Source code for lambeq.ansatz.circuit

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"""
Circuit Ansatz
==============
A circuit ansatz converts a DisCoCat diagram into a quantum circuit.

"""
from __future__ import annotations

__all__ = ['CircuitAnsatz', 'IQPAnsatz']

from abc import abstractmethod
from collections.abc import Mapping
from itertools import cycle
from typing import Callable, Optional

from discopy.quantum.circuit import (Circuit, Discard, Functor, Id,
                                     IQPansatz as IQP, qubit,
                                     Sim14ansatz as Sim14,
                                     Sim15ansatz as Sim15)
from discopy.quantum.gates import Bra, H, Ket, Rx, Ry, Rz
from discopy.rigid import Box, Diagram, Ty
import numpy as np
from sympy import Symbol, symbols

from lambeq.ansatz import BaseAnsatz

computational_basis = Id(qubit)


[docs]class CircuitAnsatz(BaseAnsatz): """Base class for circuit ansatz."""
[docs] def __init__(self, ob_map: Mapping[Ty, int], n_layers: int, n_single_qubit_params: int, circuit: Callable[[int, np.ndarray], Circuit], discard: bool = False, single_qubit_rotations: Optional[list[Circuit]] = None, postselection_basis: Circuit = computational_basis) -> None: """Instantiate a circuit ansatz. Parameters ---------- ob_map : dict A mapping from :py:class:`discopy.rigid.Ty` to the number of qubits it uses in a circuit. n_layers : int The number of layers used by the ansatz. n_single_qubit_params : int The number of single qubit rotations used by the ansatz. circuit : callable Circuit generator used by the ansatz. This is a function (or a class constructor) that takes a number of qubits and a numpy array of parameters, and returns the ansatz of that size, with parameterised boxes. discard : bool, default: False Discard open wires instead of post-selecting. postselection_basis: Circuit, default: Id(qubit) Basis to post-select in, by default the computational basis. single_qubit_rotations: list of Circuit, optional The rotations to be used for a single qubit. When only a single qubit is present, the ansatz defaults to applying a series of rotations in a cycle, determined by this parameter and `n_single_qubit_params`. """ self.ob_map = ob_map self.n_layers = n_layers self.n_single_qubit_params = n_single_qubit_params self.circuit = circuit self.discard = discard self.postselection_basis = postselection_basis self.single_qubit_rotations = single_qubit_rotations or [] self.functor = Functor(ob=ob_map, ar=self._ar)
[docs] def __call__(self, diagram: Diagram) -> Circuit: """Convert a DisCoPy diagram into a DisCoPy circuit.""" return self.functor(diagram)
[docs] def ob_size(self, pg_type: Ty) -> int: """Calculate the number of qubits used for a given type.""" return sum(self.ob_map[Ty(factor.name)] for factor in pg_type)
[docs] @abstractmethod def params_shape(self, n_qubits: int) -> tuple[int, ...]: """Calculate the shape of the parameters required."""
def _ar(self, box: Box) -> Circuit: label = self._summarise_box(box) dom, cod = self.ob_size(box.dom), self.ob_size(box.cod) n_qubits = max(dom, cod) if n_qubits == 0: circuit = Id() elif n_qubits == 1: syms = symbols(f'{label}_0:{self.n_single_qubit_params}', cls=Symbol) circuit = Id(qubit) for rot, sym in zip(cycle(self.single_qubit_rotations), syms): circuit >>= rot(sym) else: params_shape = self.params_shape(n_qubits) syms = symbols(f'{label}_0:{np.prod(params_shape)}', cls=Symbol) params: np.ndarray = np.array(syms).reshape(params_shape) circuit = self.circuit(n_qubits, params) if cod > dom: circuit <<= Id(dom) @ Ket(*[0]*(cod - dom)) elif self.discard: circuit >>= Id(cod) @ Discard(dom - cod) else: circuit >>= Id(cod).tensor(*[self.postselection_basis] * (dom-cod)) circuit >>= Id(cod) @ Bra(*[0]*(dom - cod)) return circuit
[docs]class IQPAnsatz(CircuitAnsatz): """Instantaneous Quantum Polynomial ansatz. An IQP ansatz interleaves layers of Hadamard gates with diagonal unitaries. This class uses :py:obj:`n_layers-1` adjacent CRz gates to implement each diagonal unitary. """
[docs] def __init__(self, ob_map: Mapping[Ty, int], n_layers: int, n_single_qubit_params: int = 3, discard: bool = False) -> None: """Instantiate an IQP ansatz. Parameters ---------- ob_map : dict A mapping from :py:class:`discopy.rigid.Ty` to the number of qubits it uses in a circuit. n_layers : int The number of layers used by the ansatz. n_single_qubit_params : int, default: 3 The number of single qubit rotations used by the ansatz. discard : bool, default: False Discard open wires instead of post-selecting. """ super().__init__(ob_map, n_layers, n_single_qubit_params, IQP, discard, [Rx, Rz], H)
[docs] def params_shape(self, n_qubits: int) -> tuple[int, ...]: return (self.n_layers, n_qubits - 1)
[docs]class Sim14Ansatz(CircuitAnsatz): """Modification of circuit 14 from Sim et al. Replaces circuit-block construction with two rings of CRx gates, in opposite orientation. Paper at: https://arxiv.org/pdf/1905.10876.pdf """
[docs] def __init__(self, ob_map: Mapping[Ty, int], n_layers: int, n_single_qubit_params: int = 3, discard: bool = False) -> None: """Instantiate a Sim 14 ansatz. Parameters ---------- ob_map : dict A mapping from :py:class:`discopy.rigid.Ty` to the number of qubits it uses in a circuit. n_layers : int The number of layers used by the ansatz. n_single_qubit_params : int, default: 3 The number of single qubit rotations used by the ansatz. discard : bool, default: False Discard open wires instead of post-selecting. """ super().__init__(ob_map, n_layers, n_single_qubit_params, Sim14, discard, [Rx, Rz])
[docs] def params_shape(self, n_qubits: int) -> tuple[int, ...]: return (self.n_layers, 4 * n_qubits)
[docs]class Sim15Ansatz(CircuitAnsatz): """Modification of circuit 15 from Sim et al. Replaces circuit-block construction with two rings of CNOT gates, in opposite orientation. Paper at: https://arxiv.org/pdf/1905.10876.pdf """
[docs] def __init__(self, ob_map: Mapping[Ty, int], n_layers: int, n_single_qubit_params: int = 3, discard: bool = False) -> None: """Instantiate a Sim 15 ansatz. Parameters ---------- ob_map : dict A mapping from :py:class:`discopy.rigid.Ty` to the number of qubits it uses in a circuit. n_layers : int The number of layers used by the ansatz. n_single_qubit_params : int, default: 3 The number of single qubit rotations used by the ansatz. discard : bool, default: False Discard open wires instead of post-selecting. """ super().__init__(ob_map, n_layers, n_single_qubit_params, Sim15, discard, [Rx, Rz])
[docs] def params_shape(self, n_qubits: int) -> tuple[int, ...]: return (self.n_layers, 2 * n_qubits)
[docs]class StronglyEntanglingAnsatz(CircuitAnsatz): """Strongly entangling ansatz. Ansatz using three single qubit rotations (RzRyRz) followed by a ladder of CNOT gates with different ranges per layer. This is adapted from the PennyLane implementation of the :py:class:`pennylane.StronglyEntanglingLayers`, pursuant to `Apache 2.0 licence <https://www.apache.org/licenses/LICENSE-2.0.html>`_. The original paper which introduces the architecture can be found `here <https://arxiv.org/abs/1804.00633>`_. """
[docs] def __init__(self, ob_map: Mapping[Ty, int], n_layers: int, n_single_qubit_params: int = 3, ranges: Optional[list[int]] = None, discard: bool = False) -> None: """Instantiate a strongly entangling ansatz. Parameters ---------- ob_map : dict A mapping from :py:class:`discopy.rigid.Ty` to the number of qubits it uses in a circuit. n_layers : int The number of circuit layers used by the ansatz. n_single_qubit_params : int, default: 3 The number of single qubit rotations used by the ansatz. ranges : list of int, optional The range of the CNOT gate between wires in each layer. By default, the range starts at one (i.e. adjacent wires) and increases by one for each subsequent layer. discard : bool, default: False Discard open wires instead of post-selecting. """ super().__init__(ob_map, n_layers, n_single_qubit_params, self.circuit, discard, [Rz, Ry]) self.ranges = ranges if self.ranges is not None and len(self.ranges) != self.n_layers: raise ValueError('The number of ranges must match the number of ' 'layers.')
[docs] def params_shape(self, n_qubits: int) -> tuple[int, ...]: return (self.n_layers, 3 * n_qubits)
[docs] def circuit(self, n_qubits: int, params: np.ndarray) -> Circuit: circuit = Id(qubit**n_qubits) for layer in range(self.n_layers): for j in range(n_qubits): syms = params[layer][j*3:j*3+3] circuit = circuit.Rz(syms[0], j).Ry(syms[1], j).Rz(syms[2], j) if self.ranges is None: step = layer % (n_qubits - 1) + 1 elif self.ranges[layer] >= n_qubits: raise ValueError('The maximum range must be smaller ' 'than the number of qubits.') else: step = self.ranges[layer] for j in range(n_qubits): circuit = circuit.CX(j, (j+step) % n_qubits) return circuit