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Deep learning systems extensively use convolution operations to process input data. Though convolution is clearly defined for structured data such as 2D images or 3D volumes, this is not true for other data types such as sparse point…

Computer Vision and Pattern Recognition · Computer Science 2018-09-26 Pedro Hermosilla , Tobias Ritschel , Pere-Pau Vázquez , Àlvar Vinacua , Timo Ropinski

Coherent elastic neutrino-nucleus scattering (CEvNS) provides a well-defined framework for studying nuclear recoil observables in low-energy neutrino interactions. In this work, we present a comparative Monte Carlo benchmark study of…

High Energy Physics - Experiment · Physics 2026-02-05 Yusuf Havvat

Automatic design of organic materials requires black-box optimization in a vast chemical space. In conventional molecular design algorithms, a molecule is built as a combination of predetermined fragments. Recently, deep neural network…

Chemical Physics · Physics 2018-06-27 Xiufeng Yang , Jinzhe Zhang , Kazuki Yoshizoe , Kei Terayama , Koji Tsuda

The ELIMED (MEDical and multidisciplinary application at ELI Beamlines) beam line is being developed at INFN-LNS with the aim of transporting and selecting in energy proton and ion beams accelerated by laser-matter interaction at ELI…

One of the most computationally demanding aspects of the hydrodynamical modelling of Astrophysical phenomena is the transport of energy by radiation or relativistic particles. Physical processes involving energy transport are ubiquitous and…

Instrumentation and Methods for Astrophysics · Physics 2018-04-04 Darren S. Reed , Tim Dykes , Ruben Cabezon , Claudio Gheller , Lucio Mayer

Charged and neutral current low energy neutrino cross section predictions from a variety of Monte Carlo generators in present use are compared against existing experimental data. Comparisons are made to experimental data on quasi-elastic,…

High Energy Physics - Experiment · Physics 2007-05-23 G. P. Zeller

Simulations of neutron background from rock for underground experiments are presented. Neutron propagation through two types of rock, lead and hydrocarbon material is discussed. The results show a reasonably good agreement between GEANT4,…

High Energy Physics - Experiment · Physics 2009-11-11 R. Lemrani , M. Robinson , V. A. Kudryavtsev , M. De Jesus , G. Gerbier , N. J. C. Spooner

During the last decades, neutron beam transportation has been a well-known and established subject for designing proper neutron guides. However, sometimes unusual adaptation or adjustments are required out of original projects and after…

Instrumentation and Detectors · Physics 2022-03-29 Alexandre P. S. Souza , Luiz P. de Oliveira , Frederico A. Genezini

A faithful description of chemical processes requires exploring extended regions of the molecular potential energy surface (PES), which remains challenging for strongly correlated systems. Transferable deep-learning variational Monte Carlo…

Chemical Physics · Physics 2026-03-27 P. Bernát Szabó , Zeno Schätzle , Frank Noé

High-energy physics simulations traditionally rely on classical Monte Carlo methods to model complex particle interactions, often incurring significant computational costs. In this paper, we introduce a novel quantum-enhanced simulation…

Quantum Physics · Physics 2025-02-28 Euimin Lee , Sangmin Lee , Shiho Kim

We developed a Monte Carlo event generator for production of nucleon configurations in complex nuclei consistently including effects of Nucleon-Nucleon (NN) correlations. Our approach is based on the Metropolis search for configurations…

Nuclear Theory · Physics 2013-05-14 M. Alvioli , H. -J. Drescher , M. Strikman

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying…

Accurate numerical integration over non-uniform point clouds is a challenge for modern mesh-free machine learning solvers for partial differential equations (PDEs) using variational principles. While standard Monte Carlo (MC) methods are…

Numerical Analysis · Mathematics 2026-02-10 Costas Smaragdakis

For a number of applications like low-source reactor start-up or neutron coincidence counting it is necessary to take into account the stochastic nature of neutron transport and go beyond the average neutron density, which is solution of a…

Computational Physics · Physics 2024-12-04 Philippe Humbert

We present the Monte Carlo integration code MoCaNLO, which computes cross sections and distributions for processes at high-energy colliders like the LHC at leading and next-to-leading order (NLO) in the strong and electroweak couplings. It…

High Energy Physics - Phenomenology · Physics 2026-02-24 A. Denner , D. Lombardi , S. Lopez Portillo Chavez , M. Pellen , G. Pelliccioli

The simulation of radioactive decays is a common task in Monte-Carlo systems such as Geant4. Usually, a system either uses an approach focusing on the simulations of every individual decay or an approach which simulates a large number of…

The Geant4-DNA project proposes to develop an open-source simulation software based and fully included in the general-purpose Geant4 Monte Carlo simulation toolkit. The main objective of this software is to simulate biological damages…

An algorithm has been developed for the Geant4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in…

Computational Physics · Physics 2009-11-10 Marcus H. Mendenhall , Robert A. Weller

We introduce a new code for cosmological simulations, PHoToNs, which has features on performing massive cosmological simulations on heterogeneous high performance Computer (HPC) and threads oriented programming. PHoToNs adopts a hybrid…

Cosmology and Nongalactic Astrophysics · Physics 2018-06-13 Qiao Wang , Zongyan Cao , Liang Gao , Xuebin Chi , Chen Meng , Jie Wang , Long Wang

Reliable predictions of weak rapid neutron capture ($\textit{r}$-process) abundances require a systematic treatment of nuclear physics uncertainties, especially neutron capture rates far from stability. We employ new neutron capture rates…