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-0.3.0a8.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-0.3.0a8-py3-none-any.whl (59.7 kB view details)

Uploaded Python 3

File details

Details for the file qclab-0.3.0a8.tar.gz.

File metadata

  • Download URL: qclab-0.3.0a8.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-0.3.0a8.tar.gz
Algorithm Hash digest
SHA256 2fe4dc4a586f3b841ed36fba1dbee00eb1540b9e0cd58d7291faf363a8269f35
MD5 28dcabdc3acfb9b8b8020f9274f4e4e2
BLAKE2b-256 19ccaf3cfd21c1a67e6f645d41e30ef809a5d689f622067da0e6e6cc68984a49

See more details on using hashes here.

File details

Details for the file qclab-0.3.0a8-py3-none-any.whl.

File metadata

  • Download URL: qclab-0.3.0a8-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-0.3.0a8-py3-none-any.whl
Algorithm Hash digest
SHA256 5ec7fef8c5799eff2e68e1437bf75c380b957dcc3314c40065cb00b05325ddac
MD5 fd881923fdd13a92cfcd86869c315d57
BLAKE2b-256 777b190048c4fea25482c172f2ecf1463711177e69599f61cd7decd596353a6c

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