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Field emission coupled with molecular dynamics simulation (FEcMD) software package is a computational tool for studying the electron emission characteristics and the atomic structure evolution of micro- and nano-protrusions made of pure…

Computational Physics · Physics 2023-10-10 Nan Li , Xinyu Gao , Xianghui Feng , Kai Wu , Yonghong Cheng , Bing Xiao

Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-19 Stefano Corda , Gagandeep Singh , Ahsan Javed Awan , Roel Jordans , Henk Corporaal

Microgrids, self contained electrical grids that are capable of disconnecting from the main grid, hold potential in both tackling climate change mitigation via reducing CO2 emissions and adaptation by increasing infrastructure resiliency.…

Artificial Intelligence · Computer Science 2020-11-17 Gonzague Henri , Tanguy Levent , Avishai Halev , Reda Alami , Philippe Cordier

The study of complex many-body systems via analysis of the trajectories of the units that dynamically move and interact within them is a non-trivial task. The workflow for extracting meaningful information from the raw trajectory data is…

Materials Science · Physics 2025-10-31 Simone Martino , Matteo Becchi , Andrew Tarzia , Daniele Rapetti , Giovanni M. Pavan

The Medley setup is planned to be moved to and used at the new neutron facility NFS where measurements of light-ion production and fission cross-sections are planned at 1-40 MeV. Medley has eight detector telescopes providing Delta E-Delta…

Instrumentation and Detectors · Physics 2014-09-09 K. Jansson , C. Gustavsson , S. Pomp , A. V. Prokofiev , G. Scian , D. Tarrío , U. Tippawan

The high-performance computing resources and the constant improvement of both numerical simulation accuracy and the experimental measurements with which they are confronted, bring a new compulsory step to strengthen the credence given to…

Computation · Statistics 2019-03-01 J-B. Blanchard , G. Damblin , J-M. Martinez , G. Arnaud , F. Gaudier

In the third round of the NIST Post-Quantum Cryptography standardization project, the focus is on optimizing software and hardware implementations of candidate schemes. The winning schemes are CRYSTALS Kyber and CRYSTALS Dilithium, which…

Cryptography and Security · Computer Science 2023-08-15 Richard Sattel , Christoph Spang , Carsten Heinz , Andreas Koch

We present SynRXN, a unified benchmarking framework and open-data resource for computer-aided synthesis planning (CASP). SynRXN decomposes end-to-end synthesis planning into five task families, covering reaction rebalancing, atom-to-atom…

Machine Learning · Computer Science 2026-04-21 Tieu-Long Phan , Nhu-Ngoc Nguyen Song , Peter F. Stadler

Grand canonical Monte Carlo (GCMC) simulations are essential for screening metal-organic frameworks (MOFs) for gas adsorption, yet their accuracy is limited by underlying interatomic potentials. Universal machine-learned interatomic…

Materials Science · Physics 2026-02-17 Connor W. Edwards , Fengxu Yang , Konstantin Stracke , Jack D. Evans

The primary objective of SIRENE is to simulate the response to neutrino events of any type of high energy neutrino telescope. Additionally, it implements different geometries for a neutrino detector and different configurations and…

The purpose of nondestructive assay in the context of nuclear safeguards is to precisely verify the declared mass of a sample of nuclear material in a noninhibitive amount of time. 237Np is a proliferation concern, and the capacity to…

Instrumentation and Detectors · Physics 2020-10-15 Michael Y. Hua , Thomas A. Plummer , Jesson D. Hutchinson , George E. McKenzie , Shaun D. Clarke , Sara A. Pozzi

Purpose: Widespread adoption and methodological advancement of Magnetic Resonance Fingerprinting (MRF) are limited by the lack of unified, reproducible implementation frameworks and fragmented open-source tools. To address these barriers,…

Nanofluidic systems exploit nanometre-scale confinement in channels and pores to regulate ionic transport, enabling functionalities such as osmotic energy harvesting and neuromorphic ionic memory. Studying such confined transport requires…

Mesoscale and Nanoscale Physics · Physics 2026-02-03 Yichao Wang , Munan Fang , Aziz Roshanbhai Lokhandwala , Siddhi Vinayak Pandey , Boya Radha

This paper presents a parallel Monte Carlo simulation based performance quantification method for nonlinear model predictive control (NMPC) in closed-loop. The method provides distributions for the controller performance in stochastic…

Systems and Control · Electrical Eng. & Systems 2023-06-22 Morten Wahlgreen Kaysfeld , Mario Zanon , John Bagterp Jørgensen

Emerging two terminal nanoscale memory devices, known as memristors, have over the past decade demonstrated great potential for implementing energy efficient neuro-inspired computing architectures. As a result, a wide-range of technologies…

Emerging Technologies · Computer Science 2022-07-29 Jinqi Huang , Spyros Stathopoulos , Alex Serb , Themis Prodromakis

DL_MONTE is an open source, general-purpose software package for performing Monte Carlo simulations. It includes a wide variety of force fields and MC techniques, and thus is applicable to a broad range of problems in molecular simulation.…

We describe OHBA Software Library for the analysis of electrophysiological data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for magneto-/electro-encephalography (M/EEG)…

Quantitative Methods · Quantitative Biology 2024-10-30 Mats W. J. van Es , Chetan Gohil , Andrew J. Quinn , Mark W. Woolrich

The Feynman-alpha method is a neutron noise technique that is used to estimate the prompt neutron period of fissile assemblies. The method and quantity are of widespread interest including in applications such as nuclear criticality safety,…

Data Analysis, Statistics and Probability · Physics 2020-11-03 Michael Y. Hua , Jesson D. Hutchinson , George E. McKenzie , Shaun D. Clarke , Sara A. Pozzi

Multi-fidelity Monte Carlo (MFMC) is a variance reduction method that leverages a multi-fidelity ensemble of models of varying cost and accuracy levels. Constructing an MFMC estimator with optimal variance requires knowledge of the…

Methodology · Statistics 2026-05-25 Michael Stanley , Thomas Coons , Geoffrey Bomarito , Patrick Leser , Joshua Pribe , James Warner

Running complex sets of machine learning experiments is challenging and time-consuming due to the lack of a unified framework. This leaves researchers forced to spend time implementing necessary features such as parallelization, caching,…

Machine Learning · Computer Science 2023-11-22 Zac Pullar-Strecker , Xinglong Chang , Liam Brydon , Ioannis Ziogas , Katharina Dost , Jörg Wicker
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