Skip to main content

Scientific Toolkit for Quantum Computing

Project description

skq

Python Version uv Ruff

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

The default skq installation contains conversion to qiskit. PennyLane support can be installed as an optional dependency.

All backends

pip install skq[all]

PennyLane

pip install skq[pennylane]

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-0.2.0.tar.gz (31.5 kB view details)

Uploaded Source

Built Distribution

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

skq-0.2.0-py3-none-any.whl (37.0 kB view details)

Uploaded Python 3

File details

Details for the file skq-0.2.0.tar.gz.

File metadata

  • Download URL: skq-0.2.0.tar.gz
  • Upload date:
  • Size: 31.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for skq-0.2.0.tar.gz
Algorithm Hash digest
SHA256 1bbfe1a54a9630949fb9b6b5d80cca17bb90a1c9d64709d4824bec691b050d04
MD5 cf3c6729f9476ce6828ca84bd9737af6
BLAKE2b-256 4258c81f7568e599117a932c9a53bba4d2fad73bf312a75e22029ae938316e65

See more details on using hashes here.

File details

Details for the file skq-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: skq-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 37.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for skq-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 535b813abfed78d614fd8088449c5ac040aa645e1703232d6c7706da20e88a8b
MD5 485fe154efdc8cb0b372cd283ac88092
BLAKE2b-256 699fdf68e7ec656218509b977b6aa5eea3cf4bf2c3eb6799be04a71b307c7aca

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