Do dark matter halos explain lensing peaks?
arXiv:1609.03973 · doi:10.1103/PhysRevD.94.083506
Abstract
We have investigated a recently proposed halo-based model, Camelus, for predicting weak-lensing peak counts, and compared its results over a collection of 162 cosmologies with those from N-body simulations. While counts from both models agree for peaks with (where is the ratio of the peak height to the r.m.s. shape noise), we find fewer counts for peaks near and significantly higher counts in the negative tail. Adding shape noise reduces the differences to within for all cosmologies. We also found larger covariances that are more sensitive to cosmological parameters. As a result, credibility regions in the are larger. Even though the credible contours are commensurate, each model draws its predictive power from different types of peaks. Low peaks, especially those with , convey important cosmological information in N-body data, as shown in \cite{DietrichHartlap, Kratochvil2010}, but \textsc{Camelus} constrains cosmology almost exclusively from high significance peaks . Our results confirm the importance of using a cosmology-dependent covariance with at least a 14\% improvement in parameter constraints. We identified the covariance estimation as the main driver behind differences in inference, and suggest possible ways to make Camelus even more useful as a highly accurate peak count emulator.
References in corpus (38)
- A Universal Density Profile from Hierarchical Clustering
- The cosmological simulation code GADGET-2
- Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Parameter Results
- Weak Gravitational Lensing
- Mass function of dark matter halos
- Observational Probes of Cosmic Acceleration
- Ahf: Amiga's Halo Finder
- Why your model parameter confidences might be too optimistic -- unbiased estimation of the inverse covariance matrix
- Cosmology with cosmic shear observations: a review
- Weak Gravitational Lensing by Large-Scale Structure
- Sample Variance Considerations for Cluster Surveys
- Parameter inference with estimated covariance matrices
- The Three-Point Correlation Function in Cosmology
- Cosmology with the shear-peak statistics
- Searching for massive clusters in weak lensing surveys
- Cosmology Constraints from the Weak Lensing Peak Counts and the Power Spectrum in CFHTLenS
- Probing Cosmology with Weak Lensing Peak Counts
- Noise properties of gravitational lens mass reconstruction
- Probing Cosmology with Weak Lensing Minkowski Functionals
- Statistics of Dark Matter Halos from Gravitational Lensing
- Emulating the CFHTLenS Weak Lensing data: Cosmological Constraints from moments and Minkowski functionals
- Completeness in Weak Lensing Searches for Clusters
- Cosmological Constraints From Weak Lensing Peak Statistics With CFHT Stripe 82 Survey
- Shear Selected Cluster Cosmology I: Tomography and Optimal Filtering
- Cosmological Information in Weak Lensing Peaks
- Weighing the Cosmological Energy Contents with Weak Gravitational Lensing
- Noisy weak-lensing convergence peak statistics near clusters of galaxies and beyond
- A new model to predict weak-lensing peak counts II. Parameter constraint strategies
- A new model to predict weak-lensing peak counts I. Comparison with -body Simulations
- The three-point correlation function of cosmic shear. II: Relation to the bispectrum of the projected mass density and generalized third-order aperture measures
- An analytic approach to number counts of weak-lensing peak detections
- A new stochastic approach to cumulative weak lensing
- Mocking the Weak Lensing universe: the LensTools python computing package
- Baryon impact on weak lensing peaks and power spectrum: low-bias statistics and self-calibration in future surveys
- Optimized detection of shear peaks in weak lensing maps
- The Origin of Weak Lensing Convergence Peaks
- Sample variance in weak lensing: how many simulations are required?
- Extreme value statistics of weak lensing shear peak counts
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- 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
- Weak lensing cosmology with convolutional neural networks on noisy data
- Weak Lensing Light-Cones in Modified Gravity simulations with and without Massive Neutrinos
- Weak lensing scattering transform: dark energy and neutrino mass sensitivity
- Cosmological constraints with weak lensing peak counts and second-order statistics in a large-field survey
- Probing dark energy with tomographic weak-lensing aperture mass statistics
- CosmoGridV1: a simulated CDM theory prediction for map-level cosmological inference
- Fast Weak Lensing Simulations with Halo Model
- Weak Lensing Peaks in Simulated Light-Cones: Investigating the Coupling between Dark Matter and Dark Energy
- Investigating Cosmological GAN Emulators Using Latent Space Interpolation
- Statistical connection of peak counts to power spectrum and moments in weak lensing field
- The self similarity of weak lensing peaks
- Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables
- Scattering Spectra Models for Physics
- Geometry and growth contributions to cosmic shear observables
- Cosmological Constraints from Weak Lensing Peaks: Can Halo Models Accurately Predict Peak Counts?
- Projection effects of large-scale structures on weak-lensing peak abundances
- Wavelet Conditional Renormalization Group
- The Impact of Photometric Redshift Errors on Lensing Statistics in Ray-Tracing Simulations
- Constraining cosmology with thermal Sunyaev-Zel'dovich maps: Minkowski functionals, peaks, minima, and moments
- Peaks in weak lensing mass maps for cluster astrophysics and cosmology
- An improved cosmological parameter inference scheme motivated by deep learning
- Testing and Emulating Modified Gravity on Cosmological Scales
- Conditionally Strongly Log-Concave Generative Models