A Full $w$CDM Analysis of KiDS-1000 Weak Lensing Maps using Deep Learning

Abstract

We present a full forward-modeled $w$CDM analysis of the KiDS-1000 weak lensing maps using graph-convolutional neural networks (GCNN). Utilizing the $\text{CosmoGrid}$, a novel massive simulation suite spanning six different cosmological parameters, we generate almost one million tomographic mock surveys on the sphere. Due to the large data set size and survey area, we perform a spherical analysis while limiting our map resolution to $\text{HEALPix}$ $n_{\mathrm{side}}=512$. We marginalize over systematics such as photometric redshift errors, multiplicative calibration and additive shear bias. Furthermore, we use a map-level implementation of the non-linear intrinsic alignment model along with a novel treatment of baryonic feedback to incorporate additional astrophysical nuisance parameters. We also perform a spherical power spectrum analysis for comparison. The constraints of the cosmological parameters are generated using a likelihood free inference method called Gaussian Process Approximate Bayesian Computation (GPABC). Finally, we check that our pipeline is robust against choices of the simulation parameters. We find constraints on the degeneracy parameter of $S_8\equiv {\sigma }_8\sqrt{{\Omega }_M/0.3}=0.78_{-0.06}^{+0.06}$ for our power spectrum analysis and $S_8=0.79_{-0.05}^{+0.05}$ for our GCNN analysis, improving the former by 16%. This is consistent with earlier analyses of the 2-point function, albeit slightly higher. Baryonic corrections generally broaden the constraints on the degeneracy parameter by about 10%. These results offer great prospects for full machine learning based analyses of on-going and future weak lensing surveys.

arXiv comment22 pages, 13 figures

References in corpus (58)

• emcee: The MCMC Hammer
• HEALPix -- a Framework for High Resolution Discretization, and Fast Analysis of Data Distributed on the Sphere
• Bayesian photometric redshift estimation
• Ahf: Amiga's Halo Finder
• KiDS-1000 Cosmology: Cosmic shear constraints and comparison between two point statistics
• Chandra Cluster Cosmology Project II: Samples and X-ray Data Reduction
• CFHTLenS tomographic weak lensing cosmological parameter constraints: Mitigating the impact of intrinsic galaxy alignments
• Intrinsic alignment-lensing interference as a contaminant of cosmic shear
• Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data
• Cosmology with cosmic shear observations: a review
• The BAHAMAS project: Calibrated hydrodynamical simulations for large-scale structure cosmology
• Dark energy constraints from cosmic shear power spectra: impact of intrinsic alignments on photometric redshift requirements
• The effects of galaxy formation on the matter power spectrum: A challenge for precision cosmology
• Bayesian Galaxy Shape Measurement for Weak Lensing Surveys - III. Application to the Canada-France-Hawaii Telescope Lensing Survey
• The evolution substructure I: a new identification method
• An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models
• CFHTLenS: The Canada-France-Hawaii Telescope Lensing Survey - Imaging Data and Catalogue Products
• Dark Energy Survey Year 3 Results: Cosmology from Cosmic Shear and Robustness to Modeling Uncertainty
• KiDS+VIKING-450: Cosmic shear tomography with optical+infrared data
• The fourth data release of the Kilo-Degree Survey: ugri imaging and nine-band optical-IR photometry over 1000 square degrees
• Galaxy Cluster Baryon Fractions Revisited
• Massive Lossless Data Compression and Multiple Parameter Estimation from Galaxy Spectra
• Constraints on intrinsic alignment contamination of weak lensing surveys using the MegaZ-LRG sample
• A new method to quantify the effects of baryons on the matter power spectrum
• Quantifying baryon effects on the matter power spectrum and the weak lensing shear correlation
• Cosmology with the shear-peak statistics
• DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
• CFHTLenS: Cosmological constraints from a combination of cosmic shear two-point and three-point correlations
• Modelling baryonic feedback for survey cosmology
• KiDS-1000 catalogue: Redshift distributions and their calibration
• Cosmology Constraints from the Weak Lensing Peak Counts and the Power Spectrum in CFHTLenS
• The Effective Number Density of Galaxies for Weak Lensing Measurements in the LSST Project
• KiDS-1000 catalogue: Weak gravitational lensing shear measurements
• Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data
• Cosmological constraints with deep learning from KiDS-450 weak lensing maps
• KiDS-450: Cosmological Constraints from Weak Lensing Peak Statistics - II: Inference from Shear Peaks using N-body Simulations
• KiDS-1000 Cosmology: constraints beyond flat $\Lambda$CDM
• Photometric Redshift Calibration with Self Organising Maps
• The XXL Survey. XIII. Baryon content of the bright cluster sample
• Automatic physical inference with information maximising neural networks
• KiDS-450: Cosmological Constraints from Weak Lensing Peak Statistics-I: Inference from Analytical Prediction of High Signal-to-Noise Ratio Convergence Peaks
• Cosmological Constraints From Weak Lensing Peak Statistics With CFHT Stripe 82 Survey
• Weak lensing cosmology with convolutional neural networks on noisy data
• Weak lensing from space: first cosmological constraints from three-point shear statistics
• Modelling the large scale structure of the Universe as a function of cosmology and baryonic physics
• Emulation of baryonic effects on the matter power spectrum and constraints from galaxy cluster data
• Cosmological constraints from noisy convergence maps through deep learning
• Painting with baryons: augmenting N-body simulations with gas using deep generative models
• KiDS+VIKING-450: Improved cosmological parameter constraints from redshift calibration with self-organising maps
• On the validity of the Born approximation for beyond-Gaussian weak lensing observables
• Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys
• $\nu \mathrm{CO}N\mathrm{CEPT}$: Cosmological neutrino simulations from the non-linear Boltzmann hierarchy
• Fully relativistic treatment of light neutrinos in $N$-body simulations
• The Impact of Baryons on Cosmological Inference from Weak Lensing Statistics
• Fast Generation of Covariance Matrices for Weak Lensing
• Weak lensing peak statistics in the era of large scale cosmological surveys
• Fast Lightcones for Combined Cosmological Probes
• Cosmological Parameter Estimation and Inference using Deep Summaries

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• LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
• CosmoGridV1: a simulated $w$CDM theory prediction for map-level cosmological inference
• Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data
• Cosmological constraints from HSC survey first-year data using deep learning
• KiDS-SBI: Simulation-based inference analysis of KiDS-1000 cosmic shear
• CSST Cosmological Emulator I: Matter Power Spectrum Emulation with one percent accuracy to k = 10 h/Mpc
• A simulation-based inference pipeline for cosmic shear with the Kilo-Degree Survey
• Towards a full $w$CDM map-based analysis for weak lensing surveys
• Cosmological constraints from weak lensing scattering transform using HSC Y1 data
• Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam
• UNIONS: The impact of systematic errors on weak-lensing peak counts
• Forecasting the power of Higher Order Weak Lensing Statistics with automatically differentiable simulations
• Generative models of astrophysical fields with scattering transforms on the sphere
• Fast likelihood-free inference in the LSS Stage IV era
• Simulation-Based Inference Benchmark for Weak Lensing Cosmology
• Dark Energy Survey Year 6 Results: Cell-based Coadds and Metadetection Weak Lensing Shape Catalogue
• Baryonification extended to thermal Sunyaev Zeldovich
• Map-level baryonification: unified treatment of weak lensing two-point and higher-order statistics
• Accurately Estimating Redshifts from CSST Slitless Spectroscopic Survey using Deep Learning
• Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations
• Accurate Kappa Reconstruction Algorithm for masked shear catalog (AKRA)
• AKRA 2.0: Accurate Kappa Reconstruction Algorithm for masked shear catalog
• Hybrid summary statistics: neural weak lensing inference beyond the power spectrum
• Weak lensing peak statistics -- steepness versus height
• Cosmological constraints from HSC Y1 lensing convergence PDF
• Impact of PSF misestimation and galaxy population bias on precision shear measurement using a CNN
• $\text{SBi3PCF:}$ Simulation-based inference with the integrated 3PCF
• Interpretability of deep-learning methods applied to large-scale structure surveys
• GalSBI: Phenomenological galaxy population model for cosmology using simulation-based inference