Skip to main content

Package for numerical quantum transport calculations (Python 3 version)

Project description

Kwant is a free (open source) Python package for numerical calculations on tight-binding models with a strong focus on quantum transport. It is designed to be flexible and easy to use. Thanks to the use of innovative algorithms, Kwant is often faster than other available codes, even those entirely written in the low level FORTRAN and C/C++ languages.

Tight-binding models can describe a vast variety of systems and phenomena in quantum physics. Therefore, Kwant can be used to simulate

  • metals,

  • graphene,

  • topological insulators,

  • quantum Hall effect,

  • superconductivity,

  • spintronics,

  • molecular electronics,

  • any combination of the above, and many other things.

Kwant can calculate

  • transport properties (conductance, noise, scattering matrix),

  • dispersion relations,

  • modes,

  • wave functions,

  • various Green’s functions,

  • out-of-equilibrium local quantities.

Other computations involving tight-binding Hamiltonians can be implemented easily.

See the Kwant web site for the latest stable version. The current development version is available via the Kwant gitlab instance. Contributions are welcome.

A mailing list exists for general discussions related to Kwant. Please report bugs and other issues using the issue tracker.

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

kwant-1.4.1.tar.gz (1.7 MB view details)

Uploaded Source

File details

Details for the file kwant-1.4.1.tar.gz.

File metadata

  • Download URL: kwant-1.4.1.tar.gz
  • Upload date:
  • Size: 1.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.7.2

File hashes

Hashes for kwant-1.4.1.tar.gz
Algorithm Hash digest
SHA256 8c0ccf341dfa74e1d69f1508968c4d4e9fb36f74685f101897df6a84ed7043df
MD5 2f46898480a55db372d65d243b25bd82
BLAKE2b-256 3b19b1fb09d493ad5bd07c19c74da38220c9a09f59417c70173fd90f29af5ae7

See more details on using hashes here.

Supported by

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