Cosmology Constraints from the Weak Lensing Peak Counts and the Power Spectrum in CFHTLenS

Abstract

Lensing peaks have been proposed as a useful statistic, containing cosmological information from non-Gaussianities that is inaccessible from traditional two-point statistics such as the power spectrum or two-point correlation functions. Here we examine constraints on cosmological parameters from weak lensing peak counts, using the publicly available data from the 154 deg${}^2$ CFHTLenS survey. We utilize a new suite of ray-tracing N-body simulations on a grid of 91 cosmological models, covering broad ranges of the three parameters ${\Omega }_m$, ${\sigma }_8$, and $w$, and replicating the Galaxy sky positions, redshifts, and shape noise in the CFHTLenS observations. We then build an emulator that interpolates the power spectrum and the peak counts to an accuracy of $\le 5\%$, and compute the likelihood in the three-dimensional parameter space (${\Omega }_m$, ${\sigma }_8$, $w$) from both observables. We find that constraints from peak counts are comparable to those from the power spectrum, and somewhat tighter when different smoothing scales are combined. Neither observable can constrain $w$ without external data. When the power spectrum and peak counts are combined, the area of the error "banana'' in the (${\Omega }_m$, ${\sigma }_8$) plane reduces by a factor of $\approx 2$, compared to using the power spectrum alone. For a flat $\Lambda$ cold dark matter model, combining both statistics, we obtain the constraint ${\sigma }_8({\Omega }_m/0.27{)}^{0.63}=0.85\begin{array}{c}+0.03\\ -0.03\end{array}$.

15 pages, 14 figures. The manuscript has been revised and matches published version

References in corpus (4)

• Cosmology and the Bispectrum
• CFHTLenS: Cosmological constraints from a combination of cosmic shear two-point and three-point correlations
• Probing dark energy with cluster counts and cosmic shear power spectra: including the full covariance
• Statistical and Systematic Errors in Measurement of Weak-Lensing Minkowski Functionals: Application to Canada-France-Hawaii Lensing Survey

Cited by in corpus (123)

• Cosmology with cosmic shear observations: a review
• An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models
• Dark energy two decades after: Observables, probes, consistency tests
• The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics
• Large-scale dark matter simulations
• Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data
• A new approach to observational cosmology using the scattering transform
• KiDS-450: Cosmological Constraints from Weak Lensing Peak Statistics - II: Inference from Shear Peaks using N-body Simulations
• Non-Gaussian information from weak lensing data via deep learning
• MassiveNuS: Cosmological Massive Neutrino Simulations
• CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial 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
• Dark Energy Survey Year 3 results: curved-sky weak lensing mass map reconstruction
• Detecting Neutrino Mass by Combining Matter Clustering, Halos, and Voids
• Constraining $f(R)$ Gravity Theory Using Weak Lensing Peak Statistics from the Canada-France-Hawaii-Telescope Lensing Survey
• Cosmological constraints from noisy convergence maps through deep learning
• Cosmic Shear Cosmology Beyond 2-Point Statistics: A Combined Peak Count and Correlation Function Analysis of DES-Y1
• Constraining neutrino mass with tomographic weak lensing one-point probability distribution function and power spectrum
• Cosmological Simulations for Combined-Probe Analyses: Covariance and Neighbour-Exclusion Bias
• A new model to predict weak-lensing peak counts II. Parameter constraint strategies
• Cross-correlation of Planck CMB Lensing and CFHTLenS Galaxy Weak Lensing Maps
• Bayesian emulator optimisation for cosmology: application to the Lyman-alpha forest
• Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps -- validation on simulations
• Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys
• Constraining Neutrino Mass with the Tomographic Weak Lensing Bispectrum
• Studying galaxy troughs and ridges using Weak Gravitational Lensing with the Kilo-Degree Survey
• Constraining neutrino mass with tomographic weak lensing peak counts
• Weak lensing scattering transform: dark energy and neutrino mass sensitivity
• A large sample of shear selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S16A wide field mass maps
• Cosmic Shear Covariance Matrix in $w$CDM: Cosmology Matters
• Mocking the Weak Lensing universe: the LensTools python computing package
• On the road to percent accuracy II: calibration of the non-linear matter power spectrum for arbitrary cosmologies
• A Full $w$CDM Analysis of KiDS-1000 Weak Lensing Maps using Deep Learning
• Lifting weak lensing degeneracies with a field-based likelihood
• CMB Lensing Beyond the Power Spectrum: Cosmological Constraints from the One-Point PDF and Peak Counts
• The Origin of Weak Lensing Convergence Peaks
• Cosmological constraints with weak lensing peak counts and second-order statistics in a large-field survey
• Mitigating contamination in LSS surveys: a comparison of methods
• Cosmological constraints from Subaru weak lensing cluster counts
• Interpreting deep learning models for weak lensing
• Weak Lensing Minima and Peaks: Cosmological Constraints and the Impact of Baryons
• Cosmological constraints from the convergence 1-point probability distribution
• The Accuracy of Weak Lensing Simulations
• General framework for cosmological dark matter bounds using $N$-body simulations
• Bayesian forward modelling of cosmic shear data
• $\kappa$TNG: Effect of Baryonic Processes on Weak Lensing with IllustrisTNG Simulations
• Probabilistic Mass Mapping with Neural Score Estimation
• Cosmological test of gravity using weak lensing voids
• Probing dark energy with tomographic weak-lensing aperture mass statistics
• Constraining cosmology with weak lensing voids
• Cosmological parameter estimation via iterative emulation of likelihoods
• Effects of baryons on weak lensing peak statistics
• Constraining Multiplicative Bias in CFHTLenS Weak Lensing Shear Data
• CosmoGridV1: a simulated $w$CDM theory prediction for map-level cosmological inference
• Machine Learning for Observational Cosmology
• Euclid: Reconstruction of Weak Lensing mass maps for non-Gaussianity studies
• The imprint of $f(R)$ gravity on weak gravitational lensing II : Information content in cosmic shear statistics
• Do dark matter halos explain lensing peaks?
• A new model to predict weak-lensing peak counts III. Filtering technique comparisons
• Cosmological constraints from HSC survey first-year data using deep learning
• Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data
• Simultaneously constraining cosmology and baryonic physics via deep learning from weak lensing
• Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes
• Cosmology with photometric weak lensing surveys: constraints with redshift tomography of convergence peaks and moments
• Hundreds of weak lensing shear-selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S19A data
• Weak lensing peak statistics in the era of large scale cosmological surveys
• Starlet l1-norm for weak lensing cosmology
• Bayesian weak lensing tomography: Reconstructing the 3D large-scale distribution of matter with a lognormal prior
• Consistency of cosmic shear analyses in harmonic and real space
• Joint velocity and density reconstruction of the Universe with nonlinear differentiable forward modeling
• RAY-RAMSES: a code for ray tracing on the fly in N-body simulations
• Cosmological Studies from HSC-SSP Tomographic Weak Lensing Peak Abundances
• Enhancing cosmic shear with the multi-scale lensing PDF
• Statistical connection of peak counts to power spectrum and moments in weak lensing field
• Towards a full $w$CDM map-based analysis for weak lensing surveys
• Super-sample covariance of the power spectrum, bispectrum, halos, voids, and their cross covariances
• Minkowski Functionals in Joint Galaxy Clustering & Weak Lensing Analyses
• The self similarity of weak lensing peaks
• Geometry and growth contributions to cosmic shear observables
• Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables
• Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering
• Effects of galaxy intrinsic alignment on weak lensing peak statistics
• Optimal void finders in weak lensing maps
• Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations
• Fast generation of weak lensing maps by the inverse-Gaussianization method
• The FLAMINGO project: Baryonic impact on weak gravitational lensing convergence peak counts
• UNIONS: The impact of systematic errors on weak-lensing peak counts
• Accurate field-level weak lensing inference for precision cosmology
• Quantifying systematics from the shear inversion on weak-lensing peak counts
• Forecasting the power of Higher Order Weak Lensing Statistics with automatically differentiable simulations
• The statistics of peaks of weakly non-Gaussian random fields: Effects of bispectrum in two- and three-dimensions
• Projection effects of large-scale structures on weak-lensing peak abundances
• Simulation-Based Inference Benchmark for Weak Lensing Cosmology
• Impact of baryonic feedback on HSC Y1 weak lensing non-Gaussian statistics
• Cosmological studies from tomographic weak lensing peak abundances and impacts of photo-z errors
• The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST
• The Weak Lensing Peak Statistics in the Mocks by the inverse-Gaussianization Method
• Stage IV baryonic feedback correction for non-Gaussianity inference
• Probabilistic Cosmological Mass Mapping from Weak Lensing Shear
• The Impact of Photometric Redshift Errors on Lensing Statistics in Ray-Tracing Simulations
• Weak-lensing tunnel voids in simulated light cones: A new pipeline to investigate modified gravity and massive neutrinos signatures
• Starlet higher order statistics for galaxy clustering and weak lensing
• Accurate Kappa Reconstruction Algorithm for masked shear catalog (AKRA)
• The FLAMINGO project: cosmology with the redshift dependence of weak gravitational lensing peaks
• The matter fluctuation amplitude inferred from the weak lensing power spectrum and correlation function in CFHTLenS data
• Reconstruction of weak lensing mass maps for non-Gaussian studies in the celestial sphere
• Generative modelling for mass-mapping with fast uncertainty quantification
• Constraining cosmology with thermal Sunyaev-Zel'dovich maps: Minkowski functionals, peaks, minima, and moments
• Cosmological constraints from HSC Y1 lensing convergence PDF
• Peaks in weak lensing mass maps for cluster astrophysics and cosmology
• Machine learning uncovers new cosmological information
• Weak lensing peak statistics -- steepness versus height
• A Minkowski Functional Analysis of the Cosmic Microwave Background Weak Lensing Convergence
• Neural style transfer of weak lensing mass maps
• Numerical investigation of non-Gaussianities in the phase and modulus of density Fourier modes
• An improved cosmological parameter inference scheme motivated by deep learning
• Distribution-free uncertainty quantification for inverse problems: application to weak lensing mass mapping
• A Hamiltonian, post-Born, three-dimensional, on-the-fly ray tracing algorithm for gravitational lensing
• Cosmic shear beyond 2-point statistics: Accounting for galaxy intrinsic alignment with projected tidal fields
• Generative modeling of convergence maps based on predicted one-point statistics
• Neural network emulator to constrain the high-$z$ IGM thermal state from Lyman-$\alpha$ forest flux auto-correlation function