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Title: Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling

Abstract

We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.

Authors:
; ;
Publication Date:
Research Org.:
Stanford Linear Accelerator Center (SLAC)
Sponsoring Org.:
USDOE
OSTI Identifier:
878813
Report Number(s):
SLAC-PUB-11376
astro-ph/0507613; TRN: US0602601
DOE Contract Number:  
AC02-76SF00515
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; ABUNDANCE; CLUSTER MODEL; GALAXIES; GALAXY CLUSTERS; MONTE CARLO METHOD; PHOTONS; PLASMA; SAMPLING; SIMULATION; STATISTICS; Astrophysics,ASTRO

Citation Formats

Peterson, John R, Marshall, P J, /KIPAC, Menlo Park, Andersson, K, and /Stockholm U. /SLAC. Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling. United States: N. p., 2005. Web. doi:10.2172/878813.
Peterson, John R, Marshall, P J, /KIPAC, Menlo Park, Andersson, K, & /Stockholm U. /SLAC. Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling. United States. doi:10.2172/878813.
Peterson, John R, Marshall, P J, /KIPAC, Menlo Park, Andersson, K, and /Stockholm U. /SLAC. Fri . "Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling". United States. doi:10.2172/878813. https://www.osti.gov/servlets/purl/878813.
@article{osti_878813,
title = {Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling},
author = {Peterson, John R and Marshall, P J and /KIPAC, Menlo Park and Andersson, K and /Stockholm U. /SLAC},
abstractNote = {We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.},
doi = {10.2172/878813},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2005},
month = {8}
}

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