Baryon impact on weak lensing peaks and power spectrum: low-bias statistics and self-calibration in future surveys
Xiuyuan Yang (Columbia University, Brookhaven National Laboratory),, Jan M. Kratochvil (University of Miami), Kevin Huffenberger (University of, Miami), Zolt\'an Haiman (Columbia University), Morgan May (Brookhaven, National Laboratory)

TL;DR
This study investigates how baryonic effects influence weak lensing peak counts and power spectrum, revealing that low peaks are robust and that combined analysis can self-calibrate baryonic physics and cosmology.
Contribution
It introduces a method to assess baryonic impacts on weak lensing statistics using simulations and demonstrates potential for self-calibration with combined peak and power spectrum analysis.
Findings
Low peaks are unaffected by baryonic effects and contain most cosmological information.
Baryonic effects increase high peak counts, causing modest biases if neglected.
Combining peak counts and power spectrum enables simultaneous constraints on baryonic physics and cosmological parameters.
Abstract
Peaks in two-dimensional weak lensing (WL) maps contain significant cosmological information, complementary to the WL power spectrum. This has recently been demonstrated using N-body simulations which neglect baryonic effects. Here we employ ray-tracing N-body simulations in which we manually steepen the density profile of each dark matter halo, mimicking the cooling and concentration of baryons into dark matter potential wells. We find, in agreement with previous works, that this causes a significant increase in the amplitude of the WL power spectrum on small scales (spherical harmonic index l>1,000). We then study the impact of the halo concentration increase on the peak counts, and find the following. (i) Low peaks (with convergence 0.02 < kappa_peak < 0.08), remain nearly unaffected. These peaks are created by a constellation of several halos with low masses (10^12-10^13 M_sun) and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
