MCMTVChain#

class qiskit.circuit.library.MCMTVChain(gate, num_ctrl_qubits, num_target_qubits)[fuente]#

Bases: MCMT

The MCMT implementation using the CCX V-chain.

This implementation requires ancillas but is decomposed into a much shallower circuit than the default implementation in MCMT.

Expanded Circuit:

(Source code)

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

Examples:

>>> from qiskit.circuit.library import HGate
>>> MCMTVChain(HGate(), 3, 2).draw()
q_0: ──■────────────────────────■──
│ │

q_1: ──■────────────────────────■──
│ │

q_2: ──┼────■──────────────■────┼──
│ │ ┌───┐ │ │

q_3: ──┼────┼──┤ H ├───────┼────┼──
│ │ └─┬─┘┌───┐ │ │

q_4: ──┼────┼────┼──┤ H ├──┼────┼──
┌─┴─┐ │ │ └─┬─┘ │ ┌─┴─┐

q_5: ┤ X ├──■────┼────┼────■──┤ X ├
└───┘┌─┴─┐ │ │ ┌─┴─┐└───┘

q_6: ─────┤ X ├──■────■──┤ X ├─────
└───┘ └───┘

Create a new multi-control multi-target gate.

Parámetros:

gate (Gate | Callable[[QuantumCircuit, Qubit, Qubit], circuit.Instruction]) – The gate to be applied controlled on the control qubits and applied to the target qubits. Can be either a Gate or a circuit method. If it is a callable, it will be casted to a Gate.
num_ctrl_qubits (int) – The number of control qubits.
num_target_qubits (int) – The number of target qubits.

Muestra:

AttributeError – If the gate cannot be casted to a controlled gate.
AttributeError – If the number of controls or targets is 0.

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 = 188#

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_ancilla_qubits#: Return the number of ancilla qubits required.

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 – 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 «10» comes before «2» 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()
   ┌─────────────────────────────┐
q: ┤ U(angle_1,angle_2,angle_10) ├
   └─────────────────────────────┘
>>> 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.

Methods

inverse()[fuente]#: Return the inverse MCMT circuit, which is itself.