QuantumVolume#

class qiskit.circuit.library.QuantumVolume(num_qubits, depth=None, seed=None, classical_permutation=True)[fuente]#

Bases: 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:

(Source code)

../_images/qiskit-circuit-library-QuantumVolume-1.png

Expanded Circuit:

(Source code)

../_images/qiskit-circuit-library-QuantumVolume-2.png

References:

[1] A. Cross et al. Validating quantum computers using randomized model circuits, Phys. Rev. A 100, 032328 (2019). [arXiv:1811.12926]

Create quantum volume model circuit of size num_qubits x depth.

Par谩metros:
  • num_qubits (int) 鈥 number of active qubits in model circuit.

  • depth (int | None) 鈥 layers of SU(4) operations in model circuit.

  • seed (Generator | int | None) 鈥 Random number generator or generator seed.

  • classical_permutation (bool) 鈥 use classical permutations at every layer, rather than quantum.

Attributes

ancillas#

Returns a list of ancilla bits in the order that the registers were added.

calibrations#

Return calibration dictionary.

The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}

clbits#

Returns a list of classical bits in the order that the registers were added.

data#

Return the circuit data (instructions and context).

Devuelve:

a list-like object containing the CircuitInstructions for each instruction.

Tipo del valor devuelto:

QuantumCircuitData

extension_lib = 'include "qelib1.inc";'#
global_phase#

Return the global phase of the circuit in radians.

header = 'OPENQASM 2.0;'#
instances = 425#
layout#

Return any associated layout information about the circuit

This attribute contains an optional TranspileLayout object. This is typically set on the output from transpile() or PassManager.run() to retain information about the permutations caused on the input circuit by transpilation.

There are two types of permutations caused by the transpile() function, an initial layout which permutes the qubits based on the selected physical qubits on the Target, and a final layout which is an output permutation caused by SwapGates inserted during routing.

metadata#

The user provided metadata associated with the circuit.

The metadata for the circuit is a user provided dict of metadata for the circuit. It will not be used to influence the execution or operation of the circuit, but it is expected to be passed between all transforms of the circuit (ie transpilation) and that providers will associate any circuit metadata with the results it returns from execution of that circuit.

num_ancillas#

Return the number of ancilla qubits.

num_clbits#

Return number of classical bits.

num_parameters#

The number of parameter objects in the circuit.

num_qubits#

Return number of qubits.

op_start_times#

Return a list of operation start times.

This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.

Devuelve:

List of integers representing instruction start times. The index corresponds to the index of instruction in QuantumCircuit.data.

Muestra:

AttributeError 鈥 When circuit is not scheduled.

parameters#

The parameters defined in the circuit.

This attribute returns the Parameter objects in the circuit sorted alphabetically. Note that parameters instantiated with a ParameterVector are still sorted numerically.

Ejemplos

The snippet below shows that insertion order of parameters does not matter.

>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> a, b, elephant = Parameter("a"), Parameter("b"), Parameter("elephant")
>>> circuit = QuantumCircuit(1)
>>> circuit.rx(b, 0)
>>> circuit.rz(elephant, 0)
>>> circuit.ry(a, 0)
>>> circuit.parameters  # sorted alphabetically!
ParameterView([Parameter(a), Parameter(b), Parameter(elephant)])

Bear in mind that alphabetical sorting might be unintuitive when it comes to numbers. The literal 芦10禄 comes before 芦2禄 in strict alphabetical sorting.

>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> angles = [Parameter("angle_1"), Parameter("angle_2"), Parameter("angle_10")]
>>> circuit = QuantumCircuit(1)
>>> circuit.u(*angles, 0)
>>> circuit.draw()
   鈹屸攢鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹
q: 鈹 U(angle_1,angle_2,angle_10) 鈹
   鈹斺攢鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹鈹
>>> circuit.parameters
ParameterView([Parameter(angle_1), Parameter(angle_10), Parameter(angle_2)])

To respect numerical sorting, a ParameterVector can be used.


>>> from qiskit.circuit import QuantumCircuit, Parameter, ParameterVector
>>> x = ParameterVector("x", 12)
>>> circuit = QuantumCircuit(1)
>>> for x_i in x:
...     circuit.rx(x_i, 0)
>>> circuit.parameters
ParameterView([
    ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
    ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
    ..., ParameterVectorElement(x[11])
])
Devuelve:

The sorted Parameter objects in the circuit.

prefix = 'circuit'#
qubits#

Returns a list of quantum bits in the order that the registers were added.