Cluster Catalog Validation with Multiwavelength Data

Fuente: arXiv
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Autores principales: Steelberg, Ethan K., Jeltema, Tesla E., O'Donnell, Jackson H., Solomon, Rance, Collaboration, The LSST Dark Energy Science
Formato: Preprint
Publicado: 2025
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author Steelberg, Ethan K.
Jeltema, Tesla E.
O'Donnell, Jackson H.
Solomon, Rance
Collaboration, The LSST Dark Energy Science
author_facet Steelberg, Ethan K.
Jeltema, Tesla E.
O'Donnell, Jackson H.
Solomon, Rance
Collaboration, The LSST Dark Energy Science
contents The Legacy Survey of Space and Time (LSST) will provide a ground-breaking data set for cosmology, but to achieve the precision needed, the data, data reduction, and algorithms measuring the cosmological data vectors must be thoroughly validated and calibrated. In this note, we focus on clusters of galaxies and present a set of validation tests for optical cluster finding algorithms through comparison to X-ray and Sunyaev-Zel'dovich effect cluster catalogs. As an example, we apply our pipeline to compare the performance of the redMaPPer (red-sequence Matched filter Probabilistic Percolation) and WaZP (Wavelet Z Photometric) cluster finding algorithms on Dark Energy Survey (DES) data.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07268
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cluster Catalog Validation with Multiwavelength Data
Steelberg, Ethan K.
Jeltema, Tesla E.
O'Donnell, Jackson H.
Solomon, Rance
Collaboration, The LSST Dark Energy Science
Cosmology and Nongalactic Astrophysics
The Legacy Survey of Space and Time (LSST) will provide a ground-breaking data set for cosmology, but to achieve the precision needed, the data, data reduction, and algorithms measuring the cosmological data vectors must be thoroughly validated and calibrated. In this note, we focus on clusters of galaxies and present a set of validation tests for optical cluster finding algorithms through comparison to X-ray and Sunyaev-Zel'dovich effect cluster catalogs. As an example, we apply our pipeline to compare the performance of the redMaPPer (red-sequence Matched filter Probabilistic Percolation) and WaZP (Wavelet Z Photometric) cluster finding algorithms on Dark Energy Survey (DES) data.
title Cluster Catalog Validation with Multiwavelength Data
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2509.07268