Almanac: MCMC-based signal extraction of power spectra and maps on the sphere
arXiv:2305.16134 · doi:10.21105/astro.2305.16134
Abstract
Inference in cosmology often starts with noisy observations of random fields on the celestial sphere, such as maps of the microwave background radiation, continuous maps of cosmic structure in different wavelengths, or maps of point tracers of the cosmological fields. Almanac uses Hamiltonian Monte Carlo sampling to infer the underlying all-sky noiseless maps of cosmic structures, in multiple redshift bins, together with their auto- and cross-power spectra. It can sample many millions of parameters, handling the highly variable signal-to-noise of typical cosmological signals, and it provides science-ready posterior data products. In the case of spin-weight 2 fields, Almanac infers - and -mode power spectra and parity-violating power, and, by sampling the full posteriors rather than point estimates, it avoids the problem of -leakage. For theories with no -mode signal, inferred non-zero -mode power may be a useful diagnostic of systematic errors or an indication of new physics. Almanac's aim is to characterise the statistical properties of the maps, with outputs that are completely independent of the cosmological model, beyond an assumption of statistical isotropy. Inference of parameters of any particular cosmological model follows in a separate analysis stage. We demonstrate our signal extraction on a CMB-like experiment.
arXiv comment27 pages, 18 figures. v2 accepted for publication by The Open Journal of Astrophysics with minor changes. v3 no changes, missing acknowledgement added
References in corpus (58)
- Efficient Computation of CMB anisotropies in closed FRW models
- MCMC using Hamiltonian dynamics
- Weak Gravitational Lensing
- Rank-normalization, folding, and localization: An improved for assessing convergence of MCMC
- An All-Sky Analysis of Polarization in the Microwave Background
- Planck 2018 results. V. CMB power spectra and likelihoods
- Estimating the Power Spectrum of the Cosmic Microwave Background
- The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data
- Five-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Angular Power Spectra
- Bayesian physical reconstruction of initial conditions from large scale structure surveys
- Parameter inference with estimated covariance matrices
- Global, Exact Cosmic Microwave Background Data Analysis Using Gibbs Sampling
- Power spectrum estimation from high-resolution maps by Gibbs sampling
- Power Spectrum Covariance of Weak Gravitational Lensing
- Analysis of CMB polarization on an incomplete sky
- E/B decomposition of finite pixelized CMB maps
- Weak lensing analysis in three dimensions
- Lensed CMB simulation and parameter estimation
- Precision calculations of the cosmic shear power spectrum projection
- Likelihood-free inference with neural compression of DES SV weak lensing map statistics
- Fast Hamiltonian sampling for large scale structure inference
- Automatic physical inference with information maximising neural networks
- The Limits of Cosmic Shear
- Unmasking the Masked Universe: the 2M++ catalogue through Bayesian eyes
- Libsharp - spherical harmonic transforms revisited
- Cosmic Shear Cosmology Beyond 2-Point Statistics: A Combined Peak Count and Correlation Function Analysis of DES-Y1
- Hierarchical Cosmic Shear Power Spectrum Inference
- Error analysis of quadratic power spectrum estimates for CMB polarization: sampling covariance
- Estimation of Polarized Power Spectra by Gibbs sampling
- Fast optimal CMB power spectrum estimation with Hamiltonian sampling
- Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference
- The angular power spectrum of NVSS radio galaxies
- Cosmological Measurements from Angular Power Spectra Analysis of BOSS DR12 Tomography
- Cosmic Shear Covariance Matrix in CDM: Cosmology Matters
- Efficient Cosmological Parameter Estimation with Hamiltonian Monte Carlo
- Diagnosing Suboptimal Cotangent Disintegrations in Hamiltonian Monte Carlo
- KiDS & Euclid: Cosmological implications of a pseudo angular power spectrum analysis of KiDS-1000 cosmic shear tomography
- Bayesian forward modelling of cosmic shear data
- A Markov Chain Monte Carlo Algorithm for analysis of low signal-to-noise CMB data
- Cosmic Shear: Inference from Forward Models
- CMB E/B decomposition of incomplete sky: a pixel space approach
- Redshift evolution of cosmic birefringence in CMB anisotropies
- Weak Lensing with Sizes, Magnitudes and Shapes
- Bayesian analysis of the low-resolution polarized 3-year WMAP sky maps
- Beyond two-point statistics: using the minimum spanning tree as a tool for cosmology
- On the Amplitude and Stokes Parameters of a Stochastic Gravitational-Wave Background
- On the accuracy and precision of correlation functions and field-level inference in cosmology
- Methods for pixel domain correction of EB leakage
- Disentangling magnification in combined shear-clustering analyses
- Bayesian weak lensing tomography: Reconstructing the 3D large-scale distribution of matter with a lognormal prior
- Covariance matrices for galaxy cluster weak lensing: from virial regime to uncorrelated large-scale structure
- BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
- Almanac: Weak Lensing power spectra and map inference on the masked sphere
- Field-level inference of cosmic shear with intrinsic alignments and baryons
- The Information Content of Projected Galaxy Fields
- Euclid: Covariance of weak lensing pseudo- estimates. Calculation, comparison to simulations, and dependence on survey geometry
- KaRMMa 2.0 -- Kappa Reconstruction for Mass Mapping
- Map-based cosmology inference with lognormal cosmic shear maps