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Installation

Prerequisites

moTSart requires conda (or mamba) because xTB is distributed via conda-forge.

We recommend installing Miniforge (includes mamba):

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
bash Miniforge3-Linux-x86_64.sh
~/miniforge3/bin/conda init bash
exec bash

curl -L -O https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
chmod +x Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh
exec zsh

Install moTSart

Create the environment, activate it, and install moTSart together with the vendored ML-FSM and goflow packages in editable mode:

conda env create -f environment.yml
conda activate motsart
pip install -e ./ML-FSM -e ./goflow -e .

goflow provides the generative flow-matching model used by the learning pipeline. To import goflow and run the learning/generative pipeline you also need PyTorch + PyG (see PyTorch & PyG) - the conda environment does not install them. The training/sampling scripts under goflow/scripts/ are the authors' original cluster scripts and contain machine-specific paths; adapt them before use.

Optional Dependencies

Pysisyphus (reaction path optimization)

pip install pysisyphus

GPU4PySCF (Linux only, GPU-accelerated DFT)

pip install pyscf gpu4pyscf-cuda12x

PyTorch & PyG (required for learning)

Required to import goflow and run the learning/generative pipeline. Install the version matching your platform. If you also use the mlip validator, install fairchem-core before this step (it can pull a newer torch and break the pinned versions below):

pip install --index-url https://download.pytorch.org/whl/cu124 'torch==2.6.0' 'torchvision==0.21.0'
pip install -f https://data.pyg.org/whl/torch-2.6.0+cu124.html \
    pyg-lib torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric

pip install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0
pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv torch_geometric \
    -f https://data.pyg.org/whl/torch-2.6.0+cpu.html

External Software

xTB

Installed via the conda environment. Verify:

xtb --version

ORCA 6.1

Download ORCA and configure its path in your environment config (see Configuration).