164 lines
9.2 KiB
Plaintext
164 lines
9.2 KiB
Plaintext
---
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title: execute_function
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description: API reference for qiskit.execute_function
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in_page_toc_min_heading_level: 2
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python_api_type: module
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python_api_name: qiskit.execute_function
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---
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<span id="module-qiskit.execute_function" />
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<span id="qiskit-execute" />
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# Executing Experiments
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<span id="module-qiskit.execute_function" />
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`qiskit.execute_function`
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### execute
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<Function id="qiskit.execute_function.execute" github="https://github.com/qiskit/qiskit/tree/stable/0.17/qiskit/execute_function.py" signature="execute(experiments, backend, basis_gates=None, coupling_map=None, backend_properties=None, initial_layout=None, seed_transpiler=None, optimization_level=None, pass_manager=None, qobj_id=None, qobj_header=None, shots=None, memory=False, max_credits=None, seed_simulator=None, default_qubit_los=None, default_meas_los=None, schedule_los=None, meas_level=None, meas_return=None, memory_slots=None, memory_slot_size=None, rep_time=None, rep_delay=None, parameter_binds=None, schedule_circuit=False, inst_map=None, meas_map=None, scheduling_method=None, init_qubits=None, **run_config)">
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Execute a list of [`qiskit.circuit.QuantumCircuit`](qiskit.circuit.QuantumCircuit "qiskit.circuit.QuantumCircuit") or [`qiskit.pulse.Schedule`](qiskit.pulse.Schedule "qiskit.pulse.Schedule") on a backend.
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The execution is asynchronous, and a handle to a job instance is returned.
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**Parameters**
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* **experiments** ([*QuantumCircuit*](qiskit.circuit.QuantumCircuit "qiskit.circuit.QuantumCircuit") *or list\[*[*QuantumCircuit*](qiskit.circuit.QuantumCircuit "qiskit.circuit.QuantumCircuit")*] or* [*Schedule*](qiskit.pulse.Schedule "qiskit.pulse.Schedule") *or list\[*[*Schedule*](qiskit.pulse.Schedule "qiskit.pulse.Schedule")*]*) – Circuit(s) or pulse schedule(s) to execute
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* **backend** ([*BaseBackend*](qiskit.providers.BaseBackend "qiskit.providers.BaseBackend") *or*[*Backend*](qiskit.providers.Backend "qiskit.providers.Backend")) – Backend to execute circuits on. Transpiler options are automatically grabbed from backend.configuration() and backend.properties(). If any other option is explicitly set (e.g. coupling\_map), it will override the backend’s.
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* **basis\_gates** (*list\[str]*) – List of basis gate names to unroll to. e.g: `['u1', 'u2', 'u3', 'cx']` If `None`, do not unroll.
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* **coupling\_map** ([*CouplingMap*](qiskit.transpiler.CouplingMap "qiskit.transpiler.CouplingMap") *or list*) –
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Coupling map (perhaps custom) to target in mapping. Multiple formats are supported:
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1. CouplingMap instance
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2. list Must be given as an adjacency matrix, where each entry specifies all two-qubit interactions supported by backend e.g: `[[0, 1], [0, 3], [1, 2], [1, 5], [2, 5], [4, 1], [5, 3]]`
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* **backend\_properties** ([*BackendProperties*](qiskit.providers.models.BackendProperties "qiskit.providers.models.BackendProperties")) – Properties returned by a backend, including information on gate errors, readout errors, qubit coherence times, etc. Find a backend that provides this information with: `backend.properties()`
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* **initial\_layout** ([*Layout*](qiskit.transpiler.Layout "qiskit.transpiler.Layout") *or dict or list*) –
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Initial position of virtual qubits on physical qubits. If this layout makes the circuit compatible with the coupling\_map constraints, it will be used. The final layout is not guaranteed to be the same, as the transpiler may permute qubits through swaps or other means.
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Multiple formats are supported:
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1. [`qiskit.transpiler.Layout`](qiskit.transpiler.Layout "qiskit.transpiler.Layout") instance
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2. `dict`: virtual to physical:
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```python
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{qr[0]: 0,
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qr[1]: 3,
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qr[2]: 5}
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```
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**physical to virtual::**
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**\{0: qr\[0],**
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3: qr\[1], 5: qr\[2]}
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3. `list` virtual to physical:
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```python
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[0, 3, 5] # virtual qubits are ordered (in addition to named)
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```
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physical to virtual:
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```python
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[qr[0], None, None, qr[1], None, qr[2]]
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```
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* **seed\_transpiler** (*int*) – Sets random seed for the stochastic parts of the transpiler
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* **optimization\_level** (*int*) – How much optimization to perform on the circuits. Higher levels generate more optimized circuits, at the expense of longer transpilation time. #. No optimization #. Light optimization #. Heavy optimization #. Highest optimization If None, level 1 will be chosen as default.
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* **pass\_manager** ([*PassManager*](qiskit.transpiler.PassManager "qiskit.transpiler.PassManager")) – The pass manager to use during transpilation. If this arg is present, auto-selection of pass manager based on the transpile options will be turned off and this pass manager will be used directly.
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* **qobj\_id** (*str*) – String identifier to annotate the Qobj
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* **qobj\_header** ([*QobjHeader*](qiskit.qobj.QobjHeader "qiskit.qobj.QobjHeader") *or dict*) – User input that will be inserted in Qobj header, and will also be copied to the corresponding [`qiskit.result.Result`](qiskit.result.Result "qiskit.result.Result") header. Headers do not affect the run.
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* **shots** (*int*) – Number of repetitions of each circuit, for sampling. Default: 1024
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* **memory** (*bool*) – If True, per-shot measurement bitstrings are returned as well (provided the backend supports it). For OpenPulse jobs, only measurement level 2 supports this option. Default: False
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* **max\_credits** (*int*) – Maximum credits to spend on job. Default: 10
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* **seed\_simulator** (*int*) – Random seed to control sampling, for when backend is a simulator
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* **default\_qubit\_los** (*list*) – List of default qubit LO frequencies in Hz
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* **default\_meas\_los** (*list*) – List of default meas LO frequencies in Hz
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* **schedule\_los** (*None or list or dict or LoConfig*) –
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Experiment LO configurations, if specified the list is in the format:
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```python
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list[Union[Dict[PulseChannel, float], LoConfig]] or
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Union[Dict[PulseChannel, float], LoConfig]
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```
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* **meas\_level** (*int or MeasLevel*) – Set the appropriate level of the measurement output for pulse experiments.
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* **meas\_return** (*str or MeasReturn*) – Level of measurement data for the backend to return For `meas_level` 0 and 1: `"single"` returns information from every shot. `"avg"` returns average measurement output (averaged over number of shots).
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* **memory\_slots** (*int*) – Number of classical memory slots used in this job.
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* **memory\_slot\_size** (*int*) – Size of each memory slot if the output is Level 0.
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* **rep\_time** (*int*) – Time per program execution in seconds. Must be from the list provided by the backend (`backend.configuration().rep_times`). Defaults to the first entry.
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* **rep\_delay** (*float*) – Delay between programs in seconds. Only supported on certain backends (`backend.configuration().dynamic_reprate_enabled` ). If supported, `rep_delay` will be used instead of `rep_time` and must be from the range supplied by the backend (`backend.configuration().rep_delay_range`). Default is given by `backend.configuration().default_rep_delay`.
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* **parameter\_binds** (*list\[dict]*) – List of Parameter bindings over which the set of experiments will be executed. Each list element (bind) should be of the form `{Parameter1: value1, Parameter2: value2, ...}`. All binds will be executed across all experiments, e.g. if parameter\_binds is a length-n list, and there are m experiments, a total of $m x n$ experiments will be run (one for each experiment/bind pair).
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* **schedule\_circuit** (*bool*) – If `True`, `experiments` will be converted to [`qiskit.pulse.Schedule`](qiskit.pulse.Schedule "qiskit.pulse.Schedule") objects prior to execution.
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* **inst\_map** ([*InstructionScheduleMap*](qiskit.pulse.InstructionScheduleMap "qiskit.pulse.InstructionScheduleMap")) – Mapping of circuit operations to pulse schedules. If None, defaults to the `instruction_schedule_map` of `backend`.
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* **meas\_map** (*list(list(int))*) – List of sets of qubits that must be measured together. If None, defaults to the `meas_map` of `backend`.
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* **scheduling\_method** (*str or list(str)*) – Optionally specify a particular scheduling method.
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* **init\_qubits** (*bool*) – Whether to reset the qubits to the ground state for each shot. Default: `True`.
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* **run\_config** (*dict*) – Extra arguments used to configure the run (e.g. for Aer configurable backends). Refer to the backend documentation for details on these arguments. Note: for now, these keyword arguments will both be copied to the Qobj config, and passed to backend.run()
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**Returns**
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returns job instance derived from BaseJob
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**Return type**
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[BaseJob](qiskit.providers.BaseJob "qiskit.providers.BaseJob")
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**Raises**
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**QiskitError** – if the execution cannot be interpreted as either circuits or schedules
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**Example**
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Construct a 5-qubit GHZ circuit and execute 4321 shots on a backend.
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```python
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from qiskit import QuantumCircuit, execute, BasicAer
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backend = BasicAer.get_backend('qasm_simulator')
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qc = QuantumCircuit(5, 5)
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qc.h(0)
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qc.cx(0, range(1, 5))
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qc.measure_all()
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job = execute(qc, backend, shots=4321)
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```
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</Function>
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