PECOS (Performance Estimator of Codes On Surfaces) is a package designed to facilitate the evaluation and study of quantum error correcting codes.
Project description
PECOS (Performance Estimator of Codes On Surfaces) is a Python framework for studying, developing, and evaluating quantum error-correction protocols.
- Author: Ciarán Ryan-Anderson
- Language: Python 3.5.2+ (with optional C and C++ extensions)
Contact
For questions or suggestions, please feel free to contact the author:
- Ciarán Ryan-Anderson, ciaran.ryan-anderson@quantinuum.com
Getting Started
To get started, check out the documentation in the "docs" folder or find it online at:
https://quantum-pecos.readthedocs.io
Latest Development
See the following branch for the latest version of PECOS under development:
https://github.com/PECOS-packages/PECOS/tree/development
BEAWARE: There are some changes planned in 0.2.dev that may break some backwards compatibility with 0.1. Although, we try to minimize breaks to backwards compatibility.
Requirements
- Python 3.5.2+
- NumPy 1.15+
- SciPy 1.1+
- Matplotlib 2.2+
- NetworkX 2.1+
Optional Dependencies
- Cython (to compile optional C/C++ extensions)
- pytest 3.0+ (to run tests)
- Sphinx 2.7.6+ (to compile documentation)
License
PECOS is licensed under the Apache 2.0 license
Installation
To install using pip run the command:
pip install quantum-pecos
To install from GitHub go to:
https://github.com/PECOS-packages/PECOS
Then, download/unzip or clone the version of PECOS you would like to use. Next, navigate to the root of the package (where setup.py is located) and run:
pip install .
To install and continue to develop the version of PECOS located in the install folder, run the following instead:
pip install -e .
Uninstall
To uninstall run:
pip uninstall quantum-pecos
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 Distribution
Built Distribution
File details
Details for the file quantum-pecos-0.2.0.tar.gz
.
File metadata
- Download URL: quantum-pecos-0.2.0.tar.gz
- Upload date:
- Size: 112.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 68074ec32d51f2e9bc9afaf4f69bf1b390ac4ab6a1f0220d20607b3ee82d137c |
|
MD5 | 1c0a991ea0680e4cf2434a5f7a733f1a |
|
BLAKE2b-256 | 6aacc24871f86082196a69321cab572db8cb2d7f38797978896a9e80ef04b8b6 |
File details
Details for the file quantum_pecos-0.2.0-py2.py3-none-any.whl
.
File metadata
- Download URL: quantum_pecos-0.2.0-py2.py3-none-any.whl
- Upload date:
- Size: 181.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b88800e48ab9e69e2043a3c6b8e424a16f97797809ad131ace38129e5b5d66da |
|
MD5 | 8d3bff5f375a19a239907919f2c4041b |
|
BLAKE2b-256 | 29f6f02cde2b1f67290572306e112481dbfd92ceec467603f569e25527858493 |