Skip to main content

Scientific Toolkit for Quantum Computing

Project description

skq

Scientific Toolkit for Quantum Computing

This library is used in the q4p (Quantum Computing for Programmers) course.

NOTE: This library is developed for educational purposes. While we strive for correctness of everything, the code is provided as is and not guaranteed to be bug-free. For sensitive applications make to check computations.

Why SKQ?

  • Exploration: Play with fundamental quantum building blocks (NumPy).
  • Education: Learn quantum computing concepts and algorithms.
  • Integration: Combine classical components with quantum components.
  • Democratize quantum for Python programmers and data scientists: Develop quantum algorithms in your favorite environment and easily export to your favorite quantum computing platform for running on real quantum hardware.

Install

pip install skq

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

skq-0.1.2.tar.gz (29.8 kB view details)

Uploaded Source

Built Distribution

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

skq-0.1.2-py3-none-any.whl (36.6 kB view details)

Uploaded Python 3

File details

Details for the file skq-0.1.2.tar.gz.

File metadata

  • Download URL: skq-0.1.2.tar.gz
  • Upload date:
  • Size: 29.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.5

File hashes

Hashes for skq-0.1.2.tar.gz
Algorithm Hash digest
SHA256 f01ebdbc13828fcb34cdc92b3a011eb3d3d0b8499b6d4e8bae014326e50492db
MD5 ce73709d33c60459a9d14b24501a65d9
BLAKE2b-256 a5dab2b1450c5eca4104c464cc36fc47b454b0221b287e14b432eab252fdec88

See more details on using hashes here.

File details

Details for the file skq-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: skq-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 36.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.5

File hashes

Hashes for skq-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 2e625ea8dde03769cffd355ad56c7411ccc404167ef3ce27a739a1073d2175d2
MD5 1439b88698edb4d42ff419f65c56c4eb
BLAKE2b-256 faf720c45d105dc949cae32abf383dd47da3b45781e779fa3d2cdd871fd8b31a

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