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Main Authors: Wang, Kang, Perrott, Yvette, Arnold, Richard, Huijser, David
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2310.07914
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author Wang, Kang
Perrott, Yvette
Arnold, Richard
Huijser, David
author_facet Wang, Kang
Perrott, Yvette
Arnold, Richard
Huijser, David
contents This study focuses on modelling galaxy cluster gas profiles via a semi-parametric nodal approach. While traditional methods like the generalised Navarro-Frenk-White (gNFW) often encounter parameter degeneracy, our flexible node-based method precisely defines a cluster gas pressure profile. Using Planck space telescope data from the Coma region, our model, focused on the pressure-radius relationship, showcases enhanced flexibility over the gNFW. Bayesian analyses indicated an optimal five-node structure for the Coma cluster pressure profile.
format Preprint
id arxiv_https___arxiv_org_abs_2310_07914
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A Semi-Parametric Approach to Fitting Gas Pressure Profiles of Galaxy Clusters
Wang, Kang
Perrott, Yvette
Arnold, Richard
Huijser, David
Cosmology and Nongalactic Astrophysics
This study focuses on modelling galaxy cluster gas profiles via a semi-parametric nodal approach. While traditional methods like the generalised Navarro-Frenk-White (gNFW) often encounter parameter degeneracy, our flexible node-based method precisely defines a cluster gas pressure profile. Using Planck space telescope data from the Coma region, our model, focused on the pressure-radius relationship, showcases enhanced flexibility over the gNFW. Bayesian analyses indicated an optimal five-node structure for the Coma cluster pressure profile.
title A Semi-Parametric Approach to Fitting Gas Pressure Profiles of Galaxy Clusters
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2310.07914