Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks
Abstract
Weak gravitational lensing (WL) peaks probe non-Gaussian information of the large-scale distribution of matter that is not captured by two-point lensing statistics. We study the cosmological potential of the height distribution, redshift distribution, and angular clustering of high-valued WL peaks using a Bayesian inference approach that mimics a Euclid analysis. We use a forthcoming dark-matter-only hypercube, which varies cosmology in a ten-dimensional space, including evolving dark energy, neutrino mass, decaying dark matter, and the running of the scalar spectral index. We find the individual WL peak statistics to be complementary, as the redshift distribution best constrains the matter density, Ωm, and the dark energy equation-of-state parameters, w0, and wa; the height distribution and angular clustering are most sensitive to the amplitude of the primordial power spectrum, ln(1010As); while combining the three statistics allows us to also probe the baryon density, Ωb, and the Hubble parameter, h. A comparison to the shear two-point correlation function demonstrates that WL peaks alone outperform the commonly used statistics, while even tighter constraints are obtained when combining all. Considering the 2-dimensional Ωm−ln(1010As) and w0−wa parameter planes, we find that the redshift distribution outperforms the angular clustering and peak-height distributions. We study the impact of the smoothing scale and find that, typically, the smallest scales yield the best results and the figure of merit improves by a factor ≈2 when combining multiple scales.
Versions
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BibTeX
@misc{broxterman2026cosmological,
title = {{Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks}},
author = {Jeger C. Broxterman and Matthieu Schaller and Ian G. McCarthy and Willem Elbers and John Helly and Henk Hoekstra and Konrad Kuijken and Jaime Salcido and Joop Schaye and Naomi Schutte and Elena Sellentin},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2607.29128},
eprint = {2607.29128},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2607.29128},
note = {CC0},
}
RIS
TY - UNPB
TI - Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks
AU - Jeger C. Broxterman
AU - Matthieu Schaller
AU - Ian G. McCarthy
AU - Willem Elbers
AU - John Helly
AU - Henk Hoekstra
AU - Konrad Kuijken
AU - Jaime Salcido
AU - Joop Schaye
AU - Naomi Schutte
AU - Elena Sellentin
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2607.29128
UR - https://arxiv.org/abs/2607.29128
AB - Weak gravitational lensing (WL) peaks probe non-Gaussian information of the large-scale distribution of matter that is not captured by two-point lensing statistics. We study the cosmological potential of the height distribution, redshift distribution, and angular clustering of high-valued WL peaks using a Bayesian inference approach that mimics a Euclid analysis. We use a forthcoming dark-matter-only hypercube, which varies cosmology in a ten-dimensional space, including evolving dark energy, neutrino mass, decaying dark matter, and the running of the scalar spectral index. We find the individual WL peak statistics to be complementary, as the redshift distribution best constrains the matter density, Ω_m, and the dark energy equation-of-state parameters, w_0, and w_a; the height distribution and angular clustering are most sensitive to the amplitude of the primordial power spectrum, ln(10^10A_s); while combining the three statistics allows us to also probe the baryon density, Ω_b, and the Hubble parameter, h. A comparison to the shear two-point correlation function demonstrates that WL peaks alone outperform the commonly used statistics, while even tighter constraints are obtained when combining all. Considering the 2-dimensional Ω_m−ln(10^10A_s) and w_0−w_a parameter planes, we find that the redshift distribution outperforms the angular clustering and peak-height distributions. We study the impact of the smoothing scale and find that, typically, the smallest scales yield the best results and the figure of merit improves by a factor ≈2 when combining multiple scales.
ER -