Source code for mrmustard.lab.circuit_components_utils.b_to_ch

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"""The class representing an operation that changes Bargmann into phase space."""

from __future__ import annotations

from collections.abc import Sequence

from mrmustard.parameters import Parameter
from mrmustard.physics.ansatz_factory import AnsatzFactory
from mrmustard.physics.wires import ReprEnum, Wires
from mrmustard.utils.typing import ComplexTensor

from ..transformations.base import Map
from .builtins import displacement_map_s_parametrized

__all__ = ["BtoChar"]


[docs] class BtoChar(Map): r"""The ``s``-parametrized ``Dgate`` as a ``Map``. Also known as the Fourier transform of the Stratonovich-Weyl kernel. See https://arxiv.org/abs/quant-ph/9707010. This is an unphysical component whose purpose is to modify the internal representation of another component. In particular it transforms between the Bargmann representation and the s-parametrized Characteristic functions. Note that it can be applied to a subset of modes. >>> from mrmustard.lab import BtoChar, GaussianKet >>> from mrmustard import math >>> chi = (GaussianKet.random([0]) >> BtoChar([0], s=0)).ansatz >>> assert math.allclose(chi(0,0), 1.0) Args: modes: The modes of this channel. s: The ``s`` parameter of this channel. .. details:: This class represents the transformation from the Bargmann (B) representation to characteristic function (Char). Any operator, say O can be expressed in the displacement basis. Formally, we have that the s-parametrized phase space basis is characterized by the following operators .. math:: D_s(\alpha) = exp(s|\alpha|^2/2) D(\alpha). The s-parametrized phase space representation of an object O, would therefore be .. math:: \mathrm{Tr}(D_s(\alpha) O). Important s-parametrizations include: - s=1: returns the complex Fourier transform (or often called the symplectic Fourier transform) of Galuber-Sudarshan P function. - s=0: returns the characteristic function, which is equivalent to the complex Fourier transform of the Wigner function. - s=-1: returns the complex Fourier transform of the Q function. """ short_name = "BtoCh" def __init__( self, modes: int | tuple[int, ...], s: float, ): modes = (modes,) if isinstance(modes, int) else modes super().__init__( ansatz_factory=AnsatzFactory( ansatz_dict={ ReprEnum.BARGMANN: ( displacement_map_s_parametrized, ("s", "n_modes", "lin_sup"), ) }, n_modes=len(modes), ), wires=Wires( modes_in_bra=set(modes), modes_out_bra=set(modes), modes_in_ket=set(modes), modes_out_ket=set(modes), ), name=self.__class__.__name__, ) self.parameters["s"] = Parameter.from_cc_init(s, "float64", f"{self.name}/s") for w in self.wires.output.standard_order: w.repr = ReprEnum.CHARACTERISTIC
[docs] def inverse(self): ret = BtoChar(self.modes, self.parameters.s) ret_inverse = super().inverse() ret._ansatz_factory = ret_inverse.ansatz_factory ret._wires = ret.wires.dual ret._wires._reindex() return ret
[docs] def fock_array(self, shape: int | Sequence[int] | None = None) -> ComplexTensor: raise NotImplementedError(f"{self.__class__.__name__} does not have a Fock representation.")