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We introduce atomicrex, an open-source code for constructing interatomic potentials as well as more general types of atomic-scale models. Such effective models are required to simulate extended materials structures comprising many thousands…

Materials Science · Physics 2020-08-03 Alexander Stukowski , Erik Fransson , Markus Mock , Paul Erhart

Machine learning (ML) offers powerful methods for detecting and modeling associations often in data with large feature spaces and complex associations. Many useful tools/packages (e.g. scikit-learn) have been developed to make the various…

Machine Learning · Computer Science 2022-06-27 Ryan J. Urbanowicz , Robert Zhang , Yuhan Cui , Pranshu Suri

The new and growing field of Quantitative Dependency Syntax has emerged at the crossroads between Dependency Syntax and Quantitative Linguistics. One of the main concerns in this field is the statistical patterns of syntactic dependency…

Computation and Language · Computer Science 2022-06-15 Lluís Alemany-Puig , Juan Luis Esteban , Ramon Ferrer-i-Cancho

The task of atom rearrangement has emerged in the last decade as a fundamental building block for the development of neutral atom-based quantum processors. However, despite many recent efforts to develop algorithms with favorable asymptotic…

Quantum Physics · Physics 2025-08-05 Nikhil K Harle , Bo-Yu Chen , Bob Bao , Hannes Bernien

The ExoMol project is dedicated to providing molecular line lists for exoplanet and other hot atmospheres. The ExoMol procedure uses a mixture of ab initio calculations and available laboratory data. The actual line lists are generated…

Solar and Stellar Astrophysics · Physics 2018-05-14 Jonathan Tennyson , Sergei N. Yurchenko

Epitopes are short antigenic peptide sequences which are recognized by antibodies or immune cell receptors. These are central to the development of immunotherapies, vaccines, and diagnostics. However, the rational design of synthetic…

ML4Chem is an open-source machine learning library for chemistry and materials science. It provides an extendable platform to develop and deploy machine learning models and pipelines and is targeted to the non-expert and expert users.…

Chemical Physics · Physics 2020-03-31 Muammar El Khatib , Wibe A de Jong

A generic construction of linear codes over finite fields has recently received a lot of attention, and many one-weight, two-weight and three-weight codes with good error correcting capability have been produced with this generic approach.…

Information Theory · Computer Science 2015-12-23 Can Xiang

Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure. While such models allow one to generate molecules with desirable properties, they give no guarantees…

Machine Learning · Computer Science 2019-12-05 John Bradshaw , Brooks Paige , Matt J. Kusner , Marwin H. S. Segler , José Miguel Hernández-Lobato

We present TUNA, an open-source quantum chemistry program specifically designed for atoms and diatomic molecules. Within this narrow molecular domain, a broad and consistent set of electronic structure methods and calculation types is…

Chemical Physics · Physics 2026-04-03 Harry Brough

The scanning transmission electron microscope, a workhorse instrument in materials characterization, is being transformed into an atomic-scale material manipulation platform. With an eye on the trajectory of recent developments and the…

Applied Physics · Physics 2023-08-15 Ondrej Dyck , Andrew R. Lupini , Stephen Jesse

Deep generative models have been shown powerful in generating novel molecules with desired chemical properties via their representations such as strings, trees or graphs. However, these models are limited in recommending synthetic routes…

Artificial Intelligence · Computer Science 2022-08-02 Dai Hai Nguyen , Koji Tsuda

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In the framework, a…

Machine Learning · Computer Science 2021-08-24 Naveed Ahmed Azam , Jianshen Zhu , Kazuya Haraguchi , Liang Zhao , Hiroshi Nagamochi , Tatsuya Akutsu

The Open Knowledgebase of Interatomic Models (OpenKIM) project is a framework intended to facilitate access to standardized implementations of interatomic models for molecular simulations along with computational protocols to evaluate them.…

We introduce SynFormer, a generative modeling framework designed to efficiently explore and navigate synthesizable chemical space. Unlike traditional molecular generation approaches, we generate synthetic pathways for molecules to ensure…

Machine Learning · Computer Science 2024-10-07 Wenhao Gao , Shitong Luo , Connor W. Coley

The large quantity and high quality of modern radio and infrared line observations require efficient modeling techniques to infer physical and chemical parameters such as temperature, density, and molecular abundances. We present a computer…

This paper provides the description of a novel, multi-purpose spline library. In accordance with the increasingly diverse modes of usage of splines, it is multi-purpose in the sense that it supports geometry representation, finite element…

Mathematical Software · Computer Science 2020-02-28 Markus Frings , Norbert Hosters , Corinna Müller , Max Spahn , Christoph Susen , Konstantin Key , Stefanie Elgeti

CHEMSMART (Chemistry Simulation and Modeling Automation Toolkit) is an open-source, Python-based framework designed to streamline quantum chemistry workflows for homogeneous catalysis and molecular modeling. By integrating job preparation,…

Chemical Physics · Physics 2025-08-28 Xinglong Zhang , Huiwen Tan , Jingyi Liu , Zihan Li , Lewen Wang , Benjamin W. J. Chen

With the growing popularity of Large Reasoning Models and their results in solving mathematical problems, it becomes crucial to measure their capabilities. We introduce a pipeline for both automatic and interactive verification as a more…

Artificial Intelligence · Computer Science 2026-02-25 Varvara Sazonova , Dmitri Shmelkin , Stanislav Kikot , Vasily Motolygin