Skip to main contentIBM Quantum Documentation

OptimizeCliffords

qiskit.transpiler.passes.OptimizeCliffords(*args, **kwargs)GitHub(opens in a new tab)

Bases: TransformationPass

Combine consecutive Cliffords over the same qubits. This serves as an example of extra capabilities enabled by storing Cliffords natively on the circuit.


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

Returns

Optimized Qiskit IR and state of the workflow.

Return type

tuple(opens in a new tab)[Any(opens in a new tab), qiskit.passmanager.compilation_status.PassManagerState]

name

name()

Name of the pass.

Return type

str(opens in a new tab)

run

run(dag)

Run the OptimizeCliffords pass on dag.

Parameters

dag (DAGCircuit) – the DAG to be optimized.

Returns

the optimized DAG.

Return type

DAGCircuit

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

PassManagerState

Was this page helpful?