iZ#^SrSSKrSSKrSSKrSSKJr SSKJr SSKJ r SSK J r SSK J r Jr SS KJr SS KJr SS K7 SS KJr SS KJr SSKJrJr SSKJrJr SSKJrJ r J!r!J!r" \RF"\$5r%\"\%5 Sr&Sr'Sr(\RRS:a\RT"S\+SS9 gg)a ========================================== Qiskit Runtime (:mod:`qiskit_ibm_runtime`) ========================================== .. currentmodule:: qiskit_ibm_runtime Modules related to Qiskit Runtime IBM Client. Qiskit Runtime is a new architecture that streamlines computations requiring many iterations. These experiments will execute significantly faster within its improved hybrid quantum/classical process. Primitives and sessions ======================= Qiskit Runtime has two predefined primitives: ``Sampler`` and ``Estimator``. These primitives provide a simplified interface for performing foundational quantum computing tasks while also accounting for the latest developments in quantum hardware and software. Qiskit Runtime also has the concept of a session. Jobs submitted within a session are prioritized by the scheduler. A session allows you to make iterative calls to the quantum computer more efficiently. Below is an example of using primitives within a session:: from qiskit_ibm_runtime import QiskitRuntimeService, Session from qiskit_ibm_runtime import SamplerV2 as Sampler from qiskit_ibm_runtime import EstimatorV2 as Estimator from qiskit.circuit.library import real_amplitudes from qiskit.circuit import QuantumCircuit, QuantumRegister, ClassicalRegister from qiskit.quantum_info import SparsePauliOp from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager # Initialize account. service = QiskitRuntimeService() # Prepare inputs. psi = real_amplitudes(num_qubits=2, reps=2) H1 = SparsePauliOp.from_list([("II", 1), ("IZ", 2), ("XI", 3)]) theta = [0, 1, 1, 2, 3, 5] # Bell Circuit qr = QuantumRegister(2, name="qr") cr = ClassicalRegister(2, name="cr") qc = QuantumCircuit(qr, cr, name="bell") qc.h(qr[0]) qc.cx(qr[0], qr[1]) qc.measure(qr, cr) backend = service.least_busy(operational=True, simulator=False) pm = generate_preset_pass_manager(target=backend.target, optimization_level=1) bell_isa_circuit = pm.run(qc) psi_isa_circuit = pm.run(psi) isa_observables = H1.apply_layout(psi_isa_circuit.layout) with Session(backend=backend) as session: # Submit a request to the Sampler primitive within the session. sampler = Sampler(mode=session) job = sampler.run([bell_isa_circuit]) pub_result = job.result()[0] print(f"Counts: {pub_result.data.cr.get_counts()}") # Submit a request to the Estimator primitive within the session. estimator = Estimator(mode=session) estimator.options.resilience_level = 1 # Set options. job = estimator.run( [(psi_isa_circuit, isa_observables, theta)] ) pub_result = job.result()[0] print(f"Expectation values: {pub_result.data.evs}") Local testing mode ================== You can validate your quantum programs before sending them to a physical system using the local testing mode. The local testing mode is activated if one of the fake backends in ``qiskit_ibm_runtime.fake_provider`` or a Qiskit Aer backend instance is used when instantiating a primitive or a session. For example:: from qiskit_aer import AerSimulator from qiskit.circuit.library import real_amplitudes from qiskit.circuit import QuantumCircuit, QuantumRegister, ClassicalRegister from qiskit.quantum_info import SparsePauliOp from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager from qiskit_ibm_runtime import Session from qiskit_ibm_runtime import SamplerV2 as Sampler from qiskit_ibm_runtime.fake_provider import FakeManilaV2 # Bell Circuit qc = QuantumCircuit(2) qc.h(0) qc.cx(0, 1) qc.measure_all() # Run the sampler job locally using FakeManilaV2 fake_manila = FakeManilaV2() pm = generate_preset_pass_manager(backend=fake_manila, optimization_level=1) isa_qc = pm.run(qc) sampler = Sampler(backend=fake_manila) result = sampler.run([isa_qc]).result() # Run the sampler job locally using AerSimulator. # Session syntax is supported but ignored. aer_sim = AerSimulator() pm = generate_preset_pass_manager(backend=aer_sim, optimization_level=1) isa_qc = pm.run(qc) with Session(backend=aer_sim) as session: sampler = Sampler(mode=session) result = sampler.run([isa_qc]).result() Backend data ============ :class:`QiskitRuntimeService` also has methods, such as :meth:`backend`, :meth:`backends`, and :meth:`least_busy`, that allow you to query for a target backend to use. These methods return one or more :class:`IBMBackend` instances that contains methods and attributes describing the backend. Supplementary Information ========================= Account initialization ------------------------- You need to initialize your account before you can start using the Qiskit Runtime service. This is done by initializing a :class:`QiskitRuntimeService` instance with your account credentials. If you don't want to pass in the credentials each time, you can use the :meth:`QiskitRuntimeService.save_account` method to save the credentials on disk. Qiskit Runtime is available on IBM Cloud, and you can specify the channel with ``channel="ibm_cloud"`` or ``channel="ibm_quantum_platform"``. Runtime Jobs ------------ When you use the ``run()`` method of the :class:`Sampler` or :class:`Estimator` to invoke the primitive, a :class:`RuntimeJobV2` instance is returned. This class has all the basic job methods, such as :meth:`RuntimeJobV2.status`, :meth:`RuntimeJobV2.result`, and :meth:`RuntimeJobV2.cancel`. Logging ------- ``qiskit-ibm-runtime`` uses the ``qiskit_ibm_runtime`` logger. Two environment variables can be used to control the logging: * ``QISKIT_IBM_RUNTIME_LOG_LEVEL``: Specifies the log level to use. If an invalid level is set, the log level defaults to ``WARNING``. The valid log levels are ``DEBUG``, ``INFO``, ``WARNING``, ``ERROR``, and ``CRITICAL`` (case-insensitive). If the environment variable is not set, then the parent logger's level is used, which also defaults to ``WARNING``. * ``QISKIT_IBM_RUNTIME_LOG_FILE``: Specifies the name of the log file to use. If specified, messages will be logged to the file only. Otherwise messages will be logged to the standard error (usually the screen). For more advanced use, you can modify the logger itself. For example, to manually set the level to ``WARNING``:: import logging logging.getLogger('qiskit_ibm_runtime').setLevel(logging.WARNING) Classes ======= .. autosummary:: :toctree: ../stubs/ :nosignatures: QiskitRuntimeService Estimator EstimatorV2 Sampler SamplerV2 Session Batch IBMBackend RuntimeJobV2 RuntimeEncoder RuntimeDecoder N)QiskitRuntimeService) IBMBackend) RuntimeJobV2)RuntimeOptions)RuntimeEncoderRuntimeDecoder)Session)Batch)*) setup_logger) __version__) EstimatorV2r) SamplerV2r)EstimatorOptionsSamplerOptions OptionsV2rqiskit_ibm_runtimeQISKIT_IBM_RUNTIME_LOG_LEVELQISKIT_IBM_RUNTIME_LOG_FILE) zUsing qiskit-ibm-runtime with Python 3.9 is deprecated as of the 0.41.0 release. Support for running qiskit-ibm-runtime with Python 3.9 will be removed in a future release.) stacklevel),__doc__sysloggingwarningsqiskit_runtime_servicer ibm_backendrruntime_job_v2rruntime_optionsr utils.jsonrr sessionr batchr exceptions utils.utilsr versionr estimatorr EstimatorsamplerrSampleroptionsrrrOptions getLogger__name__loggerQISKIT_IBM_RUNTIME_LOGGER_NAMErr version_infowarnDeprecationWarningU/home/james-whalen/.local/lib/python3.13/site-packages/qiskit_ibm_runtime/__init__.pyr9syv 8#(+6% 5   8 $ V"6)=];\g MM   r7