Wavelet Moments for Cosmological Parameter Estimation

Abstract

Extracting non-Gaussian information from the non-linear regime of structure formation is key to fully exploiting the rich data from upcoming cosmological surveys probing the large-scale structure of the universe. However, due to theoretical and computational complexities, this remains one of the main challenges in analyzing observational data. We present a set of summary statistics for cosmological matter fields based on 3D wavelets to tackle this challenge. These statistics are computed as the spatial average of the complex modulus of the 3D wavelet transform raised to a power $q$ and are therefore known as invariant wavelet moments. The 3D wavelets are constructed to be radially band-limited and separable on a spherical polar grid and come in three types: isotropic, oriented, and harmonic. In the Fisher forecast framework, we evaluate the performance of these summary statistics on matter fields from the Quijote suite, where they are shown to reach state-of-the-art parameter constraints on the base $\Lambda$CDM parameters, as well as the sum of neutrino masses. We show that we can improve constraints by a factor 5 to 10 in all parameters with respect to the power spectrum baseline.

References in corpus (39)

• The DESI Experiment Part I: Science,Targeting, and Survey Design
• Karhunen-Loeve eigenvalue problems in cosmology: how should we tackle large data sets?
• Global analysis of three-flavour neutrino oscillations: synergies and tensions in the determination of theta_23, delta_CP, and the mass ordering
• Deep Scattering Spectrum
• Status of neutrino oscillations 2018: first hint for normal mass ordering and improved CP sensitivity
• Hyper-Kamiokande Design Report
• The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: RSD measurement from the power spectrum and bispectrum of the DR12 BOSS galaxies
• The Quijote simulations
• Cosmology and the Bispectrum
• Cosmology with massive neutrinos II: on the universality of the halo mass function and bias
• The Bispectrum: From Theory to Observations
• A new approach to observational cosmology using the scattering transform
• Non-Gaussian information from weak lensing data via deep learning
• Towards an Optimal Estimation of Cosmological Parameters with the Wavelet Scattering Transform
• Fisher for complements: Extracting cosmology and neutrino mass from the counts-in-cells PDF
• Constraining $M_{\nu }$ with the Bispectrum II: The Total Information Content of the Galaxy Bispectrum
• Using the Marked Power Spectrum to Detect the Signature of Neutrinos in Large-Scale Structure
• Generalized massive optimal data compression
• New Interpretable Statistics for Large Scale Structure Analysis and Generation
• Near optimal bispectrum estimators for large-scale structure
• Joint Time-Frequency Scattering
• Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA
• Fewer Mocks and Less Noise: Reducing the Dimensionality of Cosmological Observables with Subspace Projections
• Weak lensing scattering transform: dark energy and neutrino mass sensitivity
• Identifying Reionization Sources from 21cm Maps using Convolutional Neural Networks
• Enhancing BOSS bispectrum cosmological constraints with maximal compression
• Cosmological cross-correlations and nearest neighbor distributions
• Prospects for Measurement of the Neutrino Mass Hierarchy
• Constraining the reionization history using deep learning from 21cm tomography with the Square Kilometre Array
• A Robust Measure of Cosmic Structure beyond the Power-Spectrum: Cosmic Filaments and the Temperature of Dark Matter
• Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints
• Deep convolutional networks on the pitch spiral for musical instrument recognition
• Beyond two-point statistics: using the minimum spanning tree as a tool for cosmology
• Precise and Accurate Cosmology with CMBxLSS Power Spectra and Bispectra
• Universal Non-Gaussian Initial Conditions for N-body Simulations
• HInet: Generating neutral hydrogen from dark matter with neural networks
• Multifield Cosmology with Artificial Intelligence
• Extreme data compression while searching for new physics
• Position-dependent power spectrum: a new observable in the large-scale structure

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• Cosmology with Persistent Homology: a Fisher Forecast
• Wavelet Based Statistics for Enhanced 21cm EoR Parameter Constraints
• Towards unveiling the large-scale nature of gravity with the wavelet scattering transform
• Hitting the mark: Optimising Marked Power Spectra for Cosmology
• An Analytically Tractable Marked Power Spectrum
• 3D ScatterNet: Inference from 21 cm Light-cones
• Cosmology with Persistent Homology: Parameter Inference via Machine Learning
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