Search · four archives
Search · four archives
13 papers · ranked by Valyu relevance
Tuteja, Keshvi, Olenik, Gregor + 12 more
Sparse linear algebra is a cornerstone of many scientific computing and machine learning applications. Python has become a popular choice for these applications due to its simplicity and ease of use. Yet high-performance sparse kernels in Python remain limited in functionality, especially on modern CPU and GPU…
Zeyi Zhang, Carlos Mora Perez, Patrick Kwon, Martin Head‐Gordon + 1 more
PARSEC.py is a Python-based real-space Kohn-Sham density functional theory (real-space KS-DFT) framework designed to provide a user- and developer-friendly platform for first-principles electronic-structure simulations. Discretization on real-space grids eliminates basis-set approximations, while enabling systematic…
Bruno M. Saraiva, Iván Hidalgo-Cenalmor, António D. Brito, Damián Martínez + 3 more
> 1 Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal 2 Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland 3 InFLAMES Research Flagship Center, University of Turku, Turku, Finland 4 Turku Bioscience Centre, University of Turku…
Ragnar Bjornsson
We introduce ASH, a multi-scale, multi-theory modeling program for quantum mechanics (QM), molecular mechanics (MM), and hybrid calculations, written in the Python programming language. ASH is written in response to the increasingly diverse computational chemistry software landscape that features more QM and MM…
Indranil Saha, Daniel Willimetz, Lukáš Grajciar
Molecular simulations are invaluable for analysing molecular systems, but existing post-processing tools are often limited by a lack of customization, interactivity, and efficiency with large datasets. To address this, we developed CRISP (Comprehensive Repository for Insightful Simulation Post-Processing), an…
Fabio Cumbo, Jayadev Joshi, Daniel Blankenberg
Background – The integration of command-line tools into the Galaxy platform is crucial for making complex computational methods accessible to a broader audience and ensuring reproducible research. However, the manual development of tool wrappers (i.e., the XML files that define the user interface and execution logic in…
Ihor Kendiukhov
ergodicity is an open-source Python library for computational work on stochastic dynamics, with particular emphasis on non-ergodicity, time-average behavior, heavy-tailed processes, and decision making under uncertainty. The package brings together three layers that are often split across ad hoc scripts: process…
Daniel P. Marshall, Elie S. Farah, Eric D. Musselman, Nicole A. Pelot + 2 more
of model nerve fibers to electrical stimulation PyFibers: A Python package to simulate nerve fiber responses to electrical stimulation Authors: Daniel P. Marshall, Elie S. Farah, Eric D. Musselman, Nicole A. Pelot, Warren M. Grill, Alain Nogaret Computational modeling of peripheral nerve fibers is a key tool for…
Tsai, Shin-Rong, Schive, Hsi-Yu + 2 more
In the exascale computing era, handling and analyzing massive datasets have become extremely challenging. In situ analysis, which processes data during simulation runtime and bypasses costly intermediate I/O steps, offers a promising solution. We present libyt (https://github.com/yt-project/libyt), an open-source C…
Darshan Mandge, Anıl Tuncel, Aurélien Jaquier, Ilkan Kilic + 5 more
The diversity of labs, tools, and data formats in neuroscientific research has historically posed challenges for data sharing and collaboration. Researchers often needed to convert data between various formats and adapt their software to new environments, which could divert attention from their main research goals.…
Fanwang Meng, Marco Martínez González, Valerii Chuiko, Alireza Tehrani + 7 more
Selector is a free, open-source Python library for selecting diverse subsets from any dataset, making it a versatile tool across a wide range of application domains. Selector implements different subset sampling algorithms based on sample distance, similarity, and spatial partitioning, along with metrics to quantify…
Haofei Gao, Tingjia Miao, Wenkai Jin, Muhua Zhang + 11 more
Lattice quantum chromodynamics (LQCD) provides a first-principles framework for computing hadronic observables, but its practical use remains limited by the substantial expertise required to turn research motivation into reliable computing workflows. Here we present \textsc{LQCDMaster}, a tool-augmented, skill-guided…
Shivamshan Sivanesan, Kazem Ardaneh
Fortran has been the cornerstone of high-performance computing for decades and remains unmatched in many domains. Yet the language faces an expertise gap: a new generation of scientists is barely familiar with it, while many experienced Fortran developers are only now transitioning to modern ecosystems such as JAX.…