Methods for Bayesian power spectrum inference with galaxy surveys

Abstract

We derive and implement a full Bayesian large scale structure inference method aiming at precision recovery of the cosmological power spectrum from galaxy redshift surveys. Our approach improves over previous Bayesian methods by performing a joint inference of the three dimensional density field, the cosmological power spectrum, luminosity dependent galaxy biases and corresponding normalizations. We account for all joint and correlated uncertainties between all inferred quantities. Classes of galaxies with different biases are treated as separate sub samples. The method therefore also allows the combined analysis of more than one galaxy survey. In particular, it solves the problem of inferring the power spectrum from galaxy surveys with non-trivial survey geometries by exploring the joint posterior distribution with efficient implementations of multiple block Markov chain and Hybrid Monte Carlo methods. Our Markov sampler achieves high statistical efficiency in low signal to noise regimes by using a deterministic reversible jump algorithm. We test our method on an artificial mock galaxy survey, emulating characteristic features of the Sloan Digital Sky Survey data release 7, such as its survey geometry and luminosity dependent biases. These tests demonstrate the numerical feasibility of our large scale Bayesian inference frame work when the parameter space has millions of dimensions. The method reveals and correctly treats the anti-correlation between bias amplitudes and power spectrum, which are not taken into account in current approaches to power spectrum estimation, a 20 percent effect across large ranges in k-space. In addition, the method results in constrained realizations of density fields obtained without assuming the power spectrum or bias parameters in advance.

References in corpus (7)

• The shape of the SDSS DR5 galaxy power spectrum
• Methods for Rapidly Processing Angular Masks of Next-Generation Galaxy Surveys
• Reconstructed Density and Velocity Fields from the 2MASS Redshift Survey
• Bayesian reconstruction of the cosmological large-scale structure: methodology, inverse algorithms and numerical optimization
• Estimation of Polarized Power Spectra by Gibbs sampling
• Fast optimal CMB power spectrum estimation with Hamiltonian sampling
• The galaxy power spectrum: precision cosmology from large scale structure?

Cited by in corpus (42)

• Weak lensing for precision cosmology
• Physical Bayesian modelling of the non-linear matter distribution: new insights into the Nearby Universe
• Past and present cosmic structure in the SDSS DR7 main sample
• Unmasking the Masked Universe: the 2M++ catalogue through Bayesian eyes
• Hierarchical Cosmic Shear Power Spectrum Inference
• A rigorous EFT-based forward model for large-scale structure
• The Denoised, Deconvolved, and Decomposed Fermi $\gamma$-ray sky - An application of the D${}^3$PO algorithm
• Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference
• Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys
• Cosmological inference from Bayesian forward modelling of deep galaxy redshift surveys
• Bayesian 3d velocity field reconstruction with VIRBIuS
• Dark matter voids in the SDSS galaxy survey
• Bayesian inference of CMB gravitational lensing
• D${}^3$PO - Denoising, Deconvolving, and Decomposing Photon Observations
• Matrix-free Large Scale Bayesian inference in cosmology
• The VIMOS Public Extragalactic Redshift Survey (VIPERS): Reconstruction of the redshift-space galaxy density field
• NECOLA: Towards a Universal Field-level Cosmological Emulator
• A map-based method for eliminating systematic modes from galaxy clustering power spectra with application to BOSS
• Bayesian estimation of our local motion from the Planck-2018 CMB temperature map
• Exploring the posterior surface of the large scale structure reconstruction
• Truthing the stretch: Non-perturbative cosmological realizations with multiscale spherical collapse
• Primordial power spectrum and cosmology from black-box galaxy surveys
• Bayesian power-spectrum inference with foreground and target contamination treatment
• Disentangling Overlapping Astronomical Sources using Spatial and Spectral Information
• Detecting Unspecified Structure in Low-Count Images
• Joint Bayesian analysis of large angular scale CMB temperature anomalies
• Blasting away a dwarf galaxy: The "tail" of ESO 324-G024
• Estimating the Integrated Bispectrum from Weak Lensing Maps
• Denoising, deconvolving and decomposing multi-domain photon observations- The D4PO algorithm
• Cosmic Cartography: Bayesian reconstruction of the galaxy density informed by large-scale structure
• Cosmological Parameters from CMB Maps without Likelihood Approximation
• Optimal and fast E/B separation with a dual messenger field
• Choose to smooth: Gaussian streaming with the truncated Zel'dovich approximation
• The cosmic spiderweb: equivalence of cosmic, architectural, and origami tessellations
• Two-point statistics without bins: A continuous-function generalization of the correlation function estimator for large-scale structure
• Dynamic system classifier
• Joint constraints on galaxy bias and ${\sigma }_8$ through the N-pdf of the galaxy number density
• A probabilistic framework for cosmological inference of peculiar velocities
• Bayesian large-scale structure inference: initial conditions and the cosmic web
• Bayesian inference methodology to characterize the dust emissivity at far-infrared and submillimeter frequencies
• Halo detection via large-scale Bayesian inference
• Bayesian inference of the initial conditions from large-scale structure surveys