SolovayKitaevDecomposition#
- class qiskit.synthesis.SolovayKitaevDecomposition(basic_approximations=None)[fuente]#
Bases:
object
The Solovay Kitaev discrete decomposition algorithm.
This class is called recursively by the transpiler pass, which is why it is separeted. See
qiskit.transpiler.passes.SolovayKitaev
for more information.- Parámetros:
basic_approximations (str | dict[str, np.ndarray] | list[GateSequence] | None) – A specification of the basic SU(2) approximations in terms of discrete gates. At each iteration this algorithm, the remaining error is approximated with the closest sequence of gates in this set. If a
str
, this specifies a.npy
filename from which to load the approximation. If adict
, then this contains{gates: effective_SO3_matrix}
pairs, e.g.{"h t": np.array([[0, 0.7071, -0.7071], [0, -0.7071, -0.7071], [-1, 0, 0]]}
. If a list, this contains the same information as the dict, but already converted toGateSequence
objects, which contain the SO(3) matrix and gates.
Methods
- find_basic_approximation(sequence)[fuente]#
Finds gate in
self._basic_approximations
that best representssequence
.- Parámetros:
sequence (GateSequence) – The gate to find the approximation to.
- Devuelve:
Gate in basic approximations that is closest to
sequence
.- Tipo del valor devuelto:
- load_basic_approximations(data)[fuente]#
Load basic approximations.
- Parámetros:
data (list | str | dict) – If a string, specifies the path to the file from where to load the data. If a dictionary, directly specifies the decompositions as
{gates: matrix}
. Theregates
are the names of the gates producing the SO(3) matrixmatrix
, e.g.{"h t": np.array([[0, 0.7071, -0.7071], [0, -0.7071, -0.7071], [-1, 0, 0]]}
.- Devuelve:
A list of basic approximations as type
GateSequence
.- Muestra:
ValueError – If the number of gate combinations and associated matrices does not match.
- Tipo del valor devuelto:
list[GateSequence]
- run(gate_matrix, recursion_degree, return_dag=False, check_input=True)[fuente]#
Run the algorithm.
- Parámetros:
gate_matrix (np.ndarray) – The 2x2 matrix representing the gate. This matrix has to be SU(2) up to global phase.
recursion_degree (int) – The recursion degree, called \(n\) in the paper.
return_dag (bool) – If
True
return aDAGCircuit
, else aQuantumCircuit
.check_input (bool) – If
True
check that the input matrix is valid for the decomposition.
- Devuelve:
A one-qubit circuit approximating the
gate_matrix
in the specified discrete basis.- Tipo del valor devuelto:
QuantumCircuit” | “DAGCircuit