BaseReadoutMitigator#
- class qiskit.result.BaseReadoutMitigator[source]#
Bases :
ABCBase readout error mitigator class.
Methods
- abstract expectation_value(data, diagonal, qubits=None, clbits=None, shots=None)[source]#
Calculate the expectation value of a diagonal Hermitian operator.
- Paramètres:
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.
- Renvoie:
The mean and an upper bound of the standard deviation of operator expectation value calculated from the current counts.
- Type renvoyé:
- abstract quasi_probabilities(data, qubits=None, clbits=None, shots=None)[source]#
Convert counts to a dictionary of quasi-probabilities
- Paramètres:
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.
- Renvoie:
- 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.
- Type renvoyé: