Skip to main content

Python module for interfacing with the CQC tket library of quantum software

Project description

Pytket is a python module for interfacing with TKET, an optimising compiler for quantum circuits developed by Quantinuum. In addition to pytket there are several extension modules for accessing a range of quantum hardware and classical simulators. The extension modules also provide integration with several widely used quantum software tools.

The source code for the TKET compiler can be found in this github repository.

Installation

Installation is supported for Linux, MacOS and Windows. Installation requires python 3.9, 3.10 or 3.11.

To install run the pip command:

pip install pytket

See Installation troubleshooting for help with installation.

To install the pytket extension modules add a hyphen and the extension name to the command:

pip install pytket-quantinuum

For a list of pytket extensions see this page: https://cqcl.github.io/pytket-extensions/api/index.html.

Documentation and Examples

API reference: https://cqcl.github.io/tket/pytket/api/

To get started using pytket see the user manual.

For worked examples using TKET see our examples repository.

Support and Discussion

For bugs and feature requests we recommend creating an issue on the github repository.

User support: tket-support@cambridgequantum.com

For discussion, join the public slack channel here.

Mailing list: join here.

Citation

If you wish to cite TKET in any academic publications, we generally recommend citing our software overview paper for most cases.

If your work is on the topic of specific compilation tasks, it may be more appropriate to cite one of our other papers:

  • "On the qubit routing problem" for qubit placement (a.k.a. allocation) and routing (a.k.a. swap network insertion, connectivity solving). https://arxiv.org/abs/1902.08091 .
  • "Phase Gadget Synthesis for Shallow Circuits" for representing exponentiated Pauli operators in the ZX calculus and their circuit decompositions. https://arxiv.org/abs/1906.01734 .
  • "A Generic Compilation Strategy for the Unitary Coupled Cluster Ansatz" for sequencing of terms in Trotterisation and Pauli diagonalisation. https://arxiv.org/abs/2007.10515 .

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

pytket-1.14.0-cp311-cp311-win_amd64.whl (6.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pytket-1.14.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pytket-1.14.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (6.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pytket-1.14.0-cp311-cp311-macosx_11_0_x86_64.whl (6.1 MB view details)

Uploaded CPython 3.11 macOS 11.0+ x86-64

pytket-1.14.0-cp311-cp311-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pytket-1.14.0-cp310-cp310-win_amd64.whl (6.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pytket-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pytket-1.14.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (6.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pytket-1.14.0-cp310-cp310-macosx_11_0_x86_64.whl (6.1 MB view details)

Uploaded CPython 3.10 macOS 11.0+ x86-64

pytket-1.14.0-cp310-cp310-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pytket-1.14.0-cp39-cp39-win_amd64.whl (6.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pytket-1.14.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pytket-1.14.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (6.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pytket-1.14.0-cp39-cp39-macosx_11_0_x86_64.whl (6.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ x86-64

pytket-1.14.0-cp39-cp39-macosx_11_0_arm64.whl (5.5 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

File details

Details for the file pytket-1.14.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pytket-1.14.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for pytket-1.14.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 06bc97306193d4fc075adcce6b033d86c6de1cdd13fadbe05c5373a8ce81b364
MD5 a84f415ac60e8e65d9ef7ebf839bdfec
BLAKE2b-256 54cb8c2ff46db2303bdaccfca2fc4fa3eb5610f83a72210d108e343ea2ff87be

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cb747af42ecb74821fa1b5e06d0ee7f667d559ca7e852c8437fecc777d1258f7
MD5 e4b09aedb4dec8cb4445ebd08c620349
BLAKE2b-256 c6b0ae7684295be34cabcbad03bf88415353762962c9e19f0a76fdd2881dd84d

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 31d34023267f529f3f9e3f39900add9253febf46041724d3877b465b45372713
MD5 ddc951be1c196065b45300ae4471beec
BLAKE2b-256 ebdad1128153011c1a624a24108147e1e676589f44de7dca4d366d2763ea2b12

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp311-cp311-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp311-cp311-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 9eac273e4873bd014eeb47234077a90d2dab436097342d3fc196679d1fedf324
MD5 69dee6cb3a4f93a89ef6ec793c34a09d
BLAKE2b-256 c61cac1e696474b41758b82379ca125ea684893a39a175b1fa43b5594c0a4171

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 388e901d94f1a36a3b2462a2e19ecef6938fbd1ef40a105d73634e7df002c541
MD5 cc6a927ed4497ceaf538c074e992e3b1
BLAKE2b-256 aa6c4f0f9cc903d65cfae1c0646106481899bedcd2fc2a7171a980535414f335

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pytket-1.14.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for pytket-1.14.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 579f43e79f9c371315bcea0ee2ceadee385ed204024ea075eee8db7ba044f5a2
MD5 b8730922a4023a09b4dcbc4454d2914f
BLAKE2b-256 4322c2682322c5d6bd23eca30950469d72dca1bfe7a2d2a9d58ddf093b3eee4b

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fb5c52f8c8339448866f2fa08b558b728262f946101c2dee67ab0ac4d288011f
MD5 4228bda469aee6e6801ebc046117fb83
BLAKE2b-256 40211498b49adb7eb5cbd2d76deb308436731418ba8fef920ca10b55ee9aaf34

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0bc046d7e692eb540af41ff25dfbff3bcb25013d8f51f97c64797a118d65a9aa
MD5 c3e77aacb19d6e34dc58de72e22d3939
BLAKE2b-256 6d828dcaa469aba518379b887a85efe714d754c5144f0ba0012a234ed75a5376

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp310-cp310-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp310-cp310-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 20b02177393a52b05bf6bafb7b3923c3dc44b2f44c19df5ebf6fe302ccf61373
MD5 3b7a202afc82f3122e6df0ed3296c23d
BLAKE2b-256 89edb9d11bf91d54ec2bfadf078a5e5bf58559aaa95f44039153d74e0ab08678

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f0961bf9a0aca5e901581fc63059ae67a999e576d1e60f9be926e49a5779133f
MD5 32f9b0e6c5ebf01272a4ca29263b6d2a
BLAKE2b-256 afa2eb4d733024e008aee09aa064ce055f2fbfb6259147c13a6e20bbf8f27cc8

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pytket-1.14.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for pytket-1.14.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 10e09d308719835526db9d4560d2be92323d5ff61a9093c4b97303b2e806008c
MD5 d201477794aac5fba799217ea45e5907
BLAKE2b-256 a873f0df524debeb0cefdbefc1a2859ade1e69c8d46d84d10750f1db72836459

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9f6a174c7584f175a06eef16b45121f270ef6185262b51688bc545cc64e7293d
MD5 a7abcef0df7b70d8c991a55fbab87f50
BLAKE2b-256 5628c946d9a349540e9291d548c6195c6a9addb719b549f171ed32ab64bc5d63

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 eae23d0093d2b1eab192c9bb84b751cf421ec905747274f391437b17ccc6dd3b
MD5 c346d6dfa7d74dbe8ff35cf2d08059d4
BLAKE2b-256 c5cf61b17a7f15d9ff1530f90c886bb0988c80e955004c303e4e190e7fc0b213

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp39-cp39-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp39-cp39-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 42b47df2c9c20448f4aa17a7ae755404715ca404d7e192a9d83cd4f8ea2c3c30
MD5 4d19e9f1bfe3416a66bca2ea008a6cf3
BLAKE2b-256 6263b922a42383b49df81a2be782435ff7273d2a31f925f3554522713d0f2333

See more details on using hashes here.

File details

Details for the file pytket-1.14.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.14.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 99a9813c17b0930571712d3cbd77520b83282baaffd8cd50c5549f48e2657f99
MD5 3fef26678572718d88a4ef40f497a5e8
BLAKE2b-256 679612d6459ff709d91cb4d558c4ff0be5638c7733b5f9bfead3ba2422732bde

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