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CollectCliffords

class qiskit_ibm_transpiler.ai.CollectCliffords(do_commutative_analysis: bool = True, min_block_size: int = 2, max_block_size: int = CLIFFORD_MAX_BLOCK_SIZE, collect_from_back: bool = False, num_reps: int = 10)

GitHub

Bases: RepeatedCollectAndCollapse

Collects Clifford blocks as Instruction objects and stores the original sub-circuit to compare against it after synthesis.

Parameters

  • do_commutative_analysis (bool, optional) – Enable or disable commutative analysis, defaults to True
  • min_block_size (int, optional) – Set the minimum size for blocks generated during the collect Cliffords pass, defaults to 2.
  • max_block_size (int, optional) – Set the maximum size for blocks generated during the collect Cliffords pass, defaults to 9.
  • collect_from_back (bool, optional) – Specify if collect blocks in reverse order or not, defaults to False.
  • num_reps (int, optional) – Specify how many times to repeat the optimization process, defaults to 10.

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) – A callback function which is caller per execution of optimization task.

Returns

Optimized Qiskit IR and state of the workflow.

Return type

tuple[Any, PassManagerState]

name

name()

Name of the pass.

Return type

str

run

run(dag)

GitHub

Run the CollectLinearFunctions pass on dag. :param dag: the DAG to be optimized. :type dag: DAGCircuit

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

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