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torchsim

Comprehensive TorchSim / torch-sim atomistic simulation skill for molecular dynamics, relaxation, high-throughput MLIP workflows, trajectory generation, trajectory analysis, validation, and movie production for materials systems.

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lamm-mit/ScienceSkills
ソースの最終更新活動
2026年6月21日 03:44
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英語
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39
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6

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SKILL.md
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name
torchsim
description
Comprehensive TorchSim / torch-sim atomistic simulation skill for molecular dynamics, relaxation, high-throughput MLIP workflows, trajectory generation, trajectory analysis, validation, and movie production for materials systems.
# TorchSim Atomistic Simulation Skill Use this skill when the user asks for atomistic molecular dynamics (MD), relaxation, static property evaluation, trajectory analysis, or visualization using **TorchSim / `torch-sim`**. This skill targets the active atomistic simulation engine at `https://github.com/torchsim/torch-sim`, installed as `torch-sim-atomistic` and imported as `torch_sim`. Do **not** confuse it with the unrelated PyPI package `torchsim` for MRI simulation or the older GoodAI TorchSim project. ## Core facts to preserve - Package name: `torch-sim-atomistic`. - Python import: `import torch_sim as ts`. - Python requirement: Python >= 3.12. - Core runners: - `ts.integrate(...)` for MD. - `ts.optimize(...)` for relaxation. - `ts.static(...)` for one-shot energy / force / stress-style evaluations. - Core state object: `ts.SimState`, with tensor-native batched state. - Trajectory writing/reading: - `ts.TrajectoryReporter(...)` for regular state/property reporting. - `ts.TorchSimTrajectory(...)` for HDF5 trajectory IO and analysis. - Standard unit convention follows TorchSim's metal-style units: energy eV, length Angstrom, time ps, temperature K, pressure bar-style quantities unless explicitly transformed. - Supported workflows include batched simulation, automatic GPU memory management/autobatching, ASE/pymatgen/phonopy interoperability, classical potentials, MLIPs, structural relaxation, elastic properties, MC/swap workflows, and differentiable simulations. ## Skill contract When using this skill for a user task, produce a complete, reproducible workflow. Do not only give prose. Depending on the request, create or provide: 1. A clear simulation protocol: model, system, ensemble, timestep, equilibration, production length, reporting cadence, and validation checks. 2. Runnable Python scripts or notebooks when appropriate. 3. Trajectory outputs in TorchSim HDF5 plus optional ASE `.traj`, `.xyz`, `.extxyz`, or `.pdb` exports. 4. Analysis outputs: CSV/JSON summaries, figures, and physical validation checks. 5. Movie/visualization outputs when requested: MP4/GIF plus raw frames or an OVITO/VMD/ASE-compatible trajectory. 6. A README explaining exact run commands and expected outputs. ## Default workflow for MD tasks Follow this order unless the user has a reason not to: 1. **System construction/import** - Read existing structures from CIF/POSCAR/XYZ/PDB/extxyz/traj if provided. - Otherwise construct with ASE/pymatgen: bulk crystals, surfaces/slabs, defects, interfaces, nanoparticles, liquids, polymers, or amorphous cells. - Make PBC explicit. Avoid accidental nonperiodic boxes. 2. **Model selection** - For realistic materials simulations, prefer a validated MLIP for the chemistry/conditions. - For demos/tests, use classical potentials such as Lennard-Jones, Morse, or soft-sphere. - Make model validity explicit: supported elements, pressure/temperature range, phase, charge/polarity, surfaces/defects/out-of-domain risks. 3. **Relaxation / static precheck** - Relax atomic positions before MD for solids and interfaces. - Relax cell only when physically appropriate and model supports stress/cell forces. - Run static energy/force sanity checks before a long MD. 4. **Equilibration** - Use NVT for thermal equilibration when volume is known. - Use NPT when density/lattice parameters should relax. - Choose timestep conservatively: typical MLIP solid/liquid MD often uses 0.5-2 fs = 0.0005-0.002 ps; reduce for H-rich systems, high T, reactive events, or stiff bonds. 5. **Production** - Save full state at a cadence that balances temporal resolution and file size. - Save scalar properties more frequently than full coordinates when needed. - Use separate trajectory files for batched systems. 6. **Validation** - Check energy drift for NVE. - Check target temperature in NVT. - Check pressure/volume stability in NPT. - Check force maxima, atom overlap, box collapse, model warnings, NaNs, and file completeness. 7. **Analysis** - Always include basic thermodynamics: potential energy, kinetic energy, total energy, temperature, pressure/volume if available. - Add material-specific analysis: RDF, MSD/diffusion, VACF, elastic tensor, stress-strain, heat flux/thermal conductivity, coordination, defects, surface/interface metrics, cluster statistics, polymer conformations, bond/angle/dihedral distributions. 8. **Visualization** - Export trajectories to standard formats for OVITO/VMD/ASE. - Make movies with cell axes/PBC wrapping awareness. - Include frame stride and atom rendering choices in the README. ## Routing Consult the task files for deeper workflows: - `tasks/setup_environment.md`: installation, dependency isolation, extras, GPU checks. - `tasks/model_selection.md`: MLIP and classical potential choice. - `tasks/systems.md`: bulk, liquids, surfaces, defects, interfaces, polymers, biomaterials. - `tasks/md_protocols.md`: NVE/NVT/NPT protocols and ensembles. - `tasks/relaxation_static.md`: geometry relaxation and static evaluation. - `tasks/trajectories.md`: HDF5 trajectory reporting and export. - `tasks/analysis.md`: trajectory and materials-property analysis. - `tasks/movies_visualization.md`: MP4/GIF/XYZ/extxyz/OVITO/VMD visualization. - `tasks/validation_reproducibility.md`: physical validation and reproducibility. - `tasks/batching_hpc.md`: autobatching, large sweeps, GPU memory. - `tasks/troubleshooting.md`: common errors. ## Ready templates Use files in `templates/` as starting points: - `templates/config.yaml`: canonical configuration schema. - `templates/run_md.py`: production MD runner with trajectory reporting. - `templates/relax_static.py`: relaxation and static precheck runner. - `templates/batch_sweep.py`: high-throughput batched MD sweeps. - `templates/analyze_trajectory.py`: energy/RDF/MSD/export analysis. - `templates/make_movie.py`: HDF5 trajectory to XYZ/MP4/GIF. - `templates/validate_run.py`: basic run-quality checks. Utility scripts: - `scripts/torchsim_doctor.py`: environment and GPU sanity check. - `scripts/trajectory_summary.py`: inspect TorchSim HDF5 trajectory contents. ## Important implementation cautions - Many MLIP extras have incompatible dependency stacks, especially around `e3nn`. Use one clean environment per MLIP family when possible. - Do not install every optional extra in one environment unless the user explicitly wants a compatibility matrix. - MACE/fairchem/sevenn/mattersim/orb/nequip/nequix may require model downloads, CUDA-specific builds, or license/model-card review. State these assumptions. - For publication-grade MD, do not treat a generic foundation model as validated for arbitrary chemistry. Include an explicit model-domain warning. - For biological polymers/proteins, TorchSim atomistic MLIPs may not replace force-field MD in explicit solvent unless a suitable model and long-range electrostatics treatment are validated. - For charged/ionic/polar systems, check whether the chosen model includes electrostatics/charge physics appropriate to the task. - For high-temperature, fracture, chemical reaction, defect migration, surfaces, or interfaces, run small pilot simulations first and inspect structural stability before long production. Note: Disable autobatcher on CPU pilot runs; TorchSim memory-estimation autobatching is intended for GPU memory management.
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