SCGO: Simple Cluster Global Optimization

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Global optimization of atomic clusters with ASE: Basin Hopping, Genetic Algorithms, NEB transition-state search, and MLIPs (MACE, UMA, UPET) via TorchSim. Covers gas-phase, surface, and adsorbate workflows.

Documentation: Read the Docs

Install

Exactly one MLIP extra per environment:

pip install "scgo[mace]"   # or [uma] / [upet]
# UPET only: pip install 'vesin==0.6.0' --force-reinstall --no-deps

Python 3.12+, SQLite JSON1. Details: installation guide.

Quick start

from scgo import run_go
from scgo.param_presets import get_testing_params

results = run_go(
    ["Pt"] * 4,
    params=get_testing_params(),
    seed=42,
    system_type="gas_cluster",
)

results is a list of (energy, Atoms) unique minima (energy-sorted). Use run_go_campaign for multi-composition runs.

Workflows

Goal	Entry point
Single composition GO	`run_go`
Multi-composition GO	`run_go_campaign`
TS from existing minima	`run_ts_search`
GO then TS	`run_go_ts`
Multi-composition TS / GO+TS	`run_ts_campaign` / `run_go_ts_campaign`

system_type is always a run argument: gas_cluster, surface_cluster, gas_cluster_adsorbate, or surface_cluster_adsorbate. Surfaces need surface_config=; adsorbates need adsorbates=.

Output: run_go writes {formula}_searches/; GO+TS/TS use a campaign root with sibling {formula}_searches/ and {formula}_ts_results/. See quickstart.

Examples

examples/ — MACE + TorchSim smoke scripts for all four system types (example_pt5_*.py).

Development

pip install -e ".[mace,dev]"   # or [uma,dev] / [upet,dev]
pre-commit install
pytest tests/ -m "not slow"

Long MLIP sweeps: benchmark/.

MIT License — see LICENSE.

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