Trending Research
CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties
In this work, we introduce CHIPS-FF (Computational High-Performance Infrastructure for Predictive Simulation-based Force Fields), a universal, open-source benchmarking platform for machine learning force fields (MLFFs).
Materials Science Computational Physics
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
lululxvi/deepxde
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Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.
Computational Physics
HepLean: Digitalising high energy physics
We introduce HepLean, an open-source project to digitalise definitions, theorems, proofs, and calculations in high energy physics using the interactive theorem prover Lean 4.
High Energy Physics - Phenomenology Logic in Computer Science High Energy Physics - Theory
TeNeS: Tensor Network Solver for Quantum Lattice Systems
TeNeS (Tensor Network Solver) is a free/libre open-source software program package for calculating two-dimensional many-body quantum states based on the tensor network method and the corner transfer matrix renormalization group (CTMRG) method.
Strongly Correlated Electrons Statistical Mechanics Computational Physics
Self-Organised Localisation
We describe a new phenomenon in quantum cosmology: self-organised localisation.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics High Energy Physics - Theory
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
SimOS: A Python Framework for Simulations of Optically Addressable Spins
We present an open-source simulation framework for optically detected magnetic resonance, developed in Python.
Quantum Physics Mesoscale and Nanoscale Physics Chemical Physics Computational Physics Physics Education
A foundation model for atomistic materials chemistry
Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations of ab initio quality on unprecedented time and length scales.
Chemical Physics Materials Science
Particle exchange statistics beyond fermions and bosons
We then construct a family of exactly solvable quantum spin models in one and two dimensions where free paraparticles emerge as quasiparticle excitations, and their exchange statistics can be physically observed and is notably distinct from fermions and bosons.
Quantum Physics Statistical Mechanics High Energy Physics - Theory Mathematical Physics Mathematical Physics
Biochars at the molecular level. Part 2 -- Development of realistic molecular models of biochars
With this work, we hope to speed up the uptake of molecular dynamics simulations for the study and development of biochar materials and, to this end, we distribute our easy-to-use surface-exposed biochar models ready for the adsorption studies.
Materials Science
