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Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys
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Outgoing claims: the papers this work cites, builds on, or argues with.
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CosmoSIS: Modular cosmological parameter estimation
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Array programming with NumPy
inferredcites →https://doi.org/10.1038/s41592-019-0686-2openalex-snapshot
SciPy 1.0: fundamental algorithms for scientific computing in Python
inferredcites →https://doi.org/10.1046/j.1365-8711.2003.06503.xopenalex-snapshot
Stable clustering, the halo model and non-linear cosmological power spectra
inferredcites →https://doi.org/10.1051/0004-6361/200911697openalex-snapshot
The non-Gaussianity of the cosmic shear likelihood or how odd is theChandraDeep Field South?
inferredcites →https://doi.org/10.1051/0004-6361/201117284openalex-snapshot
Constrained probability distributions of correlation functions
inferredcites →https://doi.org/10.1051/0004-6361/201117294openalex-snapshot
Cosmic shear covariance: the log-normal approximation
inferredcites →https://doi.org/10.1051/0004-6361/201220538openalex-snapshot
On the assumption of Gaussianity for cosmological two-point statistics and parameter dependent covariance matrices
inferredcites →https://doi.org/10.1051/0004-6361/201321718openalex-snapshot
A quasi-Gaussian approximation for the probability distribution of correlation functions
inferredcites →https://doi.org/10.1051/0004-6361/201525906openalex-snapshot
Constrained correlation functions from the Millennium Simulation
inferredcites →https://doi.org/10.1051/0004-6361/201525906/pdfopenalex-snapshot
Constrained correlation functions from the Millennium Simulation
inferredcites →https://doi.org/10.1051/0004-6361/202038831openalex-snapshot
KiDS-1000 methodology: Modelling and inference for joint weak gravitational lensing and spectroscopic galaxy clustering analysis
inferredcites →https://doi.org/10.1051/0004-6361/202038831/pdfopenalex-snapshot
KiDS-1000 Methodology: Modelling and inference for joint weak gravitational lensing and spectroscopic galaxy clustering analysis
inferredcites →https://doi.org/10.1086/308059openalex-snapshot
Power Spectrum Correlations Induced by Nonlinear Clustering
inferredcites →https://doi.org/10.1086/309179openalex-snapshot
Efficient Computation of Cosmic Microwave Background Anisotropies in Closed Friedmann‐Robertson‐Walker Models
inferredcites →https://doi.org/10.1086/321376openalex-snapshot
Power Spectrum Covariance of Weak Gravitational Lensing
inferredcites →https://doi.org/10.1086/338126openalex-snapshot
MASTER of the Cosmic Microwave Background Anisotropy Power Spectrum: A Fast Method for Statistical Analysis of Large and Complex Cosmic Microwave Background Data Sets
inferredcites →https://doi.org/10.1086/340048openalex-snapshot
Lognormal Property of Weak‐Lensing Fields
inferredcites →https://doi.org/10.1086/427976openalex-snapshot
HEALPix: A Framework for High‐Resolution Discretization and Fast Analysis of Data Distributed on the Sphere
inferredcites →https://doi.org/10.1088/0004-637x/761/2/152openalex-snapshot
REVISING THE HALOFIT MODEL FOR THE NONLINEAR MATTER POWER SPECTRUM
inferredcites →https://doi.org/10.1088/1367-2630/9/12/446openalex-snapshot
Probing dark energy with cluster counts and cosmic shear power spectra: including the full covariance
inferredcites →https://doi.org/10.1088/1475-7516/2012/04/027openalex-snapshot
CMB power spectrum parameter degeneracies in the era of precision cosmology
inferredcites →https://doi.org/10.1088/1475-7516/2018/06/015openalex-snapshot
Complete super-sample lensing covariance in the response approach
inferredcites →https://doi.org/10.1088/1475-7516/2018/10/053openalex-snapshot
Accurate cosmic shear errors: do we need ensembles of simulations?
inferredcites →https://doi.org/10.1093/mnras/staa2948openalex-snapshot
Non-Gaussianity in the weak lensing correlation function likelihood – implications for cosmological parameter biases
inferredcites →https://doi.org/10.1093/mnras/stv1671openalex-snapshot
A fast, always positive definite and normalizable approximation of non-Gaussian likelihoods
inferredcites →https://doi.org/10.1093/mnras/stv794openalex-snapshot
Simulations of weak gravitational lensing – II. Including finite support effects in cosmic shear covariance matrices
inferredcites →https://doi.org/10.1093/mnras/stw2106openalex-snapshot
Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps
inferredcites →https://doi.org/10.1093/mnras/stw2805openalex-snapshot
KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing
inferredcites →https://doi.org/10.1093/mnras/stx2491openalex-snapshot
On the insufficiency of arbitrarily precise covariance matrices: non-Gaussian weak-lensing likelihoods
inferredcites →https://doi.org/10.1093/mnras/sty2319openalex-snapshot
Cosmological simulations for combined-probe analyses: covariance and neighbour-exclusion bias
inferredcites →https://doi.org/10.1093/mnras/sty988openalex-snapshot
The skewed weak lensing likelihood: why biases arise, despite data and theory being sound
inferredcites →https://doi.org/10.1093/mnras/stz3059openalex-snapshot
Euclid-era cosmology for everyone: Neural net assisted MCMC sampling for the joint 3x2 likelihood
inferredcites →https://doi.org/10.1093/mnras/stz3225openalex-snapshot
Exact joint likelihood of pseudo-Cℓ estimates from correlated Gaussian cosmological fields
inferredcites →https://doi.org/10.1093/pasj/psz010openalex-snapshot
Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data
inferredcites →https://doi.org/10.1103/physrevd.100.023519openalex-snapshot
Cosmic shear: Inference from forward models
inferredcites →https://doi.org/10.1103/physrevd.102.103507openalex-snapshot
Flow-based likelihoods for non-Gaussian inference
inferredcites →https://doi.org/10.1103/physrevd.65.023505openalex-snapshot
Analysis of CMB polarization on an incomplete sky
inferredcites →https://doi.org/10.1103/physrevd.77.103013openalex-snapshot
Likelihood analysis of CMB temperature and polarization power spectra
inferredcites →https://doi.org/10.1103/physrevd.83.023501openalex-snapshot
Copula cosmology: Constructing a likelihood function
inferredcites →https://doi.org/10.1103/physrevd.87.123504openalex-snapshot
Power spectrum super-sample covariance
inferredcites →https://doi.org/10.1103/physrevd.89.083519openalex-snapshot
Super-sample covariance in simulations
inferredcites →https://doi.org/10.1103/physrevd.98.043528openalex-snapshot
Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear
inferredcites →https://doi.org/10.1103/physreve.69.066138openalex-snapshot
Estimating mutual information
inferredcites →https://doi.org/10.1103/physrevlett.105.251301openalex-snapshot
Precise Estimation of Cosmological Parameters Using a More Accurate Likelihood Function
inferredcites →https://doi.org/10.1109/mcse.2007.55openalex-snapshot
Matplotlib: A 2D Graphics Environment
inferredcites →https://doi.org/10.1111/j.1365-2966.2005.09111.xopenalex-snapshot
Cosmic microwave background temperature and polarization pseudo-Cℓestimators and covariances
inferredcites →https://doi.org/10.1111/j.1365-2966.2006.10910.xopenalex-snapshot
Likelihood techniques for the combined analysis of CMB temperature and polarization power spectra
inferredcites →https://doi.org/10.1111/j.1365-2966.2009.15202.xopenalex-snapshot
TEASING: a fast and accurate approximation for the low multipole likelihood of the cosmic microwave background temperature
inferredcites →https://doi.org/10.17863/cam.64134openalex-snapshot
SciPy 1.0: fundamental algorithms for scientific computing in Python
inferredcites →https://doi.org/10.21105/astro.2007.07253openalex-snapshot
The impact of signal-to-noise, redshift, and angular range on the bias of weak lensing 2-point functions
inferredcites →https://doi.org/10.21105/joss.01298openalex-snapshot
healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python
inferredcites →https://doi.org/10.2307/2346290openalex-snapshot
Algorithm AS 53: Wishart Variate Generator
inferredcites →https://doi.org/10.3847/1538-4357/ab042copenalex-snapshot
LSST: From Science Drivers to Reference Design and Anticipated Data Products
inferredcites →https://doi.org/10.48550/arxiv.1110.3193openalex-snapshot
Euclid Definition Study Report
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← backgroundhttps://doi.org/10.5281/zenodo.4316733zenodo-depositor-declared
Data accompanying arXiv:2012.06267
inferred← citeshttps://doi.org/10.1051/0004-6361/202142052openalex-snapshot
Impact of survey geometry and super-sample covariance on future photometric galaxy surveys
inferred← citeshttps://doi.org/10.1051/0004-6361/202142481openalex-snapshot
KiDS andEuclid: Cosmological implications of a pseudo angular power spectrum analysis of KiDS-1000 cosmic shear tomography
inferred← citeshttps://doi.org/10.1051/0004-6361/202142908openalex-snapshot
Euclid: Covariance of weak lensing pseudo-Cℓ estimates
inferred← citeshttps://doi.org/10.1051/0004-6361/202347164openalex-snapshot
Cosmological inference including massive neutrinos from the matter power spectrum: Biases induced by uncertainties in the covariance matrix
inferred← citeshttps://doi.org/10.1051/0004-6361/202450487openalex-snapshot
KiDS-SBI: Simulation-based inference analysis of KiDS-1000 cosmic shear
inferred← citeshttps://doi.org/10.1051/0004-6361/202553742openalex-snapshot
Euclid : Optimising tomographic redshift binning for 3 × 2 pt power spectrum constraints on dark energy
inferred← citeshttps://doi.org/10.1088/1475-7516/2022/04/003openalex-snapshot
Characterization of the polarized synchrotron emission from Planck and WMAP data
inferred← citeshttps://doi.org/10.1088/2632-2153/acc444openalex-snapshot
A robust estimator of mutual information for deep learning interpretability
inferred← citeshttps://doi.org/10.1093/mnras/stac1809openalex-snapshot
On cosmological bias due to the magnification of shear and position samples in modern weak lensing analyses
inferred← citeshttps://doi.org/10.1093/mnras/stad2262openalex-snapshot
A simulation-based inference pipeline for cosmic shear with the Kilo-Degree Survey
inferred← citeshttps://doi.org/10.1093/mnras/stad3646openalex-snapshot
Data compression and inference in cosmology with self-supervised machine learning
inferred← citeshttps://doi.org/10.1093/mnras/staf113openalex-snapshot
Mitigating baryon feedback bias in cosmic shear through a theoretical error covariance in the matter power spectrum
inferred← citeshttps://doi.org/10.1093/mnrasl/slab081openalex-snapshot
On the accuracy and precision of correlation functions and field-level inference in cosmology
inferred← citeshttps://doi.org/10.1103/physrevd.104.083527openalex-snapshot
Constraining f(R) gravity with a k -cut cosmic shear analysis of the Hyper Suprime-Cam first-year data
inferred← citeshttps://doi.org/10.1103/physrevd.107.043516openalex-snapshot
Position-dependent correlation function of weak-lensing convergence
inferred← citeshttps://doi.org/10.3847/1538-4357/aea08copenalex-snapshot
Recovering Subtle Cosmological Information with the Zel’dovich-inspired Transform
inferred← citeshttps://doi.org/10.3847/1538-4365/ad8ebdopenalex-snapshot
Data-space Validation of High-dimensional Models by Comparing Sample Quantiles
inferred← citeshttps://doi.org/10.70675/00dab43dz7cfdz4b8fzafb1z5c4e48cea974openalex-snapshot
Optimal inference of cosmological parameters in preparation of the Euclid survey
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