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A toolkit for building high-performance molecular simulations on JAX.

Project description

kUPS
kUPS demo

A toolkit for building high-performance molecular simulations on JAX

kUPS provides composable, differentiable primitives — samplers, potentials, and propagators — with hardware acceleration on CPU, GPU, and TPU.

Documentation | Quick Start | Features | Examples

License Python JAX


Installation

Standard Installation
pip install kups
GPU Support
pip install kups[cuda]
Development
git clone https://github.com/cusp-ai-oss/kups.git
cd kups
uv sync

Quick Start

[!TIP] The repository includes example applications built with kUPS in the examples/ directory.

Monte Carlo Simulation (GCMC)
cd examples
kups_mcmc_rigid --config gcmc_co2_30box.yaml
Molecular Dynamics (Lennard-Jones)
cd examples
kups_md_lj --config md_lj_argon_nvt.yaml

Features

Simulation Methods

  • Monte Carlo — NVT and GCMC ensembles with translation, rotation, reinsertion, and exchange moves
  • Molecular Dynamics — NVE, NVT, NPT ensembles
  • Geometry Optimization — FIRE and L-BFGS relaxation

Force Fields & Potentials

  • Lennard-Jones potential
  • Coulomb interactions (Ewald summation)
  • Harmonic bonds and angles
  • Morse potential
  • MACE and UMA ML force fields

Core Capabilities

  • Composable — shared propagator interface; methods and potentials snap together freely
  • Batched — run thousands of independent simulations as vectorized computations

Performance & Integration

  • GPU-native — JIT-compiled on CPU, GPU, and TPU with no code changes
  • Differentiable — full automatic differentiation via JAX
  • PyTorch interop — bring PyTorch models into JAX via Tojax

Documentation

Full documentation is available at cusp-ai-oss.github.io/kups.

Building docs locally

To build the docs locally run ./docs/scripts/build.sh, which executes and renders all documentation notebooks and generates API pages in markdown.

./docs/scripts/build.sh           # build into site/
./docs/scripts/build.sh --serve   # serve with live updates on http://127.0.0.1:8000

Citation

If you use kUPS in your research, please cite:

@software{kups2026,
  author = {{Cusp AI}},
  title = {kUPS},
  year = {2026},
  url = {https://github.com/cusp-ai-oss/kups}
}

License

Apache License 2.0 — see LICENSE.

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