Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.563011
Title: Gravitational lensing analysis of galaxy clusters in the Southern Cosmology Survey
Author: McInnes, Rachel Natalie
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2010
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Abstract:
In this thesis I present the first gravitational lensing results from the Southern Cosmology Survey (SCS). I provide a preliminary study of an automated pipeline analysis of a large survey, in preparation for larger surveys. Future large-area sky surveys, such as Pan-STARRS-1 (PS1), have similar characteristics to the SCS data and will require full automation of the processing. Therefore, this data set provides an ideal test case to highlight the problems which will be faced by such surveys. To analyse the large SCS dataset, I develop an automated weak lensing pipeline based on the KSB. This pipeline has been rigorously verified using simulations and data which I detail here. Results are shown from a weak lensing analysis of 152 optically-selected clusters in 56 square degrees. I fit universal Navarro, Frenk and White (NFW) profiles to measure cluster masses, and use the relatively large area of the survey to test the universal shape of cluster profiles using stacking of the tangential shears. I present the first lensing mass measurements of Sunyaev-Zel’dovich (SZ) selected clusters. It has been long thought that SZ surveys would be a powerful way to detect galaxy clusters for cosmological studies. Simulations show that the SZ detection is independent of redshift and that the threshold corresponds very closely to a threshold in mass. It was, however, not guaranteed that the first blind SZ experiments would detect mass. Using optical imaging from the SCS, I present lensing masses for three clusters selected by their SZ emission in the South Pole Telescope survey (SPT). I confirm that the SZ selection procedure is successful in detecting mass concentrations and find that the SZ clusters have amongst the largest masses, as high as 15x1014M . Consequently I can confirm that the first installment of SZ detections has detected large mass concentrations. Using the best fit masses for all the clusters, I analytically calculate the expected SZ integrated Y parameter. Finally, the scaling relation of Reyes et al. (2008) of lensing Mlens 200 against optical L200 is tested over the redshift range z = 0:1 - 0:3 and extended to z = 0:3 - 0:8. While there is some discrepancy in the lower redshift-range, we agree with Reyes et al (2008) in the higherredshift sample if we assume no evolution of the scaling relation. To test the tangential shear profile of these clusters, 98 clusters are stacked. We find that by allowing the model to vary from an NFW, a very good fit can be found with a higher normalisation of the shears and a lower concentration. This study supports that of Mandelbaum et al. (2008) who show that that massive halos have a lower concentration than expected. Like the SCS, new large area surveys such as PS1 are not very deep, and it is crucial to understand not only how to analyse this size of dataset, but also the sort of results one could expect to achieve. I show in this thesis that 2D mass reconstructions can be done on data of this quality, and large galaxy clusters successfully reconstructed. With a number density of n ~ 9 it is possible to detect the most massive clusters with lensing, but it is difficult. With the lower number density of n ~ 6 or lower expected from PS1 it will prove very difficult to detect individual clusters. However, PS1 will survey a massive area, and so the stacking analysis should work extremely well, and it should be possible to further test the shape of the cluster profiles with stacking as I demonstrated here with the smaller SCS dataset.
Supervisor: Heavens, Alan. ; Taylor, Andy. ; Massey, Richard. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.563011  DOI: Not available
Keywords: Southern Cosmology Survey ; gravitational lensing ; automation ; Pan-STARRS-1
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