qcmet.utils.PauliTwirl

class qcmet.utils.PauliTwirl(gates_to_twirl=None, seed=None)

Randomly insert Pauli twirls around chosen two-qubit gates.

For each targeted gate occurrence, the pass inserts a left and right Pauli so that the overall action is equivalent (up to global phase). By default, CX, ECR, and CZ are twirled.

gates_to_twirl

Iterable of two-qubit gate instances whose base classes define which gates are twirled.

twirl_set

Mapping from gate name to valid Pauli pairs on two qubits.

__init__(gates_to_twirl=None, seed=None)

Initialise the pass.

Parameters:

• gates_to_twirl (optional, Iterable[Gate]) – Gates to twirl. If None, twirls CX, ECR, and CZ.

• seed (optional, int) – Seeding random Pauli twirl pair selection. Defaults to None.

Methods

__init__([gates_to_twirl, seed])	Initialise the pass.
build_twirl_set()	Precompute valid two-qubit Pauli pairs for each target gate.
execute(passmanager_ir, state[, callback])	Execute optimization task for input Qiskit IR.
name()	Name of the pass.
run(dag)	Insert Pauli twirls around matching two-qubit gate nodes.
update_status(state, run_state)	Update workflow status.

Attributes

is_analysis_pass	Check if the pass is an analysis pass.
is_transformation_pass	Check if the pass is a transformation pass.

build_twirl_set()

Precompute valid two-qubit Pauli pairs for each target gate.

A pair (P_left, P_right) is kept if Operator(P_left) @ Operator(gate) is equivalent to Operator(gate) @ Operator(P_right) up to global phase.

run(dag)

Insert Pauli twirls around matching two-qubit gate nodes.

For each matched node, replace it by P_left -> gate -> P_right with a uniformly random Pauli pair from self.twirl_set. If a seed is set on initialization of class, then it will be used here.

Parameters:

dag (DAGCircuit) – Input DAGCircuit.

Return type:

DAGCircuit

Returns:

The modified DAGCircuit.