Skip to main content

Mitiq is an open source toolkit for implementing error mitigation techniques on most current intermediate-scale quantum computers.

Project description

Mitiq logo

All Contributors

build Documentation Status codecov PyPI version arXiv Downloads Repository Unitary Fund Discord Chat Binder

Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers.

Current quantum computers are noisy due to interactions with the environment, imperfect gate applications, state preparation and measurement errors, etc. Error mitigation seeks to reduce these effects at the software level by compiling quantum programs in clever ways.

Want to know more? Check out our documentation and chat with us on Discord.

Do you use near-term quantum hardware? Have you tried Mitiq? Either way, take our survey and help make Mitiq better!



pip install mitiq


Define a function which inputs a circuit and returns an expectation value you want to compute, then use Mitiq to mitigate errors.

import cirq
from mitiq import zne, benchmarks

def execute(circuit: cirq.Circuit, noise_level: float = 0.001) -> float:
    """Returns Tr[ρ |0⟩⟨0|] where ρ is the state prepared by the circuit with depolarizing noise."""
    noisy_circuit = circuit.with_noise(cirq.depolarize(p=noise_level))
    return cirq.DensityMatrixSimulator().simulate(noisy_circuit).final_density_matrix[0, 0].real

circuit: cirq.Circuit = benchmarks.generate_rb_circuits(n_qubits=1, num_cliffords=50)[0]

true_value = execute(circuit, noise_level=0.0)       # Ideal quantum computer.
noisy_value = execute(circuit)                       # Noisy quantum computer.
zne_value = zne.execute_with_zne(circuit, execute)   # Noisy quantum computer + Mitiq.

print(f"Error (w/o  Mitiq): %0.4f" %abs((true_value - noisy_value) / true_value))
print(f"Error (with Mitiq): %0.4f" %abs((true_value - zne_value) / true_value))

Sample output:

Error (w/o  Mitiq): 0.0688
Error (with Mitiq): 0.0002

See our guides and examples for more explanation, techniques, and benchmarks. The examples and other notebooks can be run interactively on the cloud with

Quick Tour

Error mitigation techniques

Technique Documentation Mitiq module Paper Reference(s)
Zero-noise extrapolation ZNE mitiq.zne 1611.09301
Probabilistic error cancellation PEC mitiq.pec 1612.02058
(Variable-noise) Clifford data regression CDR mitiq.cdr 2005.10189
Dynamical decoupling (In progress) (In progress) 9803057

See our roadmap for additional candidate techniques to implement. If there is a technique you are looking for, please file a feature request.


We refer to any programming language you can write quantum circuits in as a frontend, and any quantum computer / simulator you can simulate circuits in as a backend.

Supported frontends

Cirq Qiskit pyQuil Braket
Cirq logo Qiskit logo Rigetti logo AWS logo

Note: Cirq is a core requirement of Mitiq and is installed when you pip install mitiq.

Supported backends

You can use Mitiq with any backend you have access to that can interface with supported frontends.

Citing Mitiq

If you use Mitiq in your research, please reference the Mitiq preprint (bibtex). A list of papers citing Mitiq can be found on Google Scholar / Semantic Scholar.


GNU GPL v.3.0.


We welcome contributions to Mitiq including bug fixes, feature requests, etc. To get started, check out our contribution guidelines and/or documentation guidelines. An up-to-date list of contributors can be found here and below.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Will Zeng

🚧 💻 📖 🚇 🤔

Nathan Shammah

🚧 💻 📖 🚇 🤔

Ryan LaRose

🚧 💻 📖 🚇 🤔

Andrea Mari

🚧 💻 📖 🚇 🤔

Sarah Kaiser

🚧 💻 📖 🚇 🤔

Peter Karalekas

🚧 💻 📖 🚇 🤔




⚠️ 💻

Maxime Tremblay

💻 📖 🤔

Laurent AJDNIK


Cole Kissane

💻 🐛

Michał Stęchły


Kunal Marwaha




Bobin Mathew



📖 🐛




💻 🐛

Yousef Hindy

💻 ⚠️ 📖

Mohamed El Mandouh

💻 ⚠️ 📖

Aaron Robertson

💡 ⚠️ 🐛

Ashish Panigrahi



📖 ⚠️

Purva Thakre

📖 🚇 💻 🤔

Brian Lui

💻 🐛

Tianyi Hao

💻 🐛

This project follows the all-contributors specification. Contributions of any kind welcome!

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mitiq, version 0.10.0
Filename, size File type Python version Upload date Hashes
Filename, size mitiq-0.10.0-py3-none-any.whl (125.8 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size mitiq-0.10.0.tar.gz (95.4 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page