ProcessTomographyFitter
class ProcessTomographyFitter(result, circuits, meas_basis='Pauli', prep_basis='Pauli')
Bases: qiskit.ignis.verification.tomography.fitters.base_fitter.TomographyFitter
Maximum-Likelihood estimation process tomography fitter.
Initialize tomography fitter with experimental data.
Parameters
- result (
Union
[Result
,List
[Result
]]) – a Qiskit Result object obtained from executing tomography circuits. - circuits (
Union
[List
[QuantumCircuit
],List
[str
]]) – a list of circuits or circuit names to extract count information from the result object. - meas_basis (
Union
[TomographyBasis
,str
]) – (default: ‘Pauli’) A function to return measurement operators corresponding to measurement outcomes. See Additional Information. - prep_basis (
Union
[TomographyBasis
,str
]) – (default: ‘Pauli’) A function to return preparation operators. See Additional Information
Methods
add_data
ProcessTomographyFitter.add_data(results, circuits)
Add tomography data from a Qiskit Result object.
Parameters
- results (
List
[Result
]) – The results obtained from executing tomography circuits. - circuits (
List
[Union
[QuantumCircuit
,str
]]) – circuits or circuit names to extract count information from the result object.
Raises
QiskitError – In case some of the tomography data is not found in the results
fit
ProcessTomographyFitter.fit(method='auto', standard_weights=True, beta=0.5, **kwargs)
Reconstruct a quantum channel using CVXPY convex optimization.
Choi matrix
The Choi matrix object is a QuantumChannel representation which may be converted to other representations using the classes SuperOp, Kraus, Stinespring, PTM, Chi from the module qiskit.quantum_info.operators. The raw matrix data for the representation may be obtained by channel.data.
Fitter method
The cvx
fitter method used CVXPY convex optimization package. The lstsq
method uses least-squares fitting (linear inversion). The auto
method will use cvx
if the CVXPY package is found on the system, otherwise it will default to lstsq
.
Objective function
This fitter solves the constrained least-squares minimization:
subject to:
- (PSD)
- (trace)
- (trace_preserving)
where:
- a is the matrix of measurement operators
- b is the vector of expectation value data for each projector
- x is the vectorized Choi-matrix to be fitted
PSD constraint
The PSD keyword constrains the fitted matrix to be postive-semidefinite. For the lstsq
fitter method the fitted matrix is rescaled using the method proposed in Reference [1]. For the cvx
fitter method the convex constraint makes the optimization problem a SDP. If PSD=False the fitted matrix will still be constrained to be Hermitian, but not PSD. In this case the optimization problem becomes a SOCP.
Trace constraint
The trace keyword constrains the trace of the fitted matrix. If trace=None there will be no trace constraint on the fitted matrix. This constraint should not be used for process tomography and the trace preserving constraint should be used instead.
Trace preserving (TP) constraint
The trace_preserving keyword constrains the fitted matrix to be TP. This should only be used for process tomography, not state tomography. Note that the TP constraint implicitly enforces the trace of the fitted matrix to be equal to the square-root of the matrix dimension. If a trace constraint is also specified that differs from this value the fit will likely fail. Note that this can only be used for the CVX method.
CVXPY Solvers:
Various solvers can be called in CVXPY using the solver keyword argument. See the CVXPY documentation for more information on solvers.
References:
[1] J Smolin, JM Gambetta, G Smith, Phys. Rev. Lett. 108, 070502
(2012). Open access: arXiv:1106.5458 [quant-ph].
Parameters
- method (
str
) – (default: ‘auto’) the fitter method ‘auto’, ‘cvx’ or ‘lstsq’. - standard_weights (
bool
) – (default: True) apply weights to tomography data based on count probability - beta (
float
) – (default: 0.5) hedging parameter for converting counts to probabilities - **kwargs – kwargs for fitter method.
Raises
- ValueError – In case the input data is no a valid process matrix
- QiskitError – If the fit method is unrecognized
Returns
The fitted Choi-matrix J for the channel that maximizes . The Numpy matrix can be obtained from Choi.data.
Return type
set_measure_basis
ProcessTomographyFitter.set_measure_basis(basis)
Set the measurement basis
Parameters
basis (Union
[TomographyBasis
, str
]) – measurement basis
Raises
QiskitError – In case of invalid measurement or preparation basis.
set_preparation_basis
ProcessTomographyFitter.set_preparation_basis(basis)
Set the preparation basis function
Parameters
basis (Union
[TomographyBasis
, str
]) – preparation basis
Raises
QiskitError – in case the basis has no preperation data
Attributes
data
Return tomography data
measure_basis
Return the tomography measurement basis.
preparation_basis
Return the tomography preparation basis.