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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.

Quickstart#

Installation#

pip install mitiq

Example#

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, noise_level=0.005):
    """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 = 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: {abs((true_value - noisy_value) / true_value):.3f}")
print(f"Error w Mitiq:    {abs((true_value - zne_value) / true_value):.3f}")

Sample output:

Error w/o  Mitiq: 0.264
Error w Mitiq:    0.073

Calibration#

Unsure which error mitigation technique or parameters to use? Try out the calibration module demonstrated below to help find the best parameters for your particular backend!

See our guides and examples for more explanation, techniques, and benchmarks.

Quick Tour#

Error mitigation techniques#

Technique

Documentation

Mitiq module

Paper Reference(s)

Zero-noise extrapolation

ZNE

mitiq.zne

1611.09301
1612.02058
1805.04492

Probabilistic error cancellation

PEC

mitiq.pec

1612.02058
1712.09271
1905.10135

(Variable-noise) Clifford data regression

CDR

mitiq.cdr

2005.10189
2011.01157

Digital dynamical decoupling

DDD

mitiq.ddd

9803057
1807.08768

Readout-error mitigation

REM

mitiq.rem

1907.08518
2006.14044

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

Interface#

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

PennyLane

Cirq logo

Qiskit logo

Rigetti logo

AWS logo

   PennyLane 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 whitepaper using the bibtex entry found in CITATION.bib.

A list of papers citing Mitiq can be found on Google Scholar / Semantic Scholar.

License#

GNU GPL v.3.0.

Contributing#

We welcome contributions to Mitiq including bug fixes, feature requests, etc. To get started, check out our contribution guidelines and/or documentation guidelines.

Contributors ✨#

Thank you to all of the wonderful people that have made this project possible. Non-code contributors are also much appreciated, and are listed here. Thank you to

Contributions of any kind are welcome!