A simple parametric model for spherical galaxy clusters

Olamaie, Malak; Hobson, M.; Grainge, Keith

doi:10.1111/j.1365-2966.2012.20980.x

Cited by 28 publications

(45 citation statements)

References 80 publications

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“…It is at higher redshift, z = 0.412 (Böhringer et al 2000) so the large value for θ s of ≈4.5 arcmin preferred by Planck is slightly surprising. Figure 34 shows the posteriors on θ s and Y tot produced by AMI and Planck, as well as the region of the space predicted by the physical model described in Olamaie et al (2012) assuming the universal pressure profile for the gas, and the Tinker mass function (Tinker et al 2008). The AMI posterior is much more consistent with the prediction than the Planck posterior; also our simulations have shown that if the correct value were θ s ≈ 4.5, we should recover it even if the profile deviates from the universal profile.…”

Section: Rxc J22286+2036 (Psz1 G08330-3101)mentioning

confidence: 99%

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Comparison of Sunyaev-Zel’dovich measurements fromPlanckand from the Arcminute Microkelvin Imager for 99 galaxy clusters

Perrott

Olamaie

Rumsey

et al. 2015

A&A

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We present observations and analysis of a sample of 123 galaxy clusters from the 2013 Planck catalogue of Sunyaev-Zel'dovich sources with the Arcminute Microkelvin Imager (AMI), a ground-based radio interferometer. AMI provides an independent measurement with higher angular resolution, 3 arcmin compared to the Planck beams of 5-10 arcmin. The AMI observations thus provide validation of the cluster detections, improved positional estimates, and a consistency check on the fitted size (θ s ) and flux (Y tot ) parameters in the generalised Navarro, Frenk and White (GNFW) model. We detect 99 of the clusters. We use the AMI positional estimates to check the positional estimates and error-bars produced by the Planck algorithms PowellSnakes and MMF3. We find that Y tot values as measured by AMI are biased downwards with respect to the Planck constraints, especially for high Planck-S/N clusters. We perform simulations to show that this can be explained by deviation from the universal pressure profile shape used to model the clusters. We show that AMI data can constrain the α and β parameters describing the shape of the profile in the GNFW model for individual clusters provided careful attention is paid to the degeneracies between parameters, but one requires information on a wider range of angular scales than are present in AMI data alone to correctly constrain all parameters simultaneously.

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Section: Rxc J22286+2036 (Psz1 G08330-3101)mentioning

confidence: 99%

“…Alternatively, r X and M X for some overdensity radius X can be recovered given a redshift, a concentration parameter c X ≡ r X /r s and some model or scaling relationship for translating Y into mass (e.g. Planck Collaboration XX 2014; Olamaie et al 2012). Physical modelling will not be addressed in this paper.…”

Section: Cluster Modelmentioning

confidence: 99%

Comparison of Sunyaev-Zel’dovich measurements fromPlanckand from the Arcminute Microkelvin Imager for 99 galaxy clusters

Perrott

Olamaie

Rumsey

et al. 2015

A&A

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“…For the cluster model, we used a Navarro-FrenkWhite (NFW; Navarro, Frenk & White 1997) dark matter profile in hydrostatic equilibrium with a gas pressure distribution described by a generalised NFW (GNFW; Nagai, Kravtsov & Vikhlinin 2007) profile with the shape parameters given in Arnaud et al (2010); for more details of the model see Olamaie, Hobson & Grainge (2012). We refer to this as the DM-GNFW model.…”

Section: Cluster Analysismentioning

confidence: 99%

AMI-CL J0300+2613: a Galactic anomalous-microwave-emission ring masquerading as a galaxy cluster

Perrott

Cantwell

Carey

et al. 2017

Monthly Notices of the Royal Astronomical Society

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The Arcminute Microkelvin Imager (AMI) carried out a blind survey for galaxy clusters via their Sunyaev-Zel'dovich 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.

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“…We use the model described in Olamaie et al (2012) and (2013), with its corresponding assumptions on the dynamical state of the cluster (model I). As shown in Olamaie et al (2012) and(2013), the model leads to radial profiles for clusters physical properties that are consistent both with numerical simulations and multi wavelength observations of clusters (see e.g.…”

Section: Modelling the X-ray Surface Brightnessmentioning

confidence: 99%

“…Sarazin 1988;Vikhlinin et al 2005Vikhlinin et al , 2006LaRoque et al 2006; AMI Consortium: Olamaie et al 2012 andPlanck Collaboration et al 2013). These radial profiles (e.g.…”

Section: Introductionmentioning

confidence: 99%

bayes-x: a Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

Olamaie¹,

Feroz²,

Grainge

et al. 2014

Monthly Notices of the Royal Astronomical Society

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We present the first public release of our Bayesian inference tool, Bayes-X, for the analysis of X-ray observations of galaxy clusters. We illustrate the use of Bayes-X by analysing a set of four simulated clusters at z = 0.2 − 0.9 as they would be observed by a Chandralike X-ray observatory. In both the simulations and the analysis pipeline we assume that the dark matter density follows a spherically-symmetric Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalised NFW (GNFW) profile. We then perform four sets of analyses. These include prior-only analyses and analyses in which we adopt wide uniform prior probability distributions on f g (r 200 ) and on the model parameters describing the shape and slopes of the GNFW pressure profile, namely (c 500 , a, b, c). By numerically exploring the joint probability distribution of the cluster parameters given simulated Chandra-like data, we show that the model and analysis technique can robustly return the simulated cluster input quantities, constrain the cluster physical parameters and reveal the degeneracies among the model parameters and cluster physical parameters. We then use Bayes-X to analyse Chandra data on the nearby cluster, A262, and derive the cluster physical and thermodynamic profiles. The results are in good agreement with other results given in literature for the cluster. To illustrate the performance of the Bayesian model selection, we also carried out analyses assuming an Einasto profile for the matter density and calculated the Bayes factor. The results of the model selection analyses for the simulated data favour the NFW model as expected. However, we find that the Einasto profile is preferred in the analysis of A262. The Bayes-X software, which is implemented in Fortran 90, is available at

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A simple parametric model for spherical galaxy clusters

Cited by 28 publications

References 80 publications

Comparison of Sunyaev-Zel’dovich measurements fromPlanckand from the Arcminute Microkelvin Imager for 99 galaxy clusters

Comparison of Sunyaev-Zel’dovich measurements fromPlanckand from the Arcminute Microkelvin Imager for 99 galaxy clusters

AMI-CL J0300+2613: a Galactic anomalous-microwave-emission ring masquerading as a galaxy cluster

bayes-x: a Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

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