Metadata-Version: 2.1
Name: mitiq
Version: 0.5.0
Summary: UNKNOWN
Home-page: https://unitary.fund
Author: Unitary Fund
License: GPL v3.0
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        # 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](https://mitiq.readthedocs.io/en/stable/guide/guide-overview.html).
        
        ## Installation
        
        Mitiq can be installed from PyPi via
        
        ```bash
        pip install mitiq
        ```
        
        To test installation, run
        
        ```python
        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](https://mitiq.readthedocs.io/en/stable/toc_contributing.html) for more information.
        
        ### Supported quantum programming libraries
        
        Mitiq can currently interface with:
        
        * [Cirq](https://github.com/quantumlib/Cirq),
        * [Qiskit](https://qiskit.org/),
        * [pyQuil](https://github.com/rigetti/pyquil).
        
        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](https://mitiq.readthedocs.io/en/stable/guide/guide-getting-started.html) guide in
        [Mitiq's documentation](https://mitiq.readthedocs.io) 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:
        
        ```python
        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](https://mitiq.readthedocs.io/en/stable/guide/guide-zne.html),
        * [Probabilistic Error Cancellation](https://mitiq.readthedocs.io/en/stable/guide/guide-getting-started.html#error-mitigation-with-probabilistic-error-cancellation),
         
        and is designed to support [additional techniques](https://github.com/unitaryfund/mitiq/wiki).
        
        ## Documentation
        
        Mitiq's documentation is hosted at [mitiq.readthedocs.io](https://mitiq.readthedocs.io). A PDF version of the latest 
        release can be found [here](https://mitiq.readthedocs.io/_/downloads/en/latest/pdf/).
        
        ## Developer information
        
        We welcome contributions to Mitiq including bug fixes, feature requests, etc.
        Please see the  [contribution guidelines](https://mitiq.readthedocs.io/en/stable/toc_contributing.html) for more details.
        To contribute to the documentation, please see these [documentation guidelines](https://mitiq.readthedocs.io/en/stable/contributing_docs.html).
        
        ## Authors
        
        An up-to-date list of authors can be found [here](https://github.com/unitaryfund/mitiq/graphs/contributors).
        
        ## Citation
        
        If you use Mitiq in your research, please reference the [Mitiq preprint][arxiv] as follows:
        
        ```bibtex
        @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}
        }
        ```
        
        [arxiv]: https://arxiv.org/abs/2009.04417
        
        ## License
        
        [GNU GPL v.3.0.](https://github.com/unitaryfund/mitiq/blob/master/LICENSE)
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: MacOS
Classifier: Operating System :: Unix
Classifier: Operating System :: Microsoft :: Windows
Classifier: Topic :: Scientific/Engineering
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