PECOS is a library/framework for the evaluation, study, and design of QEC protocols. It also provides the ability to study and evaluate the performance advanced hybrid quantum/classical compute execution models for NISQ algorithms and beyond.
Project description
Performance Estimator of Codes On Surfaces (PECOS) is a library/framework dedicated to the study, development, and evaluation of quantum error-correction protocols. It offers tools for the study and evaluation of hybrid quantum/classical compute execution models for NISQ algorithms and beyond.
Initially conceived and developed in 2014 to verify lattice-surgery procedures presented in arXiv:1407.5103 and released publicly in 2018, PECOS filled a significant gap in the QEC/QC tools available at that time. Over the years, it has grown into a framework for studying general QECCs and hybrid computation.
With an emphasis on clarity, flexibility, and performance and catering to both QEC students and developers, PECOS is refined continually with these attributes in mind.
Features
- Quantum Error-Correction Tools: Advanced tools for studying quantum error-correction protocols and error models.
- Hybrid Quantum/Classical Execution: Evaluate advanced hybrid compute models, including support for classical compute, calls to Wasm VMs, conditional branching, and more.
- Fast Simulation: Leverage the fast stabilizer-simulation algorithm.
- Extensible: Add-ons and extensions support in C and C++ via Cython.
Getting Started
Explore the capabilities of PECOS by delving into the official documentation.
Versioning
We follow semantic versioning principles. However, before version 1.0.0, the MAJOR.MINOR.BUG format sees the roles of MAJOR and MINOR shifted down a step. This means potential breaking changes might occur between MINOR increments, such as moving from versions 0.1.0 to 0.2.0.
Latest Development
Stay updated with the latest developments on the PECOS Development branch.
Installation
- Clone or download the desired version of PECOS.
- Navigate to the root directory, where
pyproject.toml
is located. - Install using pip:
pip install .
To install optional dependencies, such as for Wasm support or state vector simulations, see pyproject.toml
for list of
options. To install all optional dependencies use:
pip install .[all]
Certain simulators have special requirements and are not installed by the command above. Installation instructions for these are provided here.
For development, use (while including installation options as necessary):
On Linux/Mac:
python -m venv .venv
source .venv/bin/activate
pip install -U pip setuptools
pip install -r requirements.txt
make metadeps
pre-commit install
pip install -e .
On Windows:
python -m venv .venv
.\venv\Scripts\activate
pip install -U pip setuptools
pip install -r requirements.txt
make metadeps
pre-commit install
pip install -e .
See Makefile
for other useful commands.
Tests can be run using:
pytest tests
Simulators with special requirements
Certain simulators from pecos.simulators
require external packages that are not installed by pip install .[all]
.
CuStateVec
requires a Linux machine with an NVIDIA GPU (see requirements here). PECOS' dependencies are specified in the[cuda]
section ofpyproject.toml
and can be installed viapip install .[cuda]
. If installation is not successful, see alternative instructions here.
Uninstall
To uninstall:
pip uninstall quantum-pecos
Citing
For publications utilizing PECOS, kindly cite PECOS such as:
@misc{pecos,
author={Ciaran Ryan-Anderson},
title={PECOS: Performance Estimator of Codes On Surfaces},
journal={GitHub},
howpublished={\url{https://github.com/PECOS-packages/PECOS}},
URL = {https://github.com/PECOS-packages/PECOS},
year={2018}
}
@phdthesis{crathesis,
author={Ciaran Ryan-Anderson},
school = {University of New Mexico},
title={Quantum Algorithms, Architecture, and Error Correction},
journal={arXiv:1812.04735},
year={2018}
}
License
This project is licensed under the Apache-2.0 License - see the LICENSE and NOTICE files for details.
Supported by
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
Hashes for quantum-pecos-0.5.0.dev10.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 96e792833fe929df4703abc0fc0d58e9e43dff1451463dfebf3d23586e875ad1 |
|
MD5 | 9316aadc52bec087ccfc103240d2bcf7 |
|
BLAKE2b-256 | c1f3e824553538cf9c3e50aeba4fdee29e4a752f7f153c7fb83d6d58d3e420b2 |
Hashes for quantum_pecos-0.5.0.dev10-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c01a97704430e9759ccf0bfa31764537b7a57ae948aea214e543ef251c7cb0b6 |
|
MD5 | 0bc92c10c6b889d778f4f4d6fba2641e |
|
BLAKE2b-256 | 15c9009b5e347cccb439e390ee19b140e93880229f9a3427ff3aca246cf6fdfe |