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Title: Cosmology with photometric weak lensing surveys: Constraints with redshift tomography of convergence peaks and moments

Journal Article · · Physical Review D
 [1];  [2];  [3]
  1. Columbia Univ., New York, NY (United States). Dept. of Physics; Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Physics
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Physics
  3. Columbia Univ., New York, NY (United States). Dept. of Astronomy
+ Show Author Affiliations

Weak gravitational lensing is becoming a mature technique for constraining cosmological parameters, and future surveys will be able to constrain the dark energy equation of state w. When analyzing galaxy surveys, redshift information has proven to be a valuable addition to angular shear correlations. We forecast parameter constraints on the triplet (Ωm,w,σ8) for a LSST-like photometric galaxy survey, using tomography of the shear-shear power spectrum, convergence peak counts and higher convergence moments. Here we find that redshift tomography with the power spectrum reduces the area of the 1σ confidence interval in (Ωm,w) space by a factor of 8 with respect to the case of the single highest redshift bin. We also find that adding non-Gaussian information from the peak counts and higher-order moments of the convergence field and its spatial derivatives further reduces the constrained area in (Ωm,w) by factors of 3 and 4, respectively. When we add cosmic microwave background parameter priors from Planck to our analysis, tomography improves power spectrum constraints by a factor of 3. Adding moments yields an improvement by an additional factor of 2, and adding both moments and peaks improves by almost a factor of 3 over power spectrum tomography alone. We evaluate the effect of uncorrected systematic photometric redshift errors on the parameter constraints. In conclusion, we find that different statistics lead to different bias directions in parameter space, suggesting the possibility of eliminating this bias via self-calibration.

Research Organization:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
SC0012704; ACI-1053575; AST-1210877; SC00112704
OSTI ID:
1336177
Alternate ID(s):
OSTI ID: 1327931
Report Number(s):
BNL-113176-2016-JA; PRVDAQ; KA2301020
Journal Information:
Physical Review D, Vol. 94, Issue 6; ISSN 2470-0010
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 23 works
Citation information provided by
Web of Science

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Cited By (14)

Weak lensing peak statistics in the era of large scale cosmological surveys journal October 2018
Constraining neutrino mass with weak lensing Minkowski Functionals journal June 2019
A nulling strategy for modelling lensing convergence in cones with large deviation theory journal January 2020
KiDS-450: cosmological constraints from weak-lensing peak statistics – II: Inference from shear peaks using N-body simulations journal October 2017
Weak lensing cosmology with convolutional neural networks on noisy data journal September 2019
Full-sky Gravitational Lensing Simulation for Large-area Galaxy Surveys and Cosmic Microwave Background Experiments journal November 2017
LSST: From Science Drivers to Reference Design and Anticipated Data Products journal March 2019
Cosmological Studies from Tomographic Weak Lensing Peak Abundances and Impacts of Photo- z Errors journal October 2019
LSST: from Science Drivers to Reference Design and Anticipated Data Products text January 2008
Full-sky Gravitational Lensing Simulation for Large-area Galaxy Surveys and Cosmic Microwave Background Experiments text January 2017
KiDS-450: Cosmological Constraints from Weak Lensing Peak Statistics - II: Inference from Shear Peaks using N-body Simulations text January 2017
Constraining neutrino mass with weak lensing Minkowski Functionals text January 2018
Weak lensing cosmology with convolutional neural networks on noisy data text January 2019
Cosmological studies from tomographic weak lensing peak abundances and impacts of photo-z errors text January 2019

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