Related papers: MG-NECOLA: Fast Neural Emulators for Modified Grav…
In this work, we introduce TUNeS (Temporal UNet emulator for Structure formation), a neural network framework for accelerating N-body simulations by predicting the nonlinear evolution of the matter density field from an initial particle…
Weak gravitational lensing mass maps play a crucial role in understanding the evolution of structures in the universe and our ability to constrain cosmological models. The prediction of these mass maps is based on expensive N-body…
Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a…
We make use of snapshots taken from the Quijote suite of simulations, consisting of 2000 simulations where five cosmological parameters have been varied ($\Omega_m$, $\Omega_b$, $h$, $n_s$ and $\sigma_8$) in order to investigate the…
Several models based on General Relativity and Modified Gravity aim to reproduce the observed universe with precision comparable to the flat-$\Lambda$CDM cosmological model. In this study, we investigate the consistency of some of these…
A class of Modified Gravity Models, consisting of inverse powers of linear combination of quadratic curvature invariants, is studied in the full parameter space. We find that singularity-free cosmological solutions, interpolating between an…
Large language model (LLM) training today runs on clusters spanning thousands of GPUs. While this scale enables rapid model advances, developing, debugging, and performance-tuning the training framework inevitably becomes complex and…
Soft, porous mechanical metamaterials exhibit pattern transformations that may have important applications in soft robotics, sound reduction and biomedicine. To design these innovative materials, it is important to be able to simulate them…
This paper presents a novel approach for accelerating n-body simulations by integrating a physics-informed graph neural networks (GNN) with traditional numerical methods. Our method implements a leapfrog-based simulation engine to generate…
Upcoming Large Scale Structure surveys aim to achieve an unprecedented level of precision in measuring galaxy clustering. However, accurately modeling these statistics may require theoretical templates that go beyond second-order…
McMule, a Monte Carlo for MUons and other LEptons, implements many major QED processes at NNLO (eg. $ee\to ee$, $e\mu\to e\mu$, $ee\to\mu\mu$, $\ell p\to\ell p$, $\mu\to\nu\bar\nu e$) including effects from the lepton masses, making it…
The study of massive neutrinos and their interactions is a critical aspect of contemporary cosmology. Recent advances in parallel computation and high-performance computing provide new opportunities for accurately constraining Large-Scale…
We present a methodology for constructing modified gravity (MG) constrained simulations of the local Universe using positions and peculiar velocities from the CosmicFlows data set. Our analysis focuses on the following MG models: the normal…
Meshes are used to represent complex objects in high fidelity physics simulators across a variety of domains, such as radar sensing and aerodynamics. There is growing interest in using neural networks to accelerate physics simulations, and…
Cosmological N-body simulations are done on massively parallel computers. This necessitates the use of simple time integrators, and, additionally, of mesh-grid approximations of the potentials. Recently, Adamek et al. (2015);…
In cosmology, emulators play a crucial role by providing fast and accurate predictions of complex physical models, enabling efficient exploration of high-dimensional parameter spaces that would be computationally prohibitive with direct…
Neural network potentials (NNPs) offer a fast and accurate alternative to ab-initio methods for molecular dynamics (MD) simulations but are hindered by the high cost of training data from high-fidelity Quantum Mechanics (QM) methods. Our…
Low-energy experiments allow for some of the most precise measurements in particle physics, such as $g-2$. To make the most of these experiments, theory needs to match the experimental precision. Over the last decade, this meant that even…
Single-$\Lambda$ hypernuclei are the most straightforward extension of atomic nuclei. A thorough description of baryonic system beyond first-generation quark sector is indispensable for the maturation of nuclear $ab$ $initio$ methods. This…
Simulating collisions of deformable objects is a fundamental yet challenging task due to the complexity of modeling solid mechanics and multi-body interactions. Existing data-driven methods often suffer from lack of equivariance to physical…