Code source de qiskit.circuit.library.basis_change.qft

# 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
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"""Quantum Fourier Transform Circuit."""

from typing import Optional
import warnings
import numpy as np

from qiskit.circuit import QuantumCircuit, QuantumRegister, CircuitInstruction

from ..blueprintcircuit import BlueprintCircuit

[docs]class QFT(BlueprintCircuit): r"""Quantum Fourier Transform Circuit. The Quantum Fourier Transform (QFT) on :math:`n` qubits is the operation .. math:: |j\rangle \mapsto \frac{1}{2^{n/2}} \sum_{k=0}^{2^n - 1} e^{2\pi ijk / 2^n} |k\rangle The circuit that implements this transformation can be implemented using Hadamard gates on each qubit, a series of controlled-U1 (or Z, depending on the phase) gates and a layer of Swap gates. The layer of Swap gates can in principle be dropped if the QFT appears at the end of the circuit, since then the re-ordering can be done classically. They can be turned off using the ``do_swaps`` attribute. For 4 qubits, the circuit that implements this transformation is: .. plot:: from qiskit.circuit.library import QFT from import _generate_circuit_library_visualization circuit = QFT(4) _generate_circuit_library_visualization(circuit) The inverse QFT can be obtained by calling the ``inverse`` method on this class. The respective circuit diagram is: .. plot:: from qiskit.circuit.library import QFT from import _generate_circuit_library_visualization circuit = QFT(4).inverse() _generate_circuit_library_visualization(circuit) One method to reduce circuit depth is to implement the QFT approximately by ignoring controlled-phase rotations where the angle is beneath a threshold. This is discussed in more detail in or Here, this can be adjusted using the ``approximation_degree`` attribute: the smallest ``approximation_degree`` rotation angles are dropped from the QFT. For instance, a QFT on 5 qubits with approximation degree 2 yields (the barriers are dropped in this example): .. plot:: from qiskit.circuit.library import QFT from import _generate_circuit_library_visualization circuit = QFT(5, approximation_degree=2) _generate_circuit_library_visualization(circuit) """ def __init__( self, num_qubits: Optional[int] = None, approximation_degree: int = 0, do_swaps: bool = True, inverse: bool = False, insert_barriers: bool = False, name: Optional[str] = None, ) -> None: """Construct a new QFT circuit. Args: num_qubits: The number of qubits on which the QFT acts. approximation_degree: The degree of approximation (0 for no approximation). do_swaps: Whether to include the final swaps in the QFT. inverse: If True, the inverse Fourier transform is constructed. insert_barriers: If True, barriers are inserted as visualization improvement. name: The name of the circuit. """ if name is None: name = "IQFT" if inverse else "QFT" super().__init__(name=name) self._approximation_degree = approximation_degree self._do_swaps = do_swaps self._insert_barriers = insert_barriers self._inverse = inverse self.num_qubits = num_qubits @property def num_qubits(self) -> int: """The number of qubits in the QFT circuit. Returns: The number of qubits in the circuit. """ # This method needs to be overwritten to allow adding the setter for num_qubits while still # complying to pylint. return super().num_qubits @num_qubits.setter def num_qubits(self, num_qubits: int) -> None: """Set the number of qubits. Note that this changes the registers of the circuit. Args: num_qubits: The new number of qubits. """ if num_qubits != self.num_qubits: self._invalidate() self.qregs = [] if num_qubits is not None and num_qubits > 0: self.qregs = [QuantumRegister(num_qubits, name="q")] @property def approximation_degree(self) -> int: """The approximation degree of the QFT. Returns: The currently set approximation degree. """ return self._approximation_degree @approximation_degree.setter def approximation_degree(self, approximation_degree: int) -> None: """Set the approximation degree of the QFT. Args: approximation_degree: The new approximation degree. Raises: ValueError: If the approximation degree is smaller than 0. """ if approximation_degree < 0: raise ValueError("Approximation degree cannot be smaller than 0.") if approximation_degree != self._approximation_degree: self._invalidate() self._approximation_degree = approximation_degree @property def insert_barriers(self) -> bool: """Whether barriers are inserted for better visualization or not. Returns: True, if barriers are inserted, False if not. """ return self._insert_barriers @insert_barriers.setter def insert_barriers(self, insert_barriers: bool) -> None: """Specify whether barriers are inserted for better visualization or not. Args: insert_barriers: If True, barriers are inserted, if False not. """ if insert_barriers != self._insert_barriers: self._invalidate() self._insert_barriers = insert_barriers @property def do_swaps(self) -> bool: """Whether the final swaps of the QFT are applied or not. Returns: True, if the final swaps are applied, False if not. """ return self._do_swaps @do_swaps.setter def do_swaps(self, do_swaps: bool) -> None: """Specify whether to do the final swaps of the QFT circuit or not. Args: do_swaps: If True, the final swaps are applied, if False not. """ if do_swaps != self._do_swaps: self._invalidate() self._do_swaps = do_swaps
[docs] def is_inverse(self) -> bool: """Whether the inverse Fourier transform is implemented. Returns: True, if the inverse Fourier transform is implemented, False otherwise. """ return self._inverse
[docs] def inverse(self) -> "QFT": """Invert this circuit. Returns: The inverted circuit. """ if in ("QFT", "IQFT"): name = "QFT" if self._inverse else "IQFT" else: name = + "_dg" inverted = self.copy(name=name) # data consists of the QFT gate only iqft =[0].operation.inverse() = name inverted._append(CircuitInstruction(iqft, inverted.qubits, [])) inverted._inverse = not self._inverse return inverted
def _warn_if_precision_loss(self): """Issue a warning if constructing the circuit will lose precision. If we need an angle smaller than ``pi * 2**-1022``, we start to lose precision by going into the subnormal numbers. We won't lose _all_ precision until an exponent of about 1075, but beyond 1022 we're using fractional bits to represent leading zeros.""" max_num_entanglements = self.num_qubits - self.approximation_degree - 1 if max_num_entanglements > -np.finfo(float).minexp: # > 1022 for doubles. warnings.warn( "precision loss in QFT." f" The rotation needed to represent {max_num_entanglements} entanglements" " is smaller than the smallest normal floating-point number.", category=RuntimeWarning, stacklevel=3, ) def _check_configuration(self, raise_on_failure: bool = True) -> bool: """Check if the current configuration is valid.""" valid = True if self.num_qubits is None: valid = False if raise_on_failure: raise AttributeError("The number of qubits has not been set.") self._warn_if_precision_loss() return valid def _build(self) -> None: """If not already built, build the circuit.""" if self._is_built: return super()._build() num_qubits = self.num_qubits if num_qubits == 0: return circuit = QuantumCircuit(*self.qregs, for j in reversed(range(num_qubits)): circuit.h(j) num_entanglements = max(0, j - max(0, self.approximation_degree - (num_qubits - j - 1))) for k in reversed(range(j - num_entanglements, j)): # Use negative exponents so that the angle safely underflows to zero, rather than # using a temporary variable that overflows to infinity in the worst case. lam = np.pi * (2.0 ** (k - j)) circuit.cp(lam, j, k) if self.insert_barriers: circuit.barrier() if self._do_swaps: for i in range(num_qubits // 2): circuit.swap(i, num_qubits - i - 1) if self._inverse: circuit = circuit.inverse() wrapped = circuit.to_instruction() if self.insert_barriers else circuit.to_gate() self.compose(wrapped, qubits=self.qubits, inplace=True)