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We apply to the nucleon-nucleus inelastic process a fully coherent microscopic multiple scattering approach. Our study addresses the complexities inherent in characterizing inelastic scattering events, offering a comprehensive theoretical…

Nuclear Theory · Physics 2026-03-30 Matteo Vorabbi , Michael Gennari , Paolo Finelli , Carlotta Giusti , Petr Navrátil

In this paper, we address the problem of efficient execution of a computation pattern, referred to here as the irregular wavefront propagation pattern (IWPP), on hybrid systems with multiple CPUs and GPUs. The IWPP is common in several…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-18 George Teodoro , Tony Pan , Tahsin Kurc , Jun Kong , Lee Cooper , Joel Saltz

In this paper, we use a straightforward numerical method to solve scattering models in one-dimensional lattices based on a tight-binding band structure. We do this by using the wave packet approach to scattering, which presents a more…

Physics Education · Physics 2022-07-06 M. Staelens , F. Marsiglio

This paper focuses on the parallel implementation of a direct $N$-body method~(particle-particle algorithm) and the application of multiple GPUs for galactic dynamics simulations. Application of a hybrid OpenMP-CUDA technology is considered…

Computational Physics · Physics 2018-03-06 S. S. Khrapov , S. A. Khoperskov , A. V. Khoperskov

Modern nuclear data evaluation increasingly requires not only accurate scattering calculations, but also efficient methods for uncertainty quantification and parameter optimization, tasks that benefit from differentiable solvers amenable to…

Nuclear Theory · Physics 2026-05-28 Jin Lei

We present a novel scattering emulator utilizing the complex scaling method to enhance nuclear reaction analysis. This approach leverages a single set of reduced bases, allowing for efficient and simultaneous emulation across multiple…

Nuclear Theory · Physics 2024-10-24 Junzhe Liu , Jin Lei , Zhongzhou Ren

In this work, we consider the approximation of parametric maps using the so-called Galerkin POD-NN method. This technique combines the computation of a reduced basis via proper orthogonal decomposition (POD) and artificial neural networks…

Numerical Analysis · Mathematics 2025-10-31 Jürgen Dölz , Fernando Henríquez

Nucleon-deuteron ($Nd$) scattering can be used to constrain three-nucleon forces in chiral effective field theory ($\chi$EFT). However, high-fidelity calculations, such as the Hyperspherical Harmonic (HH) method, are computationally…

The nonrelativistic full-folding optical model approach for nucleon-nucleus scattering is extended into the relativistic regime. In doing so, kinematical issues involving the off-shell Lorentz boost of the colliding particles between the…

Nuclear Theory · Physics 2009-11-07 H. F. Arellano , H. V. von Geramb

Electromagnetic scattering and absorption by material particles is a fundamental physical problem with a broad range of applications, going from laboratory experiments, biology and material sciences, all the way up to environmental studies…

Instrumentation and Methods for Astrophysics · Physics 2026-02-06 G. La Mura , G. Mulas , G. Aresu , M. A. Iatì , C. Cecchi-Pestellini , S. Rezaei , R. Saija

A paramount goal in the field of nuclear physics is to unify ab-initio treatments of bound and unbound states. The position-space quantum Monte Carlo (QMC) methods have a long history of successful bound state calculations in light systems…

Nuclear Theory · Physics 2023-08-29 Abraham R. Flores , Kenneth M. Nollett

Error correction is a significant step in postprocessing of continuous-variable quantum key distribution system, which is used to make two distant legitimate parties share identical corrected keys. We propose an experiment demonstration of…

Quantum Physics · Physics 2018-07-17 Xiangyu Wang , Yi-Chen Zhang , Song Yu , Hong Guo

The article discusses the correctness of the assumption about the similarity of molecular continuum electron functions with wave functions in electron-atom scattering. The elastic scattering of slow particles by pair of non-overlapping…

Atomic Physics · Physics 2022-08-01 A. S. Baltenkov , I. Woiciechowski

This paper focuses on the scaling of the S-matrix for elastic nucleon-nucleon scattering at large Nc. It is argued that the logarithm of a typical S-matrix element is proportional to Nc in the regime where the large Nc limit is taken with…

Nuclear Theory · Physics 2013-11-20 Thomas D. Cohen , Vojtěch Krejčiřík

We present an approach to simulate the 3D isotropic elastic wave propagation using nonuniform finite difference discretization on staggered grids. Specifically, we consider simulation domains composed of layers of uniform grids with…

Numerical Analysis · Mathematics 2022-09-13 Longfei Gao , Omar Ghattas , David Keyes

As edge applications using convolutional neural networks (CNN) models grow, it is becoming necessary to introduce dedicated hardware accelerators in which network parameters and feature-map data are represented with limited precision. In…

Neural and Evolutionary Computing · Computer Science 2018-11-01 Doyun Kim , Han Young Yim , Sanghyuck Ha , Changgwun Lee , Inyup Kang

Wave packet molecular dynamics (WPMD) has recently received a lot of attention as a computationally fast tool to study dynamical processes in warm dense matter beyond the Born-Oppenheimer approximation. These techniques, typically, employ…

Plasma Physics · Physics 2021-04-09 William A. Angermeier , Thomas G. White

In this note, the importance of spectral properties of viscous flux discretization in solving compressible Navier-Stokes equations for turbulent flow simulations is discussed. We studied six different methods, divided into two different…

We introduce a charge coupled device (CCD) camera based detection scheme in dynamic light scattering that provides information on the single-scattered auto-correlation function even for fairly turbid samples. It is based on the single…

Soft Condensed Matter · Physics 2009-11-11 Pavel Zakharov , Suresh Bhat , Peter Schurtenberger , Frank Scheffold

The large computing and memory cost of deep neural networks (DNNs) often precludes their use in resource-constrained devices. Quantizing the parameters and operations to lower bit-precision offers substantial memory and energy savings for…

Machine Learning · Computer Science 2023-09-01 Clemens JS Schaefer , Siddharth Joshi , Shan Li , Raul Blazquez