# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Quantum Volume model circuit."""
from typing import Optional, Union
import numpy as np
from qiskit.quantum_info.random import random_unitary
from qiskit.circuit import QuantumCircuit
from qiskit.circuit.library.generalized_gates.permutation import Permutation
[documentos]class QuantumVolume(QuantumCircuit):
"""A quantum volume model circuit.
The model circuits are random instances of circuits used to measure
the Quantum Volume metric, as introduced in [1].
The model circuits consist of layers of Haar random
elements of SU(4) applied between corresponding pairs
of qubits in a random bipartition.
**Reference Circuit:**
.. plot::
from qiskit.circuit.library import QuantumVolume
circuit = QuantumVolume(5, 6, seed=10)
circuit.draw('mpl')
**Expanded Circuit:**
.. plot::
from qiskit.circuit.library import QuantumVolume
from qiskit.tools.jupyter.library import _generate_circuit_library_visualization
circuit = QuantumVolume(5, 6, seed=10, classical_permutation=False)
_generate_circuit_library_visualization(circuit.decompose())
**References:**
[1] A. Cross et al. Validating quantum computers using
randomized model circuits, Phys. Rev. A 100, 032328 (2019).
[`arXiv:1811.12926 <https://arxiv.org/abs/1811.12926>`_]
"""
def __init__(
self,
num_qubits: int,
depth: Optional[int] = None,
seed: Optional[Union[int, np.random.Generator]] = None,
classical_permutation: bool = True,
) -> None:
"""Create quantum volume model circuit of size num_qubits x depth.
Args:
num_qubits: number of active qubits in model circuit.
depth: layers of SU(4) operations in model circuit.
seed: Random number generator or generator seed.
classical_permutation: use classical permutations at every layer,
rather than quantum.
"""
# Initialize RNG
if seed is None:
rng_set = np.random.default_rng()
seed = rng_set.integers(low=1, high=1000)
if isinstance(seed, np.random.Generator):
rng = seed
else:
rng = np.random.default_rng(seed)
# Parameters
depth = depth or num_qubits # how many layers of SU(4)
width = int(np.floor(num_qubits / 2)) # how many SU(4)s fit in each layer
name = "quantum_volume_" + str([num_qubits, depth, seed]).replace(" ", "")
# Generator random unitary seeds in advance.
# Note that this means we are constructing multiple new generator
# objects from low-entropy integer seeds rather than pass the shared
# generator object to the random_unitary function. This is done so
# that we can use the integer seed as a label for the generated gates.
unitary_seeds = rng.integers(low=1, high=1000, size=[depth, width])
# For each layer, generate a permutation of qubits
# Then generate and apply a Haar-random SU(4) to each pair
circuit = QuantumCircuit(num_qubits, name=name)
perm_0 = list(range(num_qubits))
for d in range(depth):
perm = rng.permutation(perm_0)
if not classical_permutation:
layer_perm = Permutation(num_qubits, perm)
circuit.compose(layer_perm, inplace=True)
for w in range(width):
seed_u = unitary_seeds[d][w]
su4 = random_unitary(4, seed=seed_u).to_instruction()
su4.label = "su4_" + str(seed_u)
if classical_permutation:
physical_qubits = int(perm[2 * w]), int(perm[2 * w + 1])
circuit.compose(su4, [physical_qubits[0], physical_qubits[1]], inplace=True)
else:
circuit.compose(su4, [2 * w, 2 * w + 1], inplace=True)
super().__init__(*circuit.qregs, name=circuit.name)
self.compose(circuit.to_instruction(), qubits=self.qubits, inplace=True)