English

Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations

Cosmology and Nongalactic Astrophysics 2022-12-14 v1

Abstract

Next-generation weak lensing (WL) surveys, such as by the Vera Rubin Observatory's LSST, the Roman\textit{Roman} Space Telescope, and the Euclid\textit{Euclid} space mission, will supply vast amounts of data probing small, highly nonlinear scales. Extracting information from these scales requires higher-order statistics and the controlling of related systematics such as baryonic effects. To account for baryonic effects in cosmological analyses at reduced computational cost, semi-analytic baryonic correction models (BCMs) have been proposed. Here, we study the accuracy of BCMs for WL peak counts, a well studied, simple, and effective higher-order statistic. We compare WL peak counts generated from the full hydrodynamical simulation IllustrisTNG and a baryon-corrected version of the corresponding dark matter-only simulation IllustrisTNG-Dark. We apply galaxy shape noise expected at the depths reached by DES, KiDS, HSC, LSST, Roman\textit{Roman}, and Euclid\textit{Euclid}. We find that peak counts in BCMs are (i) accurate at the percent level for peaks with S/N<4\mathrm{S/N}<4, (ii) statistically indistinguishable from IllustrisTNG in most current and ongoing surveys, but (iii) insufficient for deep future surveys covering the largest solid angles, such as LSST and Euclid\textit{Euclid}. We find that BCMs match individual peaks accurately, but underpredict the amplitude of the highest peaks. We conclude that existing BCMs are a viable substitute for full hydrodynamical simulations in cosmological parameter estimation from beyond-Gaussian statistics for ongoing and future surveys with modest solid angles. For the largest surveys, BCMs need to be refined to provide a more accurate match, especially to the highest peaks.

Keywords

Cite

@article{arxiv.2201.08320,
  title  = {Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations},
  author = {Max E. Lee and Tianhuan Lu and Zoltán Haiman and Jia Liu and Ken Osato},
  journal= {arXiv preprint arXiv:2201.08320},
  year   = {2022}
}

Comments

12 pages, 10 figures

R2 v1 2026-06-24T08:56:54.018Z