AMI SZ observations and Bayesian analysis of a sample of six redshift-one clusters of galaxies
AMI Consortium: Michel P. Schammel, Farhan Feroz, Keith J. B. Grainge,, Michael P. Hobson, Natasha Hurley-Walker, Anthony N. Lasenby, Malak Olamaie,, Yvette C. Perrott, Guy G. Pooley, Carmen Rodriguez-Gonzalvez, Clare Rumsey,, Richard D. E. Saunders, Paul F. Scott

TL;DR
This paper presents 16-GHz Sunyaev-Zel'dovich observations and Bayesian analysis of six galaxy clusters at redshift around 1, detecting two clusters and estimating their masses, while discussing model assumptions and follow-up observations.
Contribution
The study applies Bayesian analysis with two cluster models to SZ data of high-redshift clusters, providing new mass estimates and insights into model assumptions and detection significance.
Findings
Detected two clusters with SZ effect at high redshift.
Measured consistent total masses for each cluster across models.
Performed follow-up high-resolution observations confirming detections.
Abstract
We present 16-GHz Sunyaev-Zel'dovich observations using the Arcminute Microkelvin Imager (AMI) and subsequent Bayesian analysis of six galaxy clusters at redshift () chosen from an X-ray and Infrared selected sample from Culverhouse et al. (2010). In the subsequent analysis we use two cluster models, an isothermal \beta-model and a Dark Matter GNFW (DM-GNFW) model in order to derive a formal detection probability and the cluster parameters. We detect two clusters (CLJ1415+3612 & XMJ0830+5241) and measure their total masses out to a radius of 200 the critical density at the respective cluster's redshift. For CLJ1415+3612 and XMJ0830+5241, we find M_{\mathrm{T},200} for each model, which agree with each other for each cluster. We also present maps before and after source subtraction of the entire sample and provide 1D and 2D posterior marginalised probability…
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