qml.labs.zxopt.full_reduce

full_reduce(tape)

ZX-based T gate reduction on an arbitrary PennyLane circuit.

This implements the full pipeline for T gate optimizations in pyzx.

This pipeline performs, in that order

• full_reduce

• normalize

• extract_circuit

In particular, this pipeline does not apply todd() and thus is not restricted to (Clifford + T) circuits. The latter two functions are simply to retrieve the circuit from the ZX graph.

Parameters:

tape (QNode or QuantumTape or Callable) – Input PennyLane circuit.

Returns:

T gate optimized PennyLane circuit. See qml.transform for the different output formats depending on the input type.

Return type:

qnode (QNode) or quantum function (Callable) or tuple[List[QuantumTape], function]

See also

full_optimize()

Example

Let us optimize a circuit with T as well as RZ gates.

from pennylane.labs.zxopt import full_reduce

circ = qml.tape.QuantumScript([
    qml.CNOT((0, 1)),
    qml.T(0),
    qml.CNOT((3, 2)),
    qml.T(1),
    qml.CNOT((1, 2)),
    qml.T(2),
    qml.RZ(0.5, 1),
    qml.CNOT((1, 2)),
    qml.T(1),
    qml.CNOT((3, 2)),
    qml.T(0),
    qml.CNOT((0, 1)),
], [])

print(f"Circuit before:")
print(qml.drawer.tape_text(circ, wire_order=range(4)))

(new_circ,), _ = full_reduce(circ)
print(f"Circuit after full_reduce:")
print(qml.drawer.tape_text(new_circ, wire_order=range(4)))

Circuit before:
0: ─╭●──T──T───────────╭●─┤
1: ─╰X──T─╭●──RZ─╭●──T─╰X─┤
2: ─╭X────╰X──T──╰X─╭X────┤
3: ─╰●──────────────╰●────┤

Circuit after full_reduce:
0: ──S─╭●──────────────╭●─┤
1: ────╰X──RZ─╭●────╭●─╰X─┤
2: ─╭●────────│─────│──╭●─┤
3: ─╰X────────╰X──T─╰X─╰X─┤

The original circuit has five T gates which are reduced to just one.

code/api/api/pennylane.labs.zxopt.full_reduce

 

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