Related papers: How much information can be extracted from galaxy …
We present a simulation-based forward-modeling framework for cosmological inference from optical galaxy-cluster samples, and apply it to the abundance and weak-lensing signals of DES-Y1 redMaPPer clusters. The model embeds…
We present a Bayesian analysis of cosmological parameter constraints from early- and late-universe observations, focusing on the matter density parameter ($\Omega_m$) and the amplitude of matter fluctuations ($\sigma_8$) within the…
The abundance of rich clusters is a strong constraint on the mass power spectrum. The current constraint can be expressed in the form $\sigma_8 \Omega_m^{\gamma} = 0.5 \pm 0.1$ where $\sigma_8$ is the $rms$ mass fluctuation on 8 $h^{-1}$…
We constrain cosmological and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework, and choice of scales…
We use giga-particle N-body simulations to study galaxy cluster populations in Hubble Volumes of LCDM (Omega_m=0.3, Omega_Lambda=0.7) and tCDM (Omega_m=1) world models. Mapping past light-cones of locations in the computational space, we…
We present precise constraints on the normalization of the power spectrum of mass fluctuations in the nearby universe, sigma_8, as a function of the mean local matter density, Omega_m. Using the observed local X-ray luminosity function of…
We present a new formalism to separate large- and small-scale contributions to cosmic shear through \textit{lensing counterterms} (LCT) inspired by effective field theory (EFT). Marginalizing over these LCTs isolates the large-scale…
The properties of nearby galaxy clusters limit the range of cosmological parameters consistent with our universe. We describe the limits which arise from studies of the intracluster medium (ICM) mass fraction fICM and consideration of the…
The amplitude of cosmological density fluctuations, sigma_8, has been studied and estimated by analysing many cosmological observations. The values of the estimates vary considerably between the various probes. However, different estimators…
We investigate the linear amplitude of mass fluctuations in the universe, $\sigma_8$, and the present mass density parameter of the Universe, $\Omega_\mathrm{m}$, from the statistical strong gravitational lensing. We use the two populations…
We show that the counts of galaxy clusters in future deep cluster surveys can place strong constraints on the matter density, Omega_m, the vacuum energy density, Omega_L, and the normalization of the matter power spectrum, sigma_8.…
We quantify the physical memory of the cosmic density field using mutual information between $N$-body snapshots at different redshifts, removing a random baseline to isolate gravitational correlations. The shared mutual information rises…
The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the $\Lambda$CDM…
We show the improvement to cosmological constraints from galaxy cluster surveys with the addition of CMB-cluster lensing data. We explore the cosmological implications of adding mass information from the 3.1$\sigma$ detection of…
We use the direct Fourier method to calculate the redshift-space power spectrum of the maxBCG cluster catalog -- currently by far the largest existing galaxy cluster sample. The total number of clusters used in our analysis is 12,616. After…
Gravitational lensing by massive galaxy clusters distorts the observed cosmic microwave background (CMB) on arcminute scales, and these distortions carry information about cluster masses. Standard approaches to extracting cluster mass…
We present a theoretical model for the power spectrum and bispectrum of galaxy clustering that exploits the complementarity between small-scale power spectrum information and large-scale bispectrum measurements. We extend the FOLPS code by…
Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques require forward models that are both computationally fast and robust to…
As the next generation of large galaxy surveys come online, it is becoming increasingly important to develop and understand the machine learning tools that analyze big astronomical data. Neural networks are powerful and capable of probing…
We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing ($\Delta\!\Sigma$) and projected galaxy clustering ($w_{\rm p}$) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and…