Intrinsic alignments of group and cluster galaxies in photometric surveys
Nora Elisa Chisari, Rachel Mandelbaum, Michael A. Strauss, Eric Huff,, Neta Bahcall

TL;DR
This study develops a new estimator to measure galaxy intrinsic alignments around clusters using photometric data, effectively removing lensing contamination, and finds the alignment signal to be consistent with zero in the studied redshift range.
Contribution
We introduce an estimator that isolates intrinsic galaxy alignments from lensing contamination in photometric surveys, enabling non-linear regime analysis.
Findings
Intrinsic alignment signal around clusters is consistent with zero.
Constraints on alignment strength and bias are tight, limiting contamination.
Results are robust across different photometric bands and cluster centering methods.
Abstract
Intrinsic alignments of galaxies have been shown to contaminate weak gravitational lensing observables on linear scales, 10 Mpc, but studies of alignments in the non-linear regime have thus far been inconclusive. We present an estimator for extracting the intrinsic alignment signal of galaxies around stacked clusters of galaxies from multiband imaging data. Our estimator removes the contamination caused by galaxies that are gravitationally lensed by the clusters and scattered in redshift space due to photometric redshift uncertainties. It uses posterior probability distributions for the redshifts of the galaxies in the sample and it is easily extended to obtain the weak gravitational lensing signal while removing the intrinsic alignment contamination. We apply this algorithm to groups and clusters of galaxies identified in the Sloan Digital Sky Survey `Stripe 82' coadded…
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.
