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Introducing a reduced particle stiffness in discrete element method (DEM) allows for bigger time steps and therefore fewer total iterations in a simulation. Although this approach works well for dry non-adhesive particles, it has been shown…

Soft Condensed Matter · Physics 2018-10-17 Sheng Chen , Wenwei Liu , Shuiqing Li

We present the results of cosmological simulations of large-scale structure formation with massive neutrinos. The phase-space distribution of the cosmic relic neutrinos is followed, for the first time, by directly integrating the…

Cosmology and Nongalactic Astrophysics · Physics 2020-12-09 Kohji Yoshikawa , Satoshi Tanaka , Naoki Yoshida , Shun Saito

We investigate a hybrid numerical algorithm aimed at the large-scale cosmological N-body simulation for the on-going and the future high precious sky surveys. It makes use of a truncated Fast Multiple Method (FMM) for short-range gravity,…

Computational Physics · Physics 2021-01-13 Qiao Wang

We discuss an implementation of a deep learning framework to gain insight into dark matter (DM) structure formation. We investigate the contribution of velocity and density field information to the construction of the halo mass function…

Cosmology and Nongalactic Astrophysics · Physics 2025-02-13 Saba Etezad-Razavi , Erfan Abbasgholinejad , Mohammad-Hadi Sotoudeh , Farbod Hassani , Sadegh Raeisi , Shant Baghram

The set-up of the initial conditions in cosmological N-body simulations is usually implemented by rescaling the desired low-redshift linear power spectrum to the required starting redshift consistently with the Newtonian evolution of the…

Cosmology and Nongalactic Astrophysics · Physics 2017-01-18 Matteo Zennaro , Julien Bel , Francisco Villaescusa-Navarro , Carmelita Carbone , Emiliano Sefusatti , Luigi Guzzo

An adpative integration technique for time advancement of particle motion in the context of coupled computational fluid dynamics (CFD) - discrete element method (DEM) simulations is presented in this work. CFD-DEM models provide an accurate…

Computational Physics · Physics 2018-02-28 Hariswaran Sitaraman , Ray Grout

Particle-in-cell methods with stochastic collision models are commonly used to simulate collisional plasma dynamics, with applications ranging from hypersonic flight to semiconductor manufacturing. Code verification of such methods is…

Computational Physics · Physics 2026-05-26 Brian A. Freno , William J. McDoniel , Christopher H. Moore , Neil R. Matula

A novel multiscale numerical method is developed to accelerate direct simulation Monte Carlo (DSMC) simulations for polyatomic gases with internal energy. This approach applies the general synthetic iterative scheme to stochastic…

Computational Physics · Physics 2025-01-22 Liyan Luo , Tao Huang , Qi Li , Lei Wu

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…

Materials Science · Physics 2022-09-07 Bastien F. Grosso , Nicola A. Spaldin , Aria Mansouri Tehrani

Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…

Machine Learning · Computer Science 2025-10-03 Hung Le , Sherif Abbas , Minh Hoang Nguyen , Van Dai Do , Huu Hiep Nguyen , Dung Nguyen

In this era of precision cosmology, a detailed physical understanding on the evolution of cosmic baryons is required. Cosmic magnetic fields, though still poorly understood, may represent an important component in the global cosmic energy…

Astrophysics · Physics 2015-06-24 Shengtai Li , Hui Li , Renyue Cen

We present a method to numerically estimate the densities of a discretely sampled data based on binary space partitioning tree. We start with a root node containing all the particles and then recursively divide each node into two nodes each…

Astrophysics · Physics 2015-06-24 Sanjib Sharma , Matthias Steinmetz

The standard cold dark matter (CDM) model predicts too many and too dense small structures. We consider an alternative model that the dark matter undergoes two-body decays with cosmological lifetime $\tau$ into only one type of massive…

Cosmology and Nongalactic Astrophysics · Physics 2015-11-04 Dalong Cheng , M. -C. Chu , Jiayu Tang

The paper describes the coupling of the MercuryDPM discrete element method (DEM) code and the implementation of the kernel-independent fast multipole method (KIFMM). The combined simulation framework allows addressing the large class of…

Soft Condensed Matter · Physics 2025-12-11 Igor A. Ostanin

The Universe at the present epoch is found to be a network of matter over-dense and under-dense regions. To date, this picture of the Universe is best revealed through cosmological large-volume simulations and large-scale galaxy redshift…

Cosmology and Nongalactic Astrophysics · Physics 2023-11-28 Prateek Gupta , Surajit Paul

Large-scale cosmological simulations are an indispensable tool for modern cosmology. To enable model-space exploration, fast and accurate predictions are critical. In this paper, we show that the performance of such simulations can be…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-08 Florian List , Oliver Hahn

Cosmological perturbation theory is a powerful tool to predict the statistics of large-scale structure in the weakly non-linear regime, but even at 1-loop order it results in computationally expensive mode-coupling integrals. Here we…

Cosmology and Nongalactic Astrophysics · Physics 2017-02-17 Xiao Fang , Jonathan A. Blazek , Joseph E. McEwen , Christopher M. Hirata

We propose an analytic model, CuspCore II, for the response of dark matter (DM) haloes to central gas ejection, as a mechanism for generating DM-deficient cores in dwarfs and high-z massive galaxies. We test this model and three other…

Astrophysics of Galaxies · Physics 2023-04-10 Zhaozhou Li , Avishai Dekel , Nir Mandelker , Jonathan Freundlich , Thibaut François

Recent probabilistic methods for 3D triangular meshes capture diverse shapes by differentiable mesh connectivity, but face high computational costs with increased shape details. We introduce a new differentiable mesh processing method that…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Sanghyun Son , Matheus Gadelha , Yang Zhou , Matthew Fisher , Zexiang Xu , Yi-Ling Qiao , Ming C. Lin , Yi Zhou

We present new results characterizing cosmological shocks within adaptive mesh refinement N-Body/hydrodynamic simulations that are used to predict non-thermal components of large-scale structure. This represents the first study of shocks…