Edinburgh Research Archive >
Physics, School of >
Physics thesis and dissertation collection >
Please use this identifier to cite or link to this item:
|Title: ||Gravitational lensing analysis of galaxy clusters in the Southern Cosmology Survey|
|Authors: ||McInnes, Rachel Natalie|
|Supervisor(s): ||Heavens, Alan|
|Issue Date: ||2010|
|Publisher: ||The University of Edinburgh|
|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.|
|Keywords: ||Southern Cosmology Survey|
|Appears in Collections:||Physics thesis and dissertation collection|
Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.