1612.04041
Cosmology with weak-lensing peak counts
Lin
WL causes distortions of galaxy images and probes massive structures on large scales, allowing to understand the late-time evolution of the Universe. One way to extract the cosmo info from WL is to use peak statistics. Peaks are tracers of massive haloes and therefore probe the mass function. They retain non-Gaussian information and have already been shown as a promising tool to constrain cosmology. In this work, develop a new model to predict WL peak counts. The model generates fast sims based on halo sampling and selects peaks from the derived lensing maps. This approach has 3 main advantages. First, the model is very fast: only several seconds are required to perform a realization. Second, including realistic conditions is straightforward. Third, the model provides the full distribution information because of its stochasticity. Show that the model agrees well with N-body sims. Then, study the impacts of the cosmo-dependent covariance on constraints and explore different parameter inference methods. A special focus is put on approximate Bayesian computation (ABC), an accept-reject sampler without the need to estimate the likelihood. Show that ABC is able to yield robust constraints with much reduced time costs. Several filtering techniques are studied to improve the extraction of multi scale information. Finally, the new model is applied to the CFHTLenS, KiDS DR1/2, and DES SV data sets. The preliminary results agree with the Planck constraints assuming LCDM. Overall, this thesis forges an innovative tool for future WL surveys. The manuscript provides a brief review on WL peak counts.
1612.04247
Impact of baryons and super-cluster environments on weak lensing measurements
Peters, Brown, Kay, Barnes
Use a combination of full hydrodynamic and DM only sims to investigate the effect that super-cluster environments and baryonic physics have on the matter power spectrum. This is done by re-simulating a sample of super-cluster sub-volumes, identified in a large cosmologically representative DM only sim, along with a random control sample. On large scales, find that the matter PS measured from the super-cluster sample has at least 2x as much power as that measured from the random sample, while on small scales the super-cluster sample has less power than the random sample. The investigation of the effect of baryons physics on the matter PS is found to be in agreement with previous studies. However, find that the effect of environment on the matter power spectrum is dominant over the effect of baryons. In addition, investigate the effect of targeting a cosmologically non-representative, super-cluster region of the sky in the WL shear PS. Do this by generating shear and convergence maps using a LoS integration technique, which intercepts the random and supercluster sub-volumes. Find the convergence power spectrum measured from the super-cluster sample has a larger amplitude than that measured from the random sample at all scales, and by more than a factor of 2 for ell<1e3. Frame the results within the context of the Super-CLusterAssisted 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 5 Abell clusters. Assuming the Super-CLASS survey will have a source density of 1.5 galaxies/arcmin2, forecast a detection significance of 2.7±1.5, which indicates that the Super-CLASS project will likely make a cosmic shear detection with radio data alone.
1612.04360
Large-scale assembly bias of dark matter haloes
Lazeyras, Musso, Schmidt
Present precise measurements of the assembly bias of DM haloes, i.e. the dependent of halo bias on other properties than the mass, using curved "separate universe" N-body sims which effectively incorporate an infinite-wavelength matter overdnesity into the BG density. This method measure the LIMD bias parameters b_n in the large-scale limit. Focus on the dependence of the first two Eulerian biases b1 and b2 on 4 halo properties: the concentration, spin, mass accretion rate, and ellipticity. Quantitatively compare the results with previous works in which assembly bias was measured on fairly small scales. Despite this difference, the findings are in good agreement with previous results. Also look at the joint dependence of bias on 2 halo properties in addition to the mass. Finally, using the excursion set peaks model, attempt to shed new insights on how assembly bias arises in this analytical model.
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