as an Effective Fluid
• The Effective Field Theory of Cosmological Large Scale Structures
• Improving Cosmological Distance Measurements by Reconstruction of the Baryon Acoustic Peak
• On the Robustness of the Acoustic Scale in the Low-Redshift Clustering of Matter
• The evolution substructure I: a new identification method
• Bayesian physical reconstruction of initial conditions from large scale structure surveys
• Bias in the Effective Field Theory of Large Scale Structures
• Renormalized Halo Bias
• Biased Tracers and Time Evolution
• On the Renormalization of the Effective Field Theory of Large Scale Structures
• ELUCID - Exploring the Local Universe with reConstructed Initial Density field I: Hamiltonian Markov Chain Monte Carlo Method with Particle Mesh Dynamics
• The Shift of the Baryon Acoustic Oscillation Scale: A Simple Physical Picture
• Bayesian reconstruction of the cosmological large-scale structure: methodology, inverse algorithms and numerical optimization
• Fast Hamiltonian sampling for large scale structure inference
• POTENT Reconstruction from Mark III Velocities
• Reconstructing baryon oscillations
• Towards optimal extraction of cosmological information from nonlinear data
• Iterative initial condition reconstruction
• Bayesian non-linear large scale structure inference of the Sloan Digital Sky Survey data release 7
• Cubic Halo Bias in Eulerian and Lagrangian Space
• The Galaxy Power Spectrum and Bispectrum in Redshift Space
• Eulerian BAO Reconstructions and N-Point Statistics
• Reconstructing the Initial Density Field of the Local Universe: Method and Test with Mock Catalogs
• Reconstruction in Fourier space
• Beyond LIMD bias: a measurement of the complete set of third-order halo bias parameters
• On the reach of perturbative descriptions for dark matter displacement fields
• Cosmological Reconstruction From Galaxy Light: Neural Network Based Light-Matter Connection
• Systematic Renormalization of the Effective Theory of Large Scale Structure
• Towards a self-consistent halo model for the nonlinear large-scale structure
• Verifying the consistency relation for the scale-dependent bias from local primordial non-Gaussianity
• Towards an Optimal Reconstruction of Baryon Oscillations
• Bayesian inference of cosmic density fields from non-linear, scale-dependent, and stochastic biased tracers
• An iterative reconstruction of cosmological initial density fields
• Methods for Bayesian power spectrum inference with galaxy surveys
• Isobaric Reconstruction of the Baryonic Acoustic Oscillation
• N-point Statistics of Large-Scale Structure in the Zel'dovich Approximation

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