OptimizeAnnotated
class qiskit.transpiler.passes.OptimizeAnnotated(*args, **kwargs)
Bases: TransformationPass
Optimization pass on circuits with annotated operations.
Implemented optimizations:
- For each annotated operation, converting the list of its modifiers to a canonical form. For example, consecutively applying
inverse()
,control(2)
andinverse()
is equivalent to applyingcontrol(2)
. - Removing annotations when possible. For example,
AnnotatedOperation(SwapGate(), [InverseModifier(), InverseModifier()])
is equivalent toSwapGate()
. - Recursively combining annotations. For example, if
g1 = AnnotatedOperation(SwapGate(), InverseModifier())
andg2 = AnnotatedOperation(g1, ControlModifier(2))
, theng2
can be replaced withAnnotatedOperation(SwapGate(), [InverseModifier(), ControlModifier(2)])
. - Applies conjugate reduction to annotated operations. As an example,
control - [P -- Q -- P^{-1}]
can be rewritten asP -- control - [Q] -- P^{-1}
, that is, only the middle part needs to be controlled. This also works for inverse and power modifiers.
OptimizeAnnotated initializer.
Parameters
- target – Optional, the backend target to use for this pass.
- equivalence_library – The equivalence library used (instructions in this library will not be optimized by this pass).
- basis_gates – Optional, target basis names to unroll to, e.g. [‘u3’, ‘cx’] (instructions in this list will not be optimized by this pass). Ignored if
target
is also specified. - recurse – By default, when either
target
orbasis_gates
is specified, the pass recursively descends into gate definitions (and the recursion is not applied when neither is specified since such objects do not need to be synthesized). Setting this value toFalse
precludes the recursion in every case. - do_conjugate_reduction – controls whether conjugate reduction should be performed.
Attributes
is_analysis_pass
Check if the pass is an analysis pass.
If the pass is an AnalysisPass, that means that the pass can analyze the DAG and write the results of that analysis in the property set. Modifications on the DAG are not allowed by this kind of pass.
is_transformation_pass
Check if the pass is a transformation pass.
If the pass is a TransformationPass, that means that the pass can manipulate the DAG, but cannot modify the property set (but it can be read).
Methods
execute
execute(passmanager_ir, state, callback=None)
Execute optimization task for input Qiskit IR.
Parameters
- passmanager_ir (Any) – Qiskit IR to optimize.
- state (PassManagerState) – State associated with workflow execution by the pass manager itself.
- callback (Callable | None) – A callback function which is caller per execution of optimization task.
Returns
Optimized Qiskit IR and state of the workflow.
Return type
tuple[Any, qiskit.passmanager.compilation_status.PassManagerState]
name
run
run(dag)
Run the OptimizeAnnotated pass on dag.
Parameters
dag (DAGCircuit) – input dag.
Returns
Output dag with higher-level operations optimized.
Raises
TranspilerError – when something goes wrong.
update_status
update_status(state, run_state)
Update workflow status.
Parameters
- state (PassManagerState) – Pass manager state to update.
- run_state (RunState) – Completion status of current task.
Returns
Updated pass manager state.
Return type