Skip to main content

QC Lab: a python package for quantum-classical modeling.

Project description

QC Lab is a Python package designed for implementing and executing quantum-classical (QC) dynamics simulations. It offers an environment for developing physical models and QC algorithms which enables algorithms and models to be combined arbitrarily. QC Lab comes with a variety of already implemented models and algorithms which we hope will encourage new researchers to explore the field of quantum-classical dynamics. Users that implement their own models and algorithms will have the opportunity to contribute them to QC Lab to form a growing library of quantum-classical dynamics tools.

QC Lab is developed and maintained by the Tempelaar Team in the Chemistry Department of Northwestern University in Evanston, Illinois, USA.

The documentation for QC Lab can be found at https://tempelaar-team.github.io/qclab/.

Capabilities

Dynamics Algorithms

The following algorithms are implemented making use of the complex-classical coordinate formalism established in [1].

  • Mean-field (Ehrenfest) dynamics [2]

  • Fewest-switches surface hopping (FSSH) dynamics [3]

Model Systems

  • Spin-boson model [4]

  • Holstein lattice model [5]

  • Fenna-Matthews-Olson (FMO) complex [6, 7]

Installing qclab

QC Lab can be installed from the Python Package Index (PyPI) by executing:

pip install qclab

To install QC Lab without h5py or numba support, execute:

pip install qclab --no-deps
pip install numpy tqdm

QC Lab can be installed from source by downloading the repository and executing:

pip install ./

from inside its topmost directory (where the pyproject.toml file is located).

Bibliography

  1. Miyazaki, K.; Krotz, A.; Tempelaar, R. Mixed Quantum-Classical Dynamics under Arbitrary Unitary Basis Transformations. J. Chem. Theory Comput. 2024, 20 (15), 6500-6509. https://doi.org/10.1021/acs.jctc.4c00555

  2. Tully, J. C. Mixed Quantum–Classical Dynamics. Faraday Discuss. 1998, 110 (0), 407–419. https://doi.org/10.1039/A801824C.

  3. Hammes‐Schiffer, S.; Tully, J. C. Proton Transfer in Solution: Molecular Dynamics with Quantum Transitions. J. Chem. Phys. 1994, 101 (6), 4657–4667. https://doi.org/10.1063/1.467455.

  4. Tempelaar, R.; Reichman, D. R. Generalization of Fewest-Switches Surface Hopping for Coherences. The Journal of Chemical Physics 2018, 148 (10), 102309. https://doi.org/10.1063/1.5000843.

  5. Krotz, A.; Provazza, J.; Tempelaar, R. A Reciprocal-Space Formulation of Mixed Quantum–Classical Dynamics. J. Chem. Phys. 2021, 154 (22), 224101. https://doi.org/10.1063/5.0053177.

  6. Fenna, R. E. & Matthews, B. W. Chlorophyll arrangement in a bacteriochlorophyll protein from Chlorobium limicola. Nature 258, 573–577 (1975). https://doi.org/10.1038/258573a0.

  7. Mulvihill, E.; Lenn, K. M.; Gao, X.; Schubert, A.; Dunietz, B. D.; Geva, E. Simulating Energy Transfer Dynamics in the Fenna–Matthews–Olson Complex via the Modified Generalized Quantum Master Equation. The Journal of Chemical Physics 2021, 154 (20), 204109. https://doi.org/10.1063/5.0051101.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qclab-0.3.0a9.tar.gz (53.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

qclab-0.3.0a9-py3-none-any.whl (59.7 kB view details)

Uploaded Python 3

File details

Details for the file qclab-0.3.0a9.tar.gz.

File metadata

  • Download URL: qclab-0.3.0a9.tar.gz
  • Upload date:
  • Size: 53.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.12

File hashes

Hashes for qclab-0.3.0a9.tar.gz
Algorithm Hash digest
SHA256 1f0492a3f28d8ce6bbbfba63d49c89f8d7fd0608c754a967f3afa9629f33c234
MD5 e8cd25bd3ad867f4a2e117c133c5d8eb
BLAKE2b-256 e7b298da1b6715e4da5a9616d23fb12b27d7ff507ad35cce070bea43fc1aa769

See more details on using hashes here.

File details

Details for the file qclab-0.3.0a9-py3-none-any.whl.

File metadata

  • Download URL: qclab-0.3.0a9-py3-none-any.whl
  • Upload date:
  • Size: 59.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.12

File hashes

Hashes for qclab-0.3.0a9-py3-none-any.whl
Algorithm Hash digest
SHA256 9e2033a89ccf8623f36f45a5b429131503d909f0dcd19bddd1cd343a1ba2e18d
MD5 e6ed797747f98ff5777c322e1243dbed
BLAKE2b-256 1bbd8aa574eb7885626f7ce466d33002ed33e2d76bc37ad468394c41d44e3672

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page