A blind detection of a large, complex, Sunyaev–Zel’dovich structure - Shimwell, T.; Barker, R.; Biddulph, P.; Bly, D.; Boysen, R.; Brown, A.; Brown, M.; Clementson, C.; Crofts, M.; Culverhouse, T.; Czeres, J.; Dace, R.; et al. (Oxford University Press, 2012)
We present an interesting Sunyaev–Zel’dovich (SZ) detection in the first of the Arcminute Microkelvin Imager (AMI) ‘blind’, degree-square fields to have been observed down to our target sensitivity of 100 µJy beam-1. In follow-up deep pointed observations the SZ effect is detected with a maximum peak decrement greater than eight times the thermal noise. No corresponding emission is visible in the ROSAT all-sky X-ray survey and no cluster is evident in the Palomar all-sky optical survey. Compared with existing SZ images of distant clusters, the extent is large (˜10 arcmin) and complex; our analysis favours a model containing two clusters rather than a single cluster. Our Bayesian analysis is currently limited to modelling each cluster with an ellipsoidal or spherical ß model, which does not do justice to this decrement. Fitting an ellipsoid to the deeper candidate we find the following. (a) Assuming that the Evrard et al. approximation to Press & Schechter correctly gives the number density of clusters as a function of mass and redshift, then, in the search area, the formal Bayesian probability ratio of the AMI detection of this cluster is 7.9 × 104:1; alternatively assuming Jenkins et al. as the true prior, the formal Bayesian probability ratio of detection is 2.1 × 105:1. (b) The cluster mass is MT,200 = 5.5+1.2 -1.3 × 1014h -1 70 M. (c) Abandoning a physical model with number density prior and instead simply modelling the SZ decrement using a phenomenological ß model of temperature decrement as a function of angular distance, we find a central SZ temperature decrement of -295+36 -15 µK – this allows for cosmic microwave background primary anisotropies, receiver noise and radio sources.We are unsure if the cluster system we observe is a merging system or two separate clusters.