Package: qiskit-ignis
Qiskit Ignis (DEPRECATED)NOTEAs of the version 0.7.0 Qiskit Ignis is deprecated and has been
superseded by theQiskit Experimentsproject.
Active development on the project has stopped and only compatibility fixes
and other critical bugfixes will be accepted until the project is officially
retired and archived.Qiskitis 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 isIgnis, which provides tools for quantum hardware verification, noise characterization, and error correction.Migration GuideAs of version 0.7.0, Qiskit Ignis has been deprecated and some of its functionality
was migrated into theqiskit-experimentspackage and intoqiskit-terra.Ignis characterization moduleThis module was partly migrated toqiskit-experimentsand split into two different modules:qiskit_experiments.library.calibrationqiskit_experiments.library.characterizationAmpCalis now replaced byFineAmplitude.ZZFitterwas not migrated yet.Ignis discriminator moduleThis module is in the process of migration toqiskit-experimentsIgnis mitigation moduleThe readout mitigator will be soon added toqiskit-terra.Experiments for generating the readout mitigators will be added toqiskit-experimentsFor use of mitigators withqiskit.algorithmsand theQuantumInstanceclassthis has been integrated intoqiskit-terradirectly with theQuantumInstance.Ignis verification moduleRandomized benchmarking, Quantum Volume and State and Process Tomography were migrated toqiskit-experiments.Migration of Gate-set tomography toqiskit-experimentsis in progress.topological_codeswill continue development underNCCR-SPIN, while the functionality is reintegrated into Qiskit. Some additional functionality can also be found in the offshoot projectqtcodes.Currently the Accredition and Entanglement modules have not been migrated.The following table gives a more detailed breakdown that relates the function, as it existed in Ignis,
to where it now lives after this move.OldNewLibraryqiskit.ignis.characterization.calibrationsqiskit_experiments.library.calibrationqiskit-experimentsqiskit.ignis.characterization.coherenceqiskit_experiments.library.characterizationqiskit-experimentsqiskit.ignis.mitigationqiskit_terra.mitigationqiskit-terraqiskit.ignis.verification.quantum_volumeqiskit_experiments.library.quantum_volumeqiskit-experimentsqiskit.ignis.verification.randomized_benchmarkingqiskit_experiments.library.randomized_benchmarkingqiskit-experimentsqiskit.ignis.verification.tomographyqiskit_experiments.library.tomographyqiskit-experimentsInstallationWe encourage installing Qiskit via the pip tool (a python package manager). The following command installs the core Qiskit components, including Ignis.pipinstallqiskitPip 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 thecontribution guidelines.Extra RequirementsSome 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 withpip install matplotlibor when you install ignis withpip 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 withpip install cvxpyor when you install ignis withpip install qiskit-ignis[cvx]. When performing expectation value measurement
error mitigation using the CTMP method performance can be improved using
just-in-time compiling if Numbda is installed. You can do this withpip install numbaor when you install ignis withpip install qiskit-ignis[jit]. For using the discriminator classes inqiskit.ignis.measurementscikit-learn needs to be installed. You can do this withpip install scikit-learnor when you install ignis withpip install qiskit-ignis[iq]. If you want to install all extra requirements
when you install ignis you can runpip install qiskit-ignis[visualization,cvx,jit,iq].Creating your first quantum experiment with Qiskit IgnisNow that you have Qiskit Ignis installed, you can start creating experiments, to reveal information about the device quality. Here is a basic example:$ python# Import Qiskit classesimportqiskitfromqiskitimportQuantumRegister,QuantumCircuit,ClassicalRegisterfromqiskit.providers.aerimportnoise# import AER noise model# Measurement error mitigation functionsfromqiskit.ignis.mitigation.measurementimport(complete_meas_cal,CompleteMeasFitter,MeasurementFilter)# Generate a noise model for the qubitsnoise_model=noise.NoiseModel()forqiinrange(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 mitigationqr=QuantumRegister(5)meas_cals,state_labels=complete_meas_cal(qubit_list=[2,3,4],qr=qr)# Execute the calibration circuitsbackend=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 matrixmeas_fitter=CompleteMeasFitter(cal_results,state_labels)# Make a 3Q GHZ statecr=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 mitigationraw_counts=results.get_counts()print("Results without mitigation:",raw_counts)# Create a measurement filter from the calibration matrixmeas_filter=meas_fitter.filter# Apply the filter to the raw counts to mitigate# the measurement errorsmitigated_counts=meas_filter.apply(raw_counts)print("Results with mitigation:",{l:int(mitigated_counts[l])forlinmitigated_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 GuidelinesIf you'd like to contribute to Qiskit Ignis, please take a look at ourcontribution guidelines. This project adheres to Qiskit'scode of conduct. By participating, you are expect to uphold to this code.We useGitHub issuesfor tracking requests and bugs. Please use ourslackfor discussion and simple questions. To join our Slack community use thelink. For questions that are more suited for a forum we use the Qiskit tag in theStack Exchange.Next StepsNow you're set up and ready to check out some of the other examples from ourQiskit Tutorialsrepository.Authors and CitationQiskit Ignis is the work ofmany peoplewho contribute
to the project at different levels. If you use Qiskit, please cite as per the includedBibTeX file.LicenseApache License 2.0