Weak lensing cosmology and its astrophysical systematics through machine learning

In this dissertation, we investigate weak lensing cosmology and its astrophysical systematics by employing machine learning techniques. We focus on addressing the discrepancy between two previous weak lensing analyses on CFHTLenS data, understanding the impact of baryons on weak lensing statistics, and leveraging convolutional neural networks (CNNs) for constraining cosmological and baryonic parameters. First, we perform a side-by-side comparison of the two-point correlation function and power spectrum analyses on CFHTLenS data, identifying excess power in the data on small scales and discussing potential origins of this excess power. Next, we study the effect of baryons on weak lensing statistics using the baryonic correction model, demonstrating that marginalizing over baryonic parameters will degrade constraints in the Ωm–σ8 parameter space, but the degradation can be mitigated by combining the lensing power spectrum and peak counts. Second, we explore the use of CNNs to constrain cosmological and baryonic parameters. We find that CNNs can achieve tighter constraints in Ωm–σ8 space than traditional methods on simulation data. We then apply our pipeline to the HSC first-year weak lensing shear catalog. We find that statistical uncertainties of the parameters by the CNNs are smaller than those from the power spectrum and peak counts, showing that CNNs can extract additional cosmological information from weak lensing data even in a real experiment

Cosmological constraints from HSC survey first-year data using deep learning

We present cosmological constraints from the Subaru Hyper Suprime-Cam (HSC) first-year weak lensing shear catalogue using convolutional neural networks (CNNs) and conventional summary statistics. We crop 19 $3\times3\,\mathrm{{deg}^2}$ sub-fields from the first-year area, divide the galaxies with redshift $0.3\le z\le1.5$ into four equally-spaced redshift bins, and perform tomographic analyses. We develop a pipeline to generate simulated convergence maps from cosmological $N$-body simulations, where we account for effects such as intrinsic alignments (IAs), baryons, photometric redshift errors, and point spread function errors, to match characteristics of the real catalogue. We train CNNs that can predict the underlying parameters from the simulated maps, and we use them to construct likelihood functions for Bayesian analyses. In the $\Lambda$ cold dark matter model with two free cosmological parameters $\Omega_\mathrm{m}$ and $\sigma_8$, we find $\Omega_\mathrm{m}=0.278_{-0.035}^{+0.037}$, $S_8\equiv(\Omega_\mathrm{m}/0.3)^{0.5}\sigma_8=0.793_{-0.018}^{+0.017}$, and the IA amplitude $A_\mathrm{IA}=0.20_{-0.58}^{+0.55}$. In a model with four additional free baryonic parameters, we find $\Omega_\mathrm{m}=0.268_{-0.036}^{+0.040}$, $S_8=0.819_{-0.024}^{+0.034}$, and $A_\mathrm{IA}=-0.16_{-0.58}^{+0.59}$, with the baryonic parameters not being well-constrained. We also find that statistical uncertainties of the parameters by the CNNs are smaller than those from the power spectrum (5--24 percent smaller for $S_8$ and a factor of 2.5--3.0 smaller for $\Omega_\mathrm{m}$), showing the effectiveness of CNNs for uncovering additional cosmological information from the HSC data. With baryons, the $S_8$ discrepancy between HSC first-year data and Planck 2018 is reduced from $\sim2.2\,\sigma$ to $0.3\text{--}0.5\,\sigma$.Comment: 22 pages, 14 figure

Revealing the cosmic web dependent halo bias

Halo bias is the one of the key ingredients of the halo models. It was shown at a given redshift to be only dependent, to the first order, on the halo mass. In this study, four types of cosmic web environments: clusters, filaments, sheets and voids are defined within a state of the art high resolution $N$-body simulation. Within those environments, we use both halo-dark matter cross-correlation and halo-halo auto correlation functions to probe the clustering properties of halos. The nature of the halo bias differs strongly among the four different cosmic web environments we describe. With respect to the overall population, halos in clusters have significantly lower biases in the {$10^{11.0}\sim 10^{13.5}h^{-1}\rm M_\odot$} mass range. In other environments however, halos show extremely enhanced biases up to a factor 10 in voids for halos of mass {$\sim 10^{12.0}h^{-1}\rm M_\odot$}. Such a strong cosmic web environment dependence in the halo bias may play an important role in future cosmological and galaxy formation studies. Within this cosmic web framework, the age dependency of halo bias is found to be only significant in clusters and filaments for relatively small halos \la 10^{12.5}\msunh.Comment: 14 pages, 14 figures, ApJ accepte

Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations

Next-generation weak lensing (WL) surveys, such as by the Vera Rubin Observatory's LSST, the $\textit{Roman}$ Space Telescope, and the $\textit{Euclid}$ space mission, will supply vast amounts of data probing small, highly nonlinear scales. Extracting information from these scales requires higher-order statistics and the controlling of related systematics such as baryonic effects. To account for baryonic effects in cosmological analyses at reduced computational cost, semi-analytic baryonic correction models (BCMs) have been proposed. Here, we study the accuracy of BCMs for WL peak counts, a well studied, simple, and effective higher-order statistic. We compare WL peak counts generated from the full hydrodynamical simulation IllustrisTNG and a baryon-corrected version of the corresponding dark matter-only simulation IllustrisTNG-Dark. We apply galaxy shape noise expected at the depths reached by DES, KiDS, HSC, LSST, $\textit{Roman}$, and $\textit{Euclid}$. We find that peak counts in BCMs are (i) accurate at the percent level for peaks with $\mathrm{S/N}<4$, (ii) statistically indistinguishable from IllustrisTNG in most current and ongoing surveys, but (iii) insufficient for deep future surveys covering the largest solid angles, such as LSST and $\textit{Euclid}$. We find that BCMs match individual peaks accurately, but underpredict the amplitude of the highest peaks. We conclude that existing BCMs are a viable substitute for full hydrodynamical simulations in cosmological parameter estimation from beyond-Gaussian statistics for ongoing and future surveys with modest solid angles. For the largest surveys, BCMs need to be refined to provide a more accurate match, especially to the highest peaks.Comment: 12 pages, 10 figure

Galaxy-galaxy weak-lensing measurement from SDSS: II. host halo properties of galaxy groups

As the second paper of a series on studying galaxy-galaxy lensing signals using the Sloan Digital Sky Survey Data Release 7 (SDSS DR7), we present our measurement and modelling of the lensing signals around groups of galaxies. We divide the groups into four halo mass bins, and measure the signals around four different halo-center tracers: brightest central galaxy (BCG), luminosity-weighted center, number-weighted center and X-ray peak position. For X-ray and SDSS DR7 cross identified groups, we further split the groups into low and high X-ray emission subsamples, both of which are assigned with two halo-center tracers, BCGs and X-ray peak positions. The galaxy-galaxy lensing signals show that BCGs, among the four candidates, are the best halo-center tracers. We model the lensing signals using a combination of four contributions: off-centered NFW host halo profile, sub-halo contribution, stellar contribution, and projected 2-halo term. We sample the posterior of 5 parameters i.e., halo mass, concentration, off-centering distance, sub halo mass, and fraction of subhalos via a MCMC package using the galaxy-galaxy lensing signals. After taking into account the sampling effects (e.g. Eddington bias), we found the best fit halo masses obtained from lensing signals are quite consistent with those obtained in the group catalog based on an abundance matching method, except in the lowest mass bin. Subject headings: (cosmology:) gravitational lensing, galaxies: clusters: generalComment: 12 pages, 7 figures, submitted to Ap