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Published August 21, 2013 | Submitted + Published
Journal Article Open

Sunyaev–Zel'dovich observations with AMI of the hottest galaxy clusters detected in the XMM–Newton Cluster Survey

Abstract

We have obtained deep Sunyaev–Zel'dovich (SZ) observations towards 15 of the hottest XMM Cluster Survey (XCS) clusters that can be observed with the Arcminute Microkelvin Imager (AMI). We use a Bayesian analysis to quantify the significance of our SZ detections. We detect the SZ effect at high significance towards three of the clusters and at lower significance for a further two clusters. Towards the remaining 10 clusters, no clear SZ signal was measured. We derive cluster parameters using the XCS mass estimates as a prior in our Bayesian analysis. For all AMI-detected clusters, we calculate large-scale mass and temperature estimates while for all undetected clusters we determine upper limits on these parameters. We find that the large-scale mean temperatures derived from our AMI SZ measurements (and the upper limits from null detections) are substantially lower than the XCS-based core-temperature estimates. For clusters detected in the SZ, the mean temperature is, on average, a factor of 1.4 lower than temperatures from the XCS. Our upper limits on the cluster temperature of undetected systems are lower than the mean XCS derived temperature.

Additional Information

© 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2013 May 24. Received 2013 May 17; in original form 2013 February 9. We thank the anonymous referee for constructive feedback. We thank Cambridge University and STFC for their support of AMI and its operations. We are grateful to the staff of the Cavendish Laboratory and the Mullard Radio Astronomy Observatory for the maintenance and operation of AMI.We thank JulianMayers for useful discussions regarding the XCS temperature estimates. CR and MPS acknowledge PPARC/STFC studentships. YCP acknowledges the support of a Rutherford Foundation/CCT/Cavendish Laboratory studentship. This work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England, and the Altix 3700 Supercomputer at DAMTP, University of Cambridge supported by HEFCE and STFC. We are grateful to Stuart Rankin and Andrey Kaliazin for their computing assistance.

Attached Files

Published - MNRAS-2013-Shimwell-2920-37.pdf

Submitted - 1305.6654.pdf

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August 22, 2023
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