Abstract The standard Λ Cold Dark Matter (ΛCDM) cosmological model provides a good
description of a wide range of astrophysical and cosmological data. However, there are a …

An array of large observational programs using ground-based and space-borne telescopes
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …

We develop a general approach to distill symbolic representations of a learned deep model
by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The …

We present the public data release of the AbacusSummit cosmological N-body simulation
suite, produced with the Abacus N-body code on the Summit supercomputer of the Oak …

The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations -
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We present cosmological constraints from a simulation-based inference (SBI) analysis of
galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the …

With recent evidence for a possible 'curvature tension'among early and late universe
cosmological probes, Effective Field Theories of Large Scale Structure (EFTofLSS) have …

Optimal extraction of the non-Gaussian information encoded in the large-scale structure of
the Universe lies at the forefront of modern precision cosmology. We propose achieving this …

We investigate the exponential f (Q) symmetric teleparallel gravitation, namely using ME-
GADGET code to probe the structure formation with box sizes L Box= 10/100 Mpc h–1 and …

The use of summary statistics beyond the two-point correlation function to analyse the non-
Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying …