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BaseReadoutMitigator
class qiskit.result.BaseReadoutMitigator
Bases: ABC
Base readout error mitigator class.
Methods
expectation_value
abstract expectation_value(data, diagonal, qubits=None, clbits=None, shots=None)
Calculate the expectation value of a diagonal Hermitian operator.
Parameters
- data (Counts) – Counts object to be mitigated.
- diagonal (Callable |dict |str |ndarray) – the diagonal operator. This may either be specified as a string containing I,Z,0,1 characters, or as a real valued 1D array_like object supplying the full diagonal, or as a dictionary, or as Callable.
- qubits (Iterable[int] | None) – the physical qubits measured to obtain the counts clbits. If None these are assumed to be qubits [0, …, N-1] for N-bit counts.
- clbits (List[int] | None) – Optional, marginalize counts to just these bits.
- shots (int | None) – Optional, the total number of shots, if None shots will be calculated as the sum of all counts.
Returns
The mean and an upper bound of the standard deviation of operator expectation value calculated from the current counts.
Return type
quasi_probabilities
abstract quasi_probabilities(data, qubits=None, clbits=None, shots=None)
Convert counts to a dictionary of quasi-probabilities
Parameters
- data (Counts) – Counts to be mitigated.
- qubits (Iterable[int] | None) – the physical qubits measured to obtain the counts clbits. If None these are assumed to be qubits [0, …, N-1] for N-bit counts.
- clbits (List[int] | None) – Optional, marginalize counts to just these bits.
- shots (int | None) – Optional, the total number of shots, if None shots will be calculated as the sum of all counts.
Returns
A dictionary containing pairs of [output, mean] where “output”
is the key in the dictionaries, which is the length-N bitstring of a measured standard basis state, and “mean” is the mean of non-zero quasi-probability estimates.
Return type
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