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In this study, by attempting to eliminate the disadvantageous complexity of the existing particle generators, we present a discrete probabilistic scheme adapted for the discrete energy spectra in the GEANT4 simulations. In our multi-binned…

Computational Physics · Physics 2023-02-17 Ahmet Ilker Topuz , Madis Kiisk

Microscopic processes on surfaces such as adsorption, desorption, diffusion and reaction of interacting particles can be simulated using kinetic Monte Carlo (kMC) algorithms. Even though kMC methods are accurate, they are computationally…

Mathematical Physics · Physics 2013-12-24 Yannis Pantazis , Markos Katsoulakis

Exact stochastic simulation of continuous-time Markov chains (CTMCs) is essential when discreteness and noise drive system behavior, but the hard categorical event selection in Gillespie-type algorithms blocks gradient-based learning. We…

Quantitative Methods · Quantitative Biology 2026-02-24 Jose M. G. Vilar , Leonor Saiz

In this paper we investigate, with a detailed Monte-Carlo simulation based on Geant4, the novel approach [Nucl. Instrum. Methods A588 (2008) 457] to 3D imaging with photon scattering. A monochromatic and well collimated gamma beam is used…

Medical Physics · Physics 2011-09-23 M. Lenti , M. Veltri

We develop a coarse grained (CG) approach for efficiently simulating calcium dynamics in the endoplasmic reticulum membrane based on a fine stochastic lattice gas model. By grouping neighboring microscopic sites together into CG cells and…

Chemical Physics · Physics 2015-06-15 Chuansheng Shen , Hanshuang Chen

We independently develop a simulation code following the previous dynamical Monte Carlo simulation of the diffusive shock acceleration under the isotropic scattering law during the scattering process, and the same results are obtained.…

Earth and Planetary Astrophysics · Physics 2015-05-20 Xin Wang , Yihua Yan

A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is…

Computer Vision and Pattern Recognition · Computer Science 2015-05-27 Guoshen Yu , Guillermo Sapiro

The Simplified General Perturbations 4 (SGP4) orbital propagation method is widely used for predicting the positions and velocities of Earth-orbiting objects rapidly and reliably. Despite continuous refinement, SGP models still lack the…

Machine Learning · Computer Science 2024-11-22 Giacomo Acciarini , Atılım Güneş Baydin , Dario Izzo

Geant4, the leading detector simulation toolkit used in high energy physics, employs a set of physics models to simulate interactions of particles with matter across a wide range of energies. These models, especially the hadronic ones, rely…

High Energy Physics - Experiment · Physics 2023-09-25 Krzysztof Genser , Soon Yung Jun , Alberto Ribon , Vladimir Uzhinsky , Julia Yarba

The molecular dynamics (MD) simulation technique has been widely used in complex systems, but the accessible time scale is limited due to the requirement of small integration timesteps. Here, we propose a novel method, named Exploratory…

Computational Physics · Physics 2025-09-17 Hai-Ming Cao , Bin Li

This paper tackles the pressing challenge of mutagenicity prediction by introducing three ground-breaking approaches. First, it showcases the superior performance of 2D scattering coefficients extracted from molecular images, compared to…

Machine Learning · Computer Science 2024-11-26 Abdeljalil Zoubir , Badr Missaoui

A new computational algorithm, the discrete singular convolution (DSC), is introduced for computational electromagnetics. The basic philosophy behind the DSC algorithm for the approximation of functions and their derivatives is studied.…

Numerical Analysis · Mathematics 2025-10-20 G. W. Wei

Reconstructing dynamic 3D scenes with photorealistic detail and strong temporal coherence remains a significant challenge. Existing Gaussian splatting approaches for dynamic scene modeling often rely on per-frame optimization, which can…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Tingxuan Huang , Haowei Zhu , Jun-hai Yong , Hao Pan , Bin Wang

In order to minimize the emittance at the Cornell Electron Storage Ring (CESR), we measure and correct the orbit, dispersion, and transverse coupling of the beam. However, this method is limited by finite measurement resolution of the…

Accelerator Physics · Physics 2017-05-24 William F. Bergan , Adam C. Bartnik , Ivan V. Bazarov , He He , David L. Rubin , James P. Sethna

The Geant4 toolkit offers a rich variety of electromagnetic physics models; so far the evaluation of this Geant4 domain has been mostly focused on its physics functionality, while the features of its design and their impact on simulation…

We develop the extended dynamical mean field theory (E-DMFT) with a view towards realistic applications. {\bf 1)} We introduce an intuitive derivation of the E-DMFT formalism. By identifying the Hartree contributions before the E-DMFT…

Strongly Correlated Electrons · Physics 2009-11-07 Ping Sun , Gabriel Kotliar

We present an efficient implementation of periodic Gaussian density fitting (GDF) using the Coulomb metric. The three-center integrals are divided into two parts by range-separating the Coulomb kernel, with the short-range part evaluated in…

Chemical Physics · Physics 2021-04-08 Hong-Zhou Ye , Timothy C. Berkelbach

We study the problem of computationally efficient robust estimation of the covariance/scatter matrix of elliptical distributions -- that is, affine transformations of spherically symmetric distributions -- under the strong contamination…

Data Structures and Algorithms · Computer Science 2025-04-15 Gleb Novikov

Accurate and high-resolution Earth system model (ESM) simulations are essential to assess the ecological and socio-economic impacts of anthropogenic climate change, but are computationally too expensive to be run at sufficiently high…

Atmospheric and Oceanic Physics · Physics 2025-02-27 Philipp Hess , Michael Aich , Baoxiang Pan , Niklas Boers

Gaussian Quantum Monte Carlo (GQMC) is a stochastic phase space method for fermions with positive weights. In the example of the Hubbard model close to half filling it fails to reproduce all the symmetries of the ground state leading to…

Strongly Correlated Electrons · Physics 2008-03-04 P. Corboz , A. Kleine , F. F. Assaad , I. P. McCulloch , U. Schollwöck , M. Troyer