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As intelligent systems and multi-agent coordination become increasingly central to real-world applications, there is a growing need for simulation tools that are both scalable and accessible. Existing high-fidelity simulators, while…

Artificial Intelligence · Computer Science 2026-02-06 Rohan Patil , Jai Malegaonkar , Xiao Jiang , Andre Dion , Gaurav S. Sukhatme , Henrik I. Christensen

Atomic-scale simulations have progressed tremendously over the past decade, largely due to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the…

MFEM is an open-source, lightweight, flexible and scalable C++ library for modular finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretization approaches and…

The rapid advancement of AI, particularly large language models (LLMs), has raised significant concerns about the energy use and carbon emissions associated with model training and inference. However, existing tools for measuring and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-31 Hongzhen Huang , Kunming Zhang , Hanlong Liao , Kui Wu , Guoming Tang

NASA's Meteoroid Engineering Model (MEM) is designed to provide aerospace engineers with an accurate description of potentially hazardous meteoroids. It accepts a spacecraft trajectory as input and its output files describe the flux, speed,…

Earth and Planetary Astrophysics · Physics 2024-05-15 Althea V. Moorhead , Katie Milbrandt , Aaron Kingery

Recent advances in robotic mobile manipulation have spurred the expansion of the operating environment for robots from constrained workspaces to large-scale, human environments. In order to effectively complete tasks in these spaces, robots…

Robotics · Computer Science 2023-03-27 Cameron Kisailus , Daksh Narang , Matthew Shannon , Odest Chadwicke Jenkins

Extracellular matrix (ECM) remodeling is central to a wide variety of healthy and diseased tissue processes. Unfortunately, predicting ECM remodeling under various chemical and mechanical conditions has proven to be excessively challenging,…

Molecular Networks · Quantitative Biology 2026-05-26 Hasi Hays , William J. Richardson

Training sophisticated machine learning (ML) models requires large datasets that are difficult or expensive to collect for many applications. If prior knowledge about system dynamics is available, mechanistic representations can be used to…

Multiplexed imaging data are revolutionizing our understanding of the composition and organization of tissues and tumors. A critical aspect of such tissue profiling is quantifying the spatial relationship relationships among cells at…

Quantitative Methods · Quantitative Biology 2024-05-06 Ajit J. Nirmal , Peter K. Sorger

LevelScheme is a scientific figure preparation system for Mathematica. The main emphasis is upon the construction of level schemes, or level energy diagrams, as used in nuclear, atomic, molecular, and hadronic physics. LevelScheme also…

Computational Physics · Physics 2007-05-23 M. A. Caprio

Short Read Alignment Mapping Metrics (SRAMM): is an efficient and versatile command line tool providing additional short read mapping metrics, filtering, and graphs. Short read aligners report MAPing Quality (MAPQ), but these methods…

Genomics · Quantitative Biology 2021-07-08 Alvin Chon , Xiaoqiu Huang

Software Engineering and the implementation of software has become a challenging task as many tools, frameworks and languages must be orchestrated into one functioning piece. This complexity increases the need for testing and analysis…

Software Engineering · Computer Science 2018-06-27 Hannes Thaller

We present work flows and a software module for machine learning model building in surface science and heterogeneous catalysis. This includes fingerprinting atomic structures from 3D structure and/or connectivity information, it includes…

The udkm1Dsim toolbox is a collection of Python classes and routines to simulate the thermal, structural, and magnetic dynamics after laser excitation as well as the according X-ray scattering response in one-dimensional sample structures.…

Computational Physics · Physics 2021-05-31 Daniel Schick

Time- and frequency resolved optical signals provide insights into the properties of light harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the…

Chemical Physics · Physics 2018-06-15 Tobias Kramer , Matthias Noack , Alexander Reinefeld , Mirta Rodriguez , Yaroslav Zelinskyy

Prescriptive Process Monitoring (PresPM) is an emerging area within Process Mining, focused on optimizing processes through real-time interventions for effective decision-making. PresPM holds significant promise for organizations seeking…

Databases · Computer Science 2025-07-03 Jakob De Moor , Hans Weytjens , Johannes De Smedt , Jochen De Weerdt

The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintaining and executing computational saliency models. This work…

Computer Vision and Pattern Recognition · Computer Science 2018-12-24 Calden Wloka , Toni Kunić , Iuliia Kotseruba , Ramin Fahimi , Nicholas Frosst , Neil D. B. Bruce , John K. Tsotsos

NOMAD CAMELS (short: CAMELS) is a configurable, open-source measurement software that records fully self-describing experimental data. It has its origins in the field of experimental physics where a wide variety of measurement instruments…

Instrumentation and Detectors · Physics 2024-03-13 Alexander D. Fuchs , Johannes A. F. Lehmeyer , Heinz Junkes , Heiko B. Weber , Michael Krieger

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic…

Chemical Physics · Physics 2020-05-27 E. Aprà , E. J. Bylaska , W. A. de Jong , N. Govind , K. Kowalski , T. P. Straatsma , M. Valiev , H. J. J. van Dam , Y. Alexeev , J. Anchell , V. Anisimov , F. W. Aquino , R. Atta-Fynn , J. Autschbach , N. P. Bauman , J. C. Becca , D. E. Bernholdt , K. Bhaskaran-Nair , S. Bogatko , P. Borowski , J. Boschen , J. Brabec , A. Bruner , E. Cauët , Y. Chen , G. N. Chuev , C. J. Cramer , J. Daily , M. J. O. Deegan , T. H. Dunning , M. Dupuis , K. G. Dyall , G. I. Fann , S. A. Fischer , A. Fonari , H. Früuchtl , L. Gagliardi , J. Garza , N. Gawande , S. Ghosh , K. Glaesemann , A. W. Götz , J. Hammond , V. Helms , E. D. Hermes , K. Hirao , S. Hirata , M. Jacquelin , L. Jensen , B. G. Johnson , H. Jónsson , R. A. Kendall , M. Klemm , R. Kobayashi , V. Konkov , S. Krishnamoorthy , M. Krishnan , Z. Lin , R. D. Lins , R. J. Littlefield , A. J. Logsdail , K. Lopata , W. Ma , A. V. Marenich , J. Martin del Campo , D. Mejia-Rodriguez , J. E. Moore , J. M. Mullin , T. Nakajima , D. R. Nascimento , J. A. Nichols , P. J. Nichols , J. Nieplocha , A. Otero de la Roza , B. Palmer , A. Panyala , T. Pirojsirikul , B. Peng , R. Peverati , J. Pittner , L. Pollack , R. M. Richard , P. Sadayappan , G. C. Schatz , W. A. Shelton , D. W. Silverstein , D. M. A. Smith , T. A. Soares , D. Song , M. Swart , H. L. Taylor , G. S. Thomas , V. Tipparaju , D. G. Truhlar , K. Tsemekhman , T. Van Voorhis , Á. Vázquez-Mayagoitia , P. Verma , O. Villa , A. Vishnu , K. D. Vogiatzis , D. Wang , J. H. Weare , M. J. Williamson , T. L. Windus , K. Woliński , A. T. Wong , Q. Wu , C. Yang , Q. Yu , M. Zacharias , Z. Zhang , Y. Zhao , R. J. Harrison

Artificial Intelligence (AI)-driven material design has been attracting great attentions as a groundbreaking technology across a wide spectrum of industries. Molecular design is particularly important owing to its broad application domains…