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Context. Weak lensing and clustering statistics beyond two-point functions can capture non-Gaussian information about the matter density field, thereby improving the constraints on cosmological parameters relative to the mainstream methods…
Logic regression was developed more than a decade ago as a tool to construct predictors from Boolean combinations of binary covariates. It has been mainly used to model epistatic effects in genetic association studies, which is very…
Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy…
We implement a model for the two-point statistics of biased tracers that combines dark matter dynamics from $N$-body simulations with an analytic Lagrangian bias expansion. Using Aemulus, a suite of $N$-body simulations built for emulation…
We present CLUMI+, a self-consistent, multiprobe methodology for reconstructing the mass distribution in and around galaxy clusters by combining gravitational lensing and dynamical observations. Building on the joint likelihood framework of…
We explore strategies to extract cosmological constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing, galaxy clustering, cluster number counts and cluster weak lensing. We utilize the CosmoLike software to simulate results…
We outline a simple procedure designed for \emph{automatically} finding sets of multiple images in strong lensing (SL) clusters. We show that by combining (a) an arc-finding (or source extracting) program, (b) photometric redshift…
Samples of galaxy clusters allow us to better understand the physics at play in galaxy formation and to constrain cosmological models once their mass, position (for clustering studies) and redshift are known. In this context, large optical…
Upcoming galaxy surveys will allow us to probe the growth of the cosmic large-scale structure with improved sensitivity compared to current missions, and will also map larger areas of the sky. This means that in addition to the increased…
Galaxy clusters have their unique advantages for cosmology. Here we collect a new sample of 10 lensing galaxy clusters with X-ray observations to constrain cosmological parameters.The redshifts of lensing clusters lie between 0.1 and 0.6,…
Luminous red galaxies (LRGs) are one of the key tracers of the large-scale structure of the Universe used by galaxy surveys. Hence, it is important to make accurate predictions for their properties and clustering, including the errors on…
We present an analysis of the small-to-intermediate scale clustering of samples of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey and the 2dF-SDSS LRG and QSO (2SLAQ) survey carefully matched to have the same rest-frame…
We study the impact of lensing magnification on the observed three-dimensional galaxy clustering in redshift space. We used the RayGal suite of N-body simulations, from which we extracted samples of dark matter particles and haloes in the…
Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control…
The ancestral recombination graph (ARG) is the model of choice in statistical genetics to model population ancestries. Software capable of simulating ARGs on a genome scale within a reasonable amount of time are now widely available for…
Probing dark matter distribution on sub-galactic scales is essential for testing the Cold Dark Matter ($\Lambda$CDM) paradigm. Strong gravitational lensing, as one of the most powerful approach by far, provides a direct, purely…
Combustion kinetic modeling is an integral part of combustion simulation, and extensive studies have been devoted to developing both high fidelity and computationally affordable models. Despite these efforts, modeling combustion kinetics is…
We present DataDeps.jl: a julia package for the reproducible handling of static datasets to enhance the repeatability of scripts used in the data and computational sciences. It is used to automate the data setup part of running software…
Proprietary closed-source software is still the norm in advanced process control. Transparency and reproducibility are key aspects of scientific research. Free and open-source toolkit can contribute to the development, sharing and…
We present the v1.0 release of CLMM, an open source Python library for the estimation of the weak lensing masses of clusters of galaxies. CLMM is designed as a standalone toolkit of building blocks to enable end-to-end analysis pipeline…