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

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

pytket-1.13.2-cp311-cp311-win_amd64.whl (10.7 MB view details)

Uploaded CPython 3.11Windows x86-64

pytket-1.13.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

pytket-1.13.2-cp311-cp311-macosx_11_0_x86_64.whl (10.1 MB view details)

Uploaded CPython 3.11macOS 11.0+ x86-64

pytket-1.13.2-cp311-cp311-macosx_11_0_arm64.whl (9.2 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pytket-1.13.2-cp310-cp310-win_amd64.whl (10.7 MB view details)

Uploaded CPython 3.10Windows x86-64

pytket-1.13.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

pytket-1.13.2-cp310-cp310-macosx_11_0_x86_64.whl (10.1 MB view details)

Uploaded CPython 3.10macOS 11.0+ x86-64

pytket-1.13.2-cp310-cp310-macosx_11_0_arm64.whl (9.2 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pytket-1.13.2-cp39-cp39-win_amd64.whl (10.7 MB view details)

Uploaded CPython 3.9Windows x86-64

pytket-1.13.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

pytket-1.13.2-cp39-cp39-macosx_11_0_x86_64.whl (10.1 MB view details)

Uploaded CPython 3.9macOS 11.0+ x86-64

pytket-1.13.2-cp39-cp39-macosx_11_0_arm64.whl (9.2 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

File details

Details for the file pytket-1.13.2-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pytket-1.13.2-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 10.7 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for pytket-1.13.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 53f218c24dfaa3d4bcba668a44fd8dc84172ce14ac1ab24e7dfce1f5644b81ee
MD5 7760a3b24ae0b40334ce3b829eb8686f
BLAKE2b-256 30fdec33a6a130d598d8f1055ab8f37ca934db2f4e340d4e6fe01ee0a4fe3715

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6004c01ece05bb83a7ddcbfa5f3a9ca153282f0ae9e2f7c1acec2f93b3dc30b1
MD5 769eb5c2123d4231447c9f2379970c04
BLAKE2b-256 2c0a0145fac06f30d6f052ad702a9853219c27b8f0878c313bfa3ba421f4e40d

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp311-cp311-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp311-cp311-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 c56be5ccb8efb6921771244087c29df72046c395b9eec455763e730e469f8041
MD5 9e9e7c97aed583c36f9754fff035c97c
BLAKE2b-256 d7b55970112fdc75702d8a578fb8507fe0dca44749ac6528e782213c13cf2dcc

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 cbeb6ce7380cba521ff018ac51210377994927dde124774aa6eac5abdfd2cc74
MD5 94fe8b8351159002b4cc47991b551cc5
BLAKE2b-256 d2485f08c382d72f0bf7f32ec28d536d385b789b0e13d5d916c29091c419f83f

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pytket-1.13.2-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 10.7 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for pytket-1.13.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 86af7e40556dff0d898c869851af1c51f6e039c976dc2d178a1bbcdb14a9b874
MD5 59c72cba83752cf61e2d804118b75095
BLAKE2b-256 87128d22950d05d5d78dc73cc0eb5c70db4a605b407097dfab1a3c63fdac7a58

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0f9c8801060676b1bcff2352ad14b50dfa71ef857c3d4dd28b76bb62fcb8b3ba
MD5 647d83c36d56254ed768715a3d799cf7
BLAKE2b-256 ea39a900fa72332134e60e4f47162a26f93fb91292f016c3fa61c1fe2b7b52b3

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp310-cp310-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp310-cp310-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 2e83f8b9dd3b91763ee19b98d7e07f95f756019fe294762ffbeba2a4b45edff8
MD5 b63f740ddaff342d5e79b3424b53aadb
BLAKE2b-256 779a79c4fb9242e43c06e86efa020c2148fce3c535ccea5e8a60c136a27f74ef

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 51a37556b83e636a058c42954ce450206c275aa17614cfde36663ad52e802747
MD5 3e3c5e0b3c57fbd8565ec24cfc17a300
BLAKE2b-256 30b1963f08933a76a6313b8c2b970b84b900255e4c13df3327b71561f1c221e7

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pytket-1.13.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 10.7 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for pytket-1.13.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 859707ab61ddd41d7485b23bcc41cee4c16873a18e700b00ffcf4e4d0c5947a2
MD5 51f58a233bd70c051709fa8e82aa514c
BLAKE2b-256 bfdf538042919675f69275273d135a4f6fbe27e7ea0a3ae5258efc6b04be2bf8

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 19578e247c823c363c7f21f086e707221e351c06f7f182a126ff0a260b11aba7
MD5 acbfe86616dd995621390ef8478313ee
BLAKE2b-256 ed7b4905a2b71089e75efcd7b8c9692f5469916e78ae7d4a7b6fc24652295882

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp39-cp39-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp39-cp39-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 794907edc04aee8db209e2cf058583fb433a9085d98ecd4bd00c8af50d3836e3
MD5 94835b73d38702b542c906b58458ab9e
BLAKE2b-256 e0ad196bf065d6271ac0e85730465dd02e2744f7bf0568ddcce8bda99bd79ab0

See more details on using hashes here.

File details

Details for the file pytket-1.13.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pytket-1.13.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4402f2775791e25165c47040c8efd72df9362a4ef78a0275118b0610086b10d7
MD5 02fa65c58d52cd3d7d09adae44f63dcc
BLAKE2b-256 79579dfec116ae6b418aaf193928b5805df4a7468642ebc02b261d67ffd7000e

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