Package: quinteng-app
Quinteng AppQuintengis an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms.Quinteng is made up of elements that each work together to enable quantum computing. This element isApp, which provides high-performance quantum computing simulators with realistic noise models.InstallationWe encourage installing Quinteng via the PIP tool (a python package manager), which installs all Quinteng elements, including this one.pipinstallquintengPIP 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.Installing GPU supportIn order to install and run the GPU supported simulators on Linux, you need CUDA® 10.1 or newer previously installed.
CUDA® itself would require a set of specific GPU drivers. Please follow CUDA® installation procedure in the NVIDIA®web.If you want to install our GPU supported simulators, you have to install this other package:pipinstallquinteng-app-gpuThis will overwrite your currentquinteng-apppackage installation giving you
the same functionality found in the canonicalquinteng-apppackage, plus the
ability to run the GPU supported simulators: statevector, density matrix, and unitary.Note: This package is only available on x86_64 Linux. For other platforms
that have CUDA support you will have to build from source. You can refer to
thecontributing guidefor instructions on doing this.Simulating your first quantum program with Quinteng AppNow that you have Quinteng App installed, you can start simulating quantum circuits with noise. Here is a basic example:$ pythonimportquintengfromquintengimportIBMQfromquinteng.providers.appimportAppSimulator# Generate 3-qubit GHZ statecirc=quinteng.QuantumCircuit(3)circ.h(0)circ.cx(0,1)circ.cx(1,2)circ.measure_all()# Construct an ideal simulatorappsim=AppSimulator()# Perform an ideal simulationresult_ideal=quinteng.execute(circ,appsim).result()counts_ideal=result_ideal.get_counts(0)print('Counts(ideal):',counts_ideal)# Counts(ideal): {'000': 493, '111': 531}# Construct a noisy simulator backend from an IBMQ backend# This simulator backend will be automatically configured# using the device configuration and noise modelprovider=IBMQ.load_account()backend=provider.get_backend('ibmq_athens')appsim_backend=AppSimulator.from_backend(backend)# Perform noisy simulationresult_noise=quinteng.execute(circ,appsim_backend).result()counts_noise=result_noise.get_counts(0)print('Counts(noise):',counts_noise)# Counts(noise): {'000': 492, '001': 6, '010': 8, '011': 14, '100': 3, '101': 14, '110': 18, '111': 469}Contribution GuidelinesIf you'd like to contribute to Quinteng, please take a look at ourcontribution guidelines. This project adheres to Quinteng'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 Quinteng tag in theStack Exchange.Next StepsNow you're set up and ready to check out some of the other examples from ourQuinteng IQX TutorialsorQuinteng Community Tutorialsrepositories.Authors and CitationQuinteng App is the work ofmany peoplewho contribute
to the project at different levels. If you use Quinteng, please cite as per the includedBibTeX file.LicenseApache License 2.0