qiskit_noise_learning.sequences.LogPathMap
class qiskit_noise_learning.sequences.LogPathMap(fidelity_space: IndexedSpace[FidelityIndex])
Bases: LinearMap[FidelityIndex, Path]
The linear map from a space of log fidelities to its associated log path space.
This map is purely combinatorial: the row of a path is the fragment-depth-weighted multiplicity of each fidelity index appearing in the path. It does not depend on any noise model, only on the Path structure and the fidelity indices’ membership in the input space.
Parameters
fidelity_space – The space of log fidelities.
__init__
__init__(fidelity_space: IndexedSpace[FidelityIndex])
Methods
Column 1 | Column 2 |
|---|---|
__init__(fidelity_space) | |
compose(outer) | Post-compose: self maps I->O, outer maps O->C, result maps I->C. |
left_multiply(matrix) | Multiply on the left by an explicit matrix. |
pre_compose(inner) | Pre-compose: inner maps A->I, self maps I->O, result maps A->O. |
projected_output(output_indices, vector) | Compute a projection of the map applied to a vector. |
rows(output_indices) | Construct the sub-matrix whose rows are the given output indices. |
Attributes
Column 1 | Column 2 |
|---|---|
input_space | The input space. |
output_space | The output space. |
rows
rows(output_indices: Iterable[Path]) → IndexedMatrix[Path, FidelityIndex]
Construct the sub-matrix whose rows are the given output indices.
Parameters
output_indices – The labels for the desired rows of the matrix.
Returns