Trending Research
Large-scale machine-learning molecular dynamics simulation of primary radiation damage in tungsten
Simulating collision cascades and radiation damage poses a long-standing challenge for existing interatomic potentials, both in terms of accuracy and efficiency.
Computational Physics
An equivariant graph neural network for the elasticity tensors of all seven crystal systems
wengroup/matten
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The elasticity tensor that describes the elastic response of a material to external forces is among the most fundamental properties of materials.
Materials Science
Why neural functionals suit statistical mechanics
We describe recent progress in the statistical mechanical description of many-body systems via machine learning combined with concepts from density functional theory and many-body simulations.
Soft Condensed Matter Statistical Mechanics
nimCSO: A Nim package for Compositional Space Optimization
nimCSO is a high-performance tool implementing several methods for selecting components (data dimensions) in compositional datasets, which optimize the data availability and density for applications such as machine learning.
Materials Science Data Analysis, Statistics and Probability
Python-Based Quantum Chemistry Calculations with GPU Acceleration
To make the package easy to extend and integrate with other Python packages, it is designed with PySCF-compatible interfaces and Pythonic implementations.
Computational Physics Chemical Physics Quantum Physics
Graded Symmetry Groups: Plane and Simple
qualcomm-ai-research/geometric-algebra-transformer
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The symmetries described by Pin groups are the result of combining a finite number of discrete reflections in (hyper)planes.
Mathematical Physics Robotics Mathematical Physics
NCON: A tensor network contractor for MATLAB
This article presents a MATLAB function ncon(), or "Network CONtractor", which accepts as its input a tensor network and a contraction sequence describing how this network may be reduced to a single tensor or number.
Computational Physics Strongly Correlated Electrons Quantum Physics
Automated discovery of superconducting circuits and its application to 4-local coupler design
Superconducting circuits have emerged as a promising platform to build quantum processors.
Quantum Physics
Accurate global machine learning force fields for molecules with hundreds of atoms
stefanch/sGDML
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Global machine learning force fields (MLFFs), that have the capacity to capture collective many-atom interactions in molecular systems, currently only scale up to a few dozen atoms due a considerable growth of the model complexity with system size.
Chemical Physics Computational Physics
DeePMD-kit v2: A software package for Deep Potential models
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models.
Chemical Physics Atomic and Molecular Clusters J.2
