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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


PyPI version Documentation Status Python versions Supported by Quantinuum

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.


  • 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.


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.


  1. Clone or download the desired version of PECOS.
  2. Navigate to the root directory, where pyproject.toml is located.
  3. 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
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 of pyproject.toml and can be installed via pip install .[cuda]. If installation is not successful, see alternative instructions here.


To uninstall:

pip uninstall quantum-pecos


For publications utilizing PECOS, kindly cite PECOS such as:

 author={Ciaran Ryan-Anderson},
 title={PECOS: Performance Estimator of Codes On Surfaces},
 URL = {},

 author={Ciaran Ryan-Anderson},
 school = {University of New Mexico},
 title={Quantum Algorithms, Architecture, and Error Correction},


This project is licensed under the Apache-2.0 License - see the LICENSE and NOTICE files for details.

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