Related papers: Analytic Gaussian Covariance Matrices for Galaxy $…
We perform a blinded cosmology analysis with cosmic shear two-point correlation functions (2PCFs) measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from…
Higher-order statistics are a useful and complementary tool for measuring the clustering of galaxies, containing information on the non-gaussian evolution and morphology of large-scale structure in the Universe. In this work we present…
Neural-net-induced Gaussian process (NNGP) regression inherits both the high expressivity of deep neural networks (deep NNs) as well as the uncertainty quantification property of Gaussian processes (GPs). We generalize the current NNGP to…
We present an axially symmetric formula to calculate the probability of finding gravitational arcs in galaxy clusters, being induced by their massive dark matter haloes, as a function of clusters redshifts and virial masses. The formula…
We present an optimised multipole algorithm for computing the three-point correlation function (3PCF), tailored for application to large-scale cosmological datasets. The algorithm builds on a $in\, situ$ interpretation of correlation…
We use the full-sky ray-tracing weak lensing simulations to generate 2268 mock catalogues for the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalogue. Our mock catalogues take into account various effects as in the real data:…
Gaussian processes (GPs) are crucial in machine learning for quantifying uncertainty in predictions. However, their associated covariance matrices, defined by kernel functions, are typically dense and large-scale, posing significant…
We present new measurements of the redshift-space three-point correlation function (3PCF) of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS). Using the largest dataset to date, the Data Release 7 (DR7) LRGs, and an…
New arguments supporting the reality of large-scale fluctuations in the density of the visible matter in deep galaxy surveys are presented. A statistical analysis of the radial distributions of galaxies in the COSMOS and HDF-N deep fields…
We model the two-point correlation function of galaxies in a cold dark matter Universe by combining two powerful theoretical tools - dissipationless N-body simulations of dark matter clustering (specifically the GIF simulations carried out…
In this study, we introduce a novel analytical Gaussian Process (GP) cosmography methodology, leveraging the differentiable properties of GPs to derive key cosmological quantities analytically. Our approach combines cosmic chronometer (CC)…
In order to quantify higher-order correlations of the galaxy cluster distribution we use a complete family of additive measures which give scale-dependent morphological information. Minkowski functionals can be expressed analytically in…
Cosmological parameter estimation requires that the likelihood function of the data is accurately known. Assuming that cosmological large-scale structure power spectra data are multivariate Gaussian-distributed, we show the accuracy of…
We discuss the galaxy-galaxy-mass three-point correlation function and show how to measure it with weak gravitational lensing. The method entails choosing a large of pairs of foreground lens galaxies and constructing a mean shear map with…
We study linear spectral statistics of high dimensional sample covariance matrices in a regime where the empirical spectral distribution remains governed by the classical sample covariance law but the fluctuation theory is nonclassical. Our…
We consider the shape of the posterior distribution to be used when fitting cosmological models to power spectra measured from galaxy surveys. At very large scales, Gaussian posterior distributions in the power do not approximate the…
In Gaussian graphical models, the likelihood equations must typically be solved iteratively. We investigate two algorithms: A version of iterative proportional scaling which avoids inversion of large matrices, and an algorithm based on…
We present a framework for inferring the dark matter halo masses of quasars and [O III]-emitting galaxies from JWST/NIRCam Wide Field Slitless Spectroscopy (WFSS) clustering measurements at z approximately 6. Using the FLAMINGO-10k N-body…
We introduce a new galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes), to provide full posterior probability distributions and reliable confidence intervals for all model parameters. GALPHAT is designed to yield a high…
The definition and the properties of a Gaussian point distribution, in contrast to the well-known properties of a Gaussian random field are discussed. Constraints for the number density and the two-point correlation function arise. A simple…