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IBM Quantum Platform

qiskit_noise_learning.sequences.LogPathSpace

class qiskit_noise_learning.sequences.LogPathSpace(fidelity_space: IndexedSpace[FidelityIndex])

GitHub

Bases: IndexedSpace[Path]

The (infinite-dimensional) space of log path-fidelities.

For a Path, the “path-fidelity” is:

  • If the path is unbound, the product of the fidelities in the repeatable fragment.
  • If the path is bound, the product of all fidelities in the path (counting multiplicities).

This corresponds to the sign-corrected observable of an experiment traversing the path.

The log path space represents the vector space of such log path-fidelities, indexed by the paths themselves. It is defined relative to a space of log fidelities: a path is a member if all of the fidelity indices in its fragments are members of that fidelity space.

Parameters

fidelity_space – The space of log fidelities whose fidelity indices the paths are built from.

__init__

__init__(fidelity_space: IndexedSpace[FidelityIndex])


Methods

Column 1
Column 2
__init__(fidelity_space)

Attributes

Column 1
Column 2
dimThe dimension (cardinality) of the space.
fidelity_spaceThe space of log fidelities whose fidelity indices the paths are built from.

fidelity_space

Type: IndexedSpace[FidelityIndex]

The space of log fidelities whose fidelity indices the paths are built from.

dim

Type: int | float

The dimension (cardinality) of the space.

May be math.inf for infinite-dimensional spaces.

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