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CircuitSampler

class CircuitSampler(backend, statevector=None, param_qobj=False, attach_results=False, caching='last')

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Bases: qiskit.opflow.converters.converter_base.ConverterBase

The CircuitSampler traverses an Operator and converts any CircuitStateFns into approximations of the state function by a DictStateFn or VectorStateFn using a quantum backend. Note that in order to approximate the value of the CircuitStateFn, it must 1) send state function through a depolarizing channel, which will destroy all phase information and 2) replace the sampled frequencies with square roots of the frequency, rather than the raw probability of sampling (which would be the equivalent of sampling the square of the state function, per the Born rule.

The CircuitSampler aggressively caches transpiled circuits to handle re-parameterization of the same circuit efficiently. If you are converting multiple different Operators, you are better off using a different CircuitSampler for each Operator to avoid cache thrashing.

Parameters

  • backend (Union[Backend, BaseBackend, QuantumInstance]) – The quantum backend or QuantumInstance to use to sample the circuits.
  • statevector (Optional[bool]) – If backend is a statevector backend, whether to replace the CircuitStateFns with DictStateFns (from the counts) or VectorStateFns (from the statevector). None will set this argument automatically based on the backend.
  • attach_results (bool) – Whether to attach the data from the backend Results object for a given CircuitStateFn` to an execution_results field added the converted DictStateFn or VectorStateFn.
  • param_qobj (bool) – Whether to use Aer’s parameterized Qobj capability to avoid re-assembling the circuits.
  • caching (str) – The caching strategy. Can be ‘last’ (default) to store the last operator that was converted, set to ‘all’ to cache all processed operators.

Raises

ValueError – Set statevector or param_qobj True when not supported by backend.


Methods Defined Here

clear_cache

CircuitSampler.clear_cache()

Clear the cache of sampled operator expressions.

Return type

None

convert

CircuitSampler.convert(operator, params=None)

Converts the Operator to one in which the CircuitStateFns are replaced by DictStateFns or VectorStateFns. Extracts the CircuitStateFns out of the Operator, caches them, calls sample_circuits below to get their converted replacements, and replaces the CircuitStateFns in operator with the replacement StateFns.

Parameters

  • operator (OperatorBase) – The Operator to convert
  • params (Optional[Dict[Parameter, Union[float, List[float], List[List[float]]]]]) – A dictionary mapping parameters to either single binding values or lists of binding values.

Return type

OperatorBase

Returns

The converted Operator with CircuitStateFns replaced by DictStateFns or VectorStateFns.

Raises

OpflowError – if extracted circuits are empty.

sample_circuits

CircuitSampler.sample_circuits(circuit_sfns=None, param_bindings=None)

Samples the CircuitStateFns and returns a dict associating their id() values to their replacement DictStateFn or VectorStateFn. If param_bindings is provided, the CircuitStateFns are broken into their parameterizations, and a list of StateFns is returned in the dict for each circuit id(). Note that param_bindings is provided here in a different format than in convert, and lists of parameters within the dict is not supported, and only binding dicts which are valid to be passed into Terra can be included in this list.

Parameters

  • circuit_sfns (Optional[List[CircuitStateFn]]) – The list of CircuitStateFns to sample.
  • param_bindings (Optional[List[Dict[Parameter, float]]]) – The parameterizations to bind to each CircuitStateFn.

Return type

Dict[int, List[StateFn]]

Returns

The dictionary mapping ids of the CircuitStateFns to their replacement StateFns.

Raises

OpflowError – if extracted circuits are empty.


Attributes

quantum_instance

Returns the quantum instance.

Return type

QuantumInstance

Returns

The QuantumInstance used by the CircuitSampler

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