有哪些信誉好的足球投注网站Markov Chain Monte Carlo joint analysis of Chandra X-ray imaging spectroscopy and Sunyaev-Z.pdf
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Markov Chain Monte Carlo joint analysis of Chandra X-ray imaging spectroscopy and Sunyaev-Z
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Markov Chain Monte Carlo joint analysis of Chandra X-ray
imaging spectroscopy and Sunyaev-Zeldovich Effect data
Massimiliano Bonamente 1,2, Marshall K. Joy 2, John E. Carlstrom 3,4, Erik D. Reese 5,6 and
Samuel J. LaRoque 3,4
1Department of Physics, University of Alabama, Huntsville, AL
2NASA Marshall Space Flight Center, Huntsville, AL
3Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL 60637
4Kavli Institute for Cosmological Physics, Department of Physics, Enrico Fermi Institute,
University of Chicago, Chicago, IL 60637
5Physics Department, University of California, Berkeley, CA 94720
6Chandra Fellow
ABSTRACT
X-ray and Sunyaev-Zeldovich Effect data can be combined to determine the
distance to galaxy clusters. High-resolution X-ray data are now available from the
Chandra Observatory, which provides both spatial and spectral information, and
Sunyaev-Zeldovich Effect data were obtained from the BIMA and OVRO arrays.
We introduce a Markov chain Monte Carlo procedure for the joint analysis of
X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are
the high computational efficiency and the ability to measure simultaneously the
probability distribution of all parameters of interest, such as the spatial and
spectral properties of the cluster gas and also for derivative quantities such as
the distance to the cluster. We demonstrate this technique by applying it to the
Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611.
Comparisons with traditional likelihood-ratio methods reveal the robustness of
the method. This method will be used in follow-up papers to determine the
distances to a large sample of galaxy clusters.
Subject headings: cosmic microwave background – cosmology:observations – dis-
tance scale – galaxies:clusters:general – techniques:interferometric – methods:
statistical
1. Introduction
Analysis of Sunyaev-Zeldovich Effect
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