q2m3 is a research framework for hybrid quantum-classical QM/MM (quantum mechanics / molecular mechanics). It connects PySCF molecular models to PennyLane quantum algorithms and resource estimates.
The project is an alpha proof of concept. Its small-system checks do not establish production chemistry accuracy. Read each example's assumptions before interpreting its results.
q2m3 requires Python 3.11+. To use the library, install it in a virtual environment:
python -m venv .venv
source .venv/bin/activate
python -m pip install q2m3To run examples, use a source checkout with uv:
git clone https://github.com/yjmaxpayne/q2m3.git
cd q2m3
uv syncEach example guide lists its optional dependencies and execution commands.
Start with the example guide. Choose a chapter for runnable examples, inputs, outputs, and scientific limits.
| Topic | Guide |
|---|---|
| Quantum phase estimation (QPE) | QPE examples |
| Sample-based quantum diagonalization (SQD) | SQD examples |
| QM/MM and solvation | QM/MM examples |
| Fragment interactions | Fragment examples |
| Quantum resource estimates | Resource examples |
| Compilation and runtime | Performance examples |
See the documentation site for tutorials, model assumptions, and API references.
See the development guide for tests, code checks, and documentation builds. Follow the contribution notes. Do not commit generated outputs.
For research use, cite the release that produced your results. CITATION.cff contains the citation metadata. q2m3 uses the MIT License.