Published in

Oxford University Press, Monthly Notices of the Royal Astronomical Society, 3(474), p. 3173-3186, 2017

DOI: 10.1093/mnras/stx2780

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Supercluster simulations: impact of baryons on the matter power spectrum and weak lensing forecasts for Super-CLASS

Journal article published in 2017 by Aaron Peters, Michael L. Brown, Scott T. Kay, David J. Barnes ORCID
This paper is available in a repository.
This paper is available in a repository.

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Data provided by SHERPA/RoMEO

Abstract

Abstract We use a combination of full hydrodynamic and dark matter only simulations to investigate the effect that supercluster environments and baryonic physics have on the matter power spectrum, by re-simulating a sample of supercluster sub-volumes. On large scales we find that the matter power spectrum measured from our supercluster sample has at least twice as much power as that measured from our random sample. Our investigation of the effect of baryonic physics on the matter power spectrum is found to be in agreement with previous studies and is weaker than the selection effect over the majority of scales. In addition, we investigate the effect of targeting a cosmologically non-representative, supercluster region of the sky on the weak lensing shear power spectrum. We do this by generating shear and convergence maps using a line-of-sight integration technique, which intercepts our random and supercluster sub-volumes. We find the convergence power spectrum measured from our supercluster sample has a larger amplitude than that measured from the random sample at all scales. We frame our results within the context of the Super-CLuster Assisted Shear Survey (Super-CLASS), which aims to measure the cosmic shear signal in the radio band by targeting a region of the sky that contains five Abell clusters. Assuming the Super-CLASS survey will have a source density of 1.5 galaxies arcmin−2, we forecast a detection significance of $2.7^{+1.5}_{-1.2}$, which indicates that in the absence of systematics the Super-CLASS project could make a cosmic shear detection with radio data alone.