Metadata-Version: 2.1
Name: qiskit-ignis
Version: 0.4.0
Summary: Qiskit tools for quantum information science
Home-page: https://github.com/Qiskit/qiskit-ignis
Author: Qiskit Development Team
Author-email: qiskit@qiskit.org
License: Apache 2.0
Description: # Qiskit Ignis
        
        [![License](https://img.shields.io/github/license/Qiskit/qiskit-ignis.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)[![Build Status](https://img.shields.io/travis/com/Qiskit/qiskit-ignis/master.svg?style=popout-square)](https://travis-ci.com/Qiskit/qiskit-ignis)[![](https://img.shields.io/github/release/Qiskit/qiskit-ignis.svg?style=popout-square)](https://github.com/Qiskit/qiskit-ignis/releases)[![](https://img.shields.io/pypi/dm/qiskit-ignis.svg?style=popout-square)](https://pypi.org/project/qiskit-ignis/)
        
        **Qiskit** is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms.
        
        Qiskit is made up of elements that each work together to enable quantum computing. This element is **Ignis**, which provides tools for quantum hardware verification, noise characterization, and error correction.
        
        
        ## Installation
        
        We encourage installing Qiskit via the PIP tool (a python package manager), which installs all Qiskit elements, including this one.
        
        ```bash
        pip install qiskit
        ```
        
        PIP will handle all dependencies automatically for us and you will always install the latest (and well-tested) version.
        
        To install from source, follow the instructions in the [contribution guidelines](./CONTRIBUTING.md).
        
        ### Extra Requirements
        
        Some functionality has extra optional requirements. If you're going to use any
        visualization functions for fitters you'll need to install matplotlib. You
        can do this with `pip install matplotlib` or when you install ignis with
        `pip install qiskit-ignis[visualization]`. If you're going to use a cvx fitter
        for running tomogography you'll need to install cvxpy. You can do this with
        `pip install cvxpy` or when you install install ignis with
        `pip install qiskit-ignis[cvx]`. If you want to install both when you install
        ignis you can run `pip install qiskit-ignis[visualization,cvx]`.
        
        ## Creating your first quantum experiment with Qiskit Ignis
        Now that you have Qiskit Ignis installed, you can start creating experiments, to reveal information about the device quality. Here is a basic example:
        
        ```
        $ python
        ```
        
        ```python
        # Import Qiskit classes
        import qiskit
        from qiskit import QuantumRegister, QuantumCircuit, ClassicalRegister
        from qiskit.providers.aer import noise # import AER noise model
        
        # Measurement error mitigation functions
        from qiskit.ignis.mitigation.measurement import (complete_meas_cal,
                                                         CompleteMeasFitter, 
                                                         MeasurementFilter)
        
        # Generate a noise model for the qubits
        noise_model = noise.NoiseModel()
        for qi in range(5):
            read_err = noise.errors.readout_error.ReadoutError([[0.75, 0.25],[0.1, 0.9]])
            noise_model.add_readout_error(read_err, [qi])
        
        # Generate the measurement calibration circuits
        # for running measurement error mitigation
        qr = QuantumRegister(5)
        meas_cals, state_labels = complete_meas_cal(qubit_list=[2,3,4], qr=qr)
        
        # Execute the calibration circuits
        backend = qiskit.Aer.get_backend('qasm_simulator')
        job = qiskit.execute(meas_cals, backend=backend, shots=1000, noise_model=noise_model)
        cal_results = job.result()
        
        # Make a calibration matrix
        meas_fitter = CompleteMeasFitter(cal_results, state_labels)
        
        # Make a 3Q GHZ state
        cr = ClassicalRegister(3)
        ghz = QuantumCircuit(qr, cr)
        ghz.h(qr[2])
        ghz.cx(qr[2], qr[3])
        ghz.cx(qr[3], qr[4])
        ghz.measure(qr[2],cr[0])
        ghz.measure(qr[3],cr[1])
        ghz.measure(qr[4],cr[2])
        
        # Execute the GHZ circuit (with the same noise model)
        job = qiskit.execute(ghz, backend=backend, shots=1000, noise_model=noise_model)
        results = job.result()
        
        # Results without mitigation
        raw_counts = results.get_counts()
        print("Results without mitigation:", raw_counts)
        
        # Create a measurement filter from the calibration matrix
        meas_filter = meas_fitter.filter
        # Apply the filter to the raw counts to mitigate 
        # the measurement errors
        mitigated_counts = meas_filter.apply(raw_counts)
        print("Results with mitigation:", {l:int(mitigated_counts[l]) for l in mitigated_counts})
        ```
        
        ```
        Results without mitigation: {'000': 181, '001': 83, '010': 59, '011': 65, '100': 101, '101': 48, '110': 72, '111': 391}
        
        Results with mitigation: {'000': 421, '001': 2, '011': 1, '100': 53, '110': 13, '111': 510}
        ```
        
        ## Contribution guidelines
        
        ## Contribution Guidelines
        
        If you'd like to contribute to Qiskit Ignis, please take a look at our
        [contribution guidelines](./CONTRIBUTING.md). This project adheres to Qiskit's [code of conduct](./CODE_OF_CONDUCT.md). By participating, you are expect to uphold to this code.
        
        We use [GitHub issues](https://github.com/Qiskit/qiskit-ignis/issues) for tracking requests and bugs. Please use our [slack](https://qiskit.slack.com) for discussion and simple questions. To join our Slack community use the [link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk). For questions that are more suited for a forum we use the Qiskit tag in the [Stack Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit).
        
        ## Next Steps
        
        Now you're set up and ready to check out some of the other examples from our
        [Qiskit Tutorials](https://github.com/Qiskit/qiskit-iqx-tutorials/tree/master/qiskit/advanced/ignis) repository.
        
        ## Authors and Citation
        
        Qiskit Ignis is the work of [many people](https://github.com/Qiskit/qiskit-ignis/graphs/contributors) who contribute
        to the project at different levels. If you use Qiskit, please cite as per the included [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).
        
        ## License
        
        [Apache License 2.0](LICENSE.txt)
        
Keywords: qiskit sdk quantum
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: visualization
Provides-Extra: cvx
