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Register a new userA joint analysis of AMI and CARMA observations of the recently discovered SZ galaxy cluster system AMI-CL J0300+2613
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We present CARMA observations of a massive galaxy cluster discovered in the AMI blind SZ survey. Without knowledge of the cluster redshift a Bayesian analysis of the AMI, CARMA and joint AMI & CARMA uv-data is used to quantify the detection significance and parameterise both the physical and observational properties of the cluster whilst accounting for the statistics of primary CMB anisotropies, receiver noise and radio sources. The joint analysis of the AMI & CARMA uv-data was performed with two parametric physical cluster models: the {beta}-model; and the model described in Olamaie et al. 2012 with the pressure profile fixed according to Arnaud et al. 2010. The cluster mass derived from these different models is comparable but our Bayesian evidences indicate a preference for the {beta}-profile which we, therefore, use throughout our analysis. From the CARMA data alone we obtain a Bayesian probability of detection ratio of 12.8:1 when assuming that a cluster exists within our search area; alternatively assuming that Jenkins et al. 2001 accurately predicts the number of clusters as a function of mass and redshift, the Bayesian probability of detection is 0.29:1. From the analysis of the AMI or AMI & CARMA data the probability of detection ratio exceeds 4.5x10^3:1. Performing a joint analysis of the AMI & CARMA data with a physical cluster model we derive the total mass internal to r200 as MT,200 = 4.1x10^14Msun. Using a phenomenological {beta}-model to quantify the temperature decrement as a function of angular distance we find a central SZ temperature decrement of 170{mu}K in the AMI & CARMA data. The SZ decrement in the CARMA data is weaker than expected and we speculate that this is a consequence of the cluster morphology. In a forthcoming study we will assess the impact of cluster morphology on the SZ decrements that are observed with interferometers such as AMI and CARMA.
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The Arcminute Microkelvin Imager (AMI) carried out a blind survey for galaxy clusters via their Sunyaev-Zeldovich effect decrements between 2008 and 2011. The first detection, known as AMI-CL J0300+2613, has been reobserved with AMI equipped with a new digital correlator with high dynamic range. The combination of the new AMI data and more recent high-resolution sub-mm and infra-red maps now shows the feature in fact to be a ring of positive dust-correlated Galactic emission, which is likely to be anomalous microwave emission (AME). If so, this is the first completely blind detection of AME at arcminute scales.
We have obtained deep SZ observations towards 15 of the apparently 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 ten 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. For clusters undetected in SZ, the average 68% upper limit on the mean temperature is a factor of 1.9 below the XCS temperature.
We present 16-GHz Sunyaev-Zeldovich observations using the Arcminute Microkelvin Imager (AMI) and subsequent Bayesian analysis of six galaxy clusters at redshift ($z approx 1$) 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 $times$ the critical density at the respective clusters 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 distributions for each fitted cluster profile parameter of the detected clusters. Using simulations which take into account the measured source environment from the AMI Large Array (LA), source confusion noise, CMB primordials, instrument noise, we estimate from low-radius X-ray data from Culverhouse et al. (2010), the detectability of each cluster in the sample and compare it with the result from the Small Array (SA) data. Furthermore, we discuss the validity of the assumptions of isothermality and constant gas mass fraction. We comment on the bias that these small-radius estimates introduce to large-radius SZ predictions. In addition, we follow-up the two detections with deep, single-pointed LA observations. We find a 3 sigma tentative decrement toward CLJ1415+3612 at high-resolution and a 5 sigma high-resolution decrement towards XMJ0830+5241.
Using Arcminute Microkelvin Imager (AMI) SZ observations towards ten CLASH clusters we investigate the influence of cluster mergers on observational galaxy cluster studies. Although selected to be largely relaxed, there is disagreement in the literature on the dynamical states of CLASH sample members. We analyse our AMI data in a fully Bayesian way to produce estimated cluster parameters and consider the intrinsic correlations in our NFW/GNFW-based model. Varying pressure profile shape parameters, illustrating an influence of mergers on scaling relations, induces small deviations from the canonical self-similar predictions -- in agreement with simulations of Poole et al. 2007 who found that merger activity causes only small scatter perpendicular to the relations. We demonstrate this effect observationally using the different dependencies of SZ and X-ray signals to $n_{rm e}$ that cause different sensitivities to the shocking and/or fractionation produced by mergers. Plotting $Y_{rm X}$--$M_{rm gas}$ relations (where $Y_{rm X}=M_{rm gas}T$) derived from AMI SZ and from $Chandra$ X-ray gives ratios of AMI and $Chandra$ $Y_{rm X}$ and $M_{rm gas}$ estimates that indicate movement of clusters textit{along} the scaling relation, as predicted by Poole et al. 2007. Clusters that have moved most along the relation have the most discrepant $T_{rm SZ}$ and $T_{rm X}$ estimates: all the other clusters (apart from one) have SZ and X-ray estimates of $M_{rm gas}$, $T$ and $Y_{rm X}$ that agree within $r_{500}$. We use SZ vs X-ray discrepancies in conjunction with $Chandra$ maps and $T_{rm X}$ profiles, making comparisons with simulated cluster merger maps in Poole et al. 2006, to identify disturbed members of our sample and estimate merger stages.
We present a deep survey of the SuperCLASS super-cluster - a region of sky known to contain five Abell clusters at redshift $zsim0.2$ - performed using the Arcminute Microkelvin Imager (AMI) Large Array (LA) at 15.5$~$GHz. Our survey covers an area of approximately 0.9 square degrees. We achieve a nominal sensitivity of $32.0~mu$Jy beam$^{-1}$ toward the field centre, finding 80 sources above a $5sigma$ threshold. We derive the radio colour-colour distribution for sources common to three surveys that cover the field and identify three sources with strongly curved spectra - a high-frequency-peaked source and two GHz-peaked-spectrum sources. The differential source count (i) agrees well with previous deep radio source count, (ii) exhibits no evidence of an emerging population of star-forming galaxies, down to a limit of 0.24$~$mJy, and (iii) disagrees with some models of the 15$~$GHz source population. However, our source count is in agreement with recent work that provides an analytical correction to the source count from the SKADS Simulated Sky, supporting the suggestion that this discrepancy is caused by an abundance of flat-spectrum galaxy cores as-yet not included in source population models.
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