Skip to main content

No project description provided

Project description

build codecov Documentation Status PyPI version arXiv Unitary Fund

Mitiq

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.

Installation

Mitiq can be installed from PyPi via

pip install mitiq

To test installation, run

import mitiq
mitiq.about()

This prints out version information about core requirements and optional quantum software packages which Mitiq can interface with.

If you'd prefer to clone and install from source, our would like to develop Mitiq, check out the contribution guidelines for more information.

Supported quantum programming libraries

Mitiq can currently interface with

Cirq is a core requirement of Mitiq and is automatically installed. To use Mitiq with other quantum programming libraries, install the optional package(s) following the instructions linked above.

Supported quantum processors

Mitiq can be used on any quantum processor which can be accessed by supported quantum programming libraries and is available to the user.

Getting started

See the getting started guide in Mitiq's documentation for a complete walkthrough of how to use mitiq. For a quick preview, check out the following snippet for a simple example of Mitiq in action:

import numpy as np
from cirq import depolarize, Circuit, DensityMatrixSimulator, LineQubit, X
from mitiq import execute_with_zne

def noisy_simulation(circ: Circuit) -> float:
    """Simulates a circuit with depolarizing noise.

    Args:
        circ: The quantum program as a Cirq Circuit.

    Returns:
        The expectation value of the |0><0| observable.
    """
    circuit = circ.with_noise(depolarize(p=0.001))
    rho = DensityMatrixSimulator().simulate(circuit).final_density_matrix
    return np.real(np.trace(rho @ np.diag([1, 0])))

# simple circuit that should compose to the identity when noiseless
circ = Circuit(X(LineQubit(0)) for _ in range(80))

# run the circuit using a density matrix simulator with depolarizing noise
unmitigated = noisy_simulation(circ)
print(f"Error in simulation (w/o  mitigation): {1.0 - unmitigated:.{3}}")

# run again, but using mitiq's zero-noise extrapolation to mitigate errors
mitigated = execute_with_zne(circ, noisy_simulation)
print(f"Error in simulation (with mitigation): {1.0 - mitigated:.{3}}")

Sample output:

Error in simulation (w/o  mitigation): 0.0506
Error in simulation (with mitigation): 0.000519

Error mitigation techniques

Mitiq currently implements zero-noise extrapolation and is designed to support additional techniques.

Documentation

Mitiq's documentation is hosted at mitiq.readthedocs.io. A PDF version of the latest release can be found here.

Developer information

We welcome contributions to Mitiq including bug fixes, feature requests, etc. Please see the contribution guidelines for more details. To contribute to the documentation, please see these documentation guidelines.

Authors

An up-to-date list of authors can be found here.

Citation

If you use Mitiq in your research, please reference the Mitiq preprint as follows:

@misc{larose2020mitiq,
    title={Mitiq: A software package for error mitigation on noisy quantum computers},
    author={Ryan LaRose and Andrea Mari and Peter J. Karalekas
            and Nathan Shammah and William J. Zeng},
    year={2020},
    eprint={2009.04417},
    archivePrefix={arXiv},
    primaryClass={quant-ph}
}

License

GNU GPL v.3.0.

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

mitiq-0.4.1.tar.gz (61.2 kB view details)

Uploaded Source

Built Distribution

mitiq-0.4.1-py3-none-any.whl (78.8 kB view details)

Uploaded Python 3

File details

Details for the file mitiq-0.4.1.tar.gz.

File metadata

  • Download URL: mitiq-0.4.1.tar.gz
  • Upload date:
  • Size: 61.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.2.post20210110 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.9.1

File hashes

Hashes for mitiq-0.4.1.tar.gz
Algorithm Hash digest
SHA256 5be4996be8cad3d1c46d0dceb33b7463c934bd9c64f7cfd6e7a66b9c16e88675
MD5 b918c680f3fad6f1771bdc5f08962169
BLAKE2b-256 b116bc3bf135b7abf54d34045918af17476e6e86ad1686d014ff108d13129986

See more details on using hashes here.

File details

Details for the file mitiq-0.4.1-py3-none-any.whl.

File metadata

  • Download URL: mitiq-0.4.1-py3-none-any.whl
  • Upload date:
  • Size: 78.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.2.post20210110 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.9.1

File hashes

Hashes for mitiq-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4ae3dc4e45d8301b958675e83fd502c3d37456294c621fa7678f3ddfe73878d8
MD5 f1def87e9e3b285ba2287c8365ba8812
BLAKE2b-256 58ec953b5cb8ff7470eff2bbd3e95e074b623efe1a9dfa43c9d594ed8ab0d1be

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page