# Copyright 2021-2024 Cambridge Quantum Computing Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Ansatz
======
An ansatz is used to convert a DisCoCat diagram into a quantum circuit.
"""
from __future__ import annotations
__all__ = ['BaseAnsatz', 'Symbol']
from abc import ABC, abstractmethod
from collections.abc import Mapping
from typing import Any, Literal
import sympy
from lambeq.backend import grammar, tensor
[docs]class Symbol(sympy.Symbol):
"""A sympy symbol augmented with extra information.
Attributes
----------
directed_dom : int
The size of the domain of the tensor-box that this symbol
represents.
directed_cod : int
The size of the codomain of the tensor-box that this symbol
represents.
size : int
The total size of the tensor that this symbol represents
(directed_dom * directed_cod).
"""
directed_dom: int
directed_cod: int
def __new__(cls,
name: str,
directed_dom: int = 1,
directed_cod: int = 1,
**assumptions: bool) -> Symbol:
"""Initialise a symbol.
Parameters
----------
directed_dom : int, default: 1
The size of the domain of the tensor-box that this symbol
represents.
directed_cod : int, default: 1
The size of the codomain of the tensor-box that this symbol
represents.
"""
cls._sanitize(assumptions, cls)
obj: Symbol = sympy.Symbol.__xnew__(cls, name, **assumptions)
obj.directed_dom = directed_dom
obj.directed_cod = directed_cod
return obj
def __getnewargs_ex__(self) -> tuple[tuple[str, int], dict[str, bool]]:
return (self.name, self.size), self.assumptions0
@property
def size(self) -> int:
return self.directed_dom * self.directed_cod
[docs] @sympy.cacheit
def sort_key(self, order: Literal[None] = None) -> tuple[Any, ...]:
return (self.class_key(),
(2, (self.name, self.size)),
sympy.S.One.sort_key(),
sympy.S.One)
def _hashable_content(self) -> tuple[Any, ...]:
return (*super()._hashable_content(), self.size)
[docs]class BaseAnsatz(ABC):
"""Base class for ansatz."""
[docs] @abstractmethod
def __init__(self, ob_map: Mapping[grammar.Ty, tensor.Dim]) -> None:
"""Instantiate an ansatz.
Parameters
----------
ob_map : dict
A mapping from `lambeq.backend.grammar.Ty` to a type in
the target category. In the category of quantum circuits,
this type is the number of qubits; in the category of
vector spaces, this type is a vector space.
"""
[docs] @abstractmethod
def __call__(self, diagram: grammar.Diagram) -> tensor.Diagram:
"""Convert a diagram into a circuit or tensor."""
@staticmethod
def _summarise_box(box: grammar.Box) -> str:
"""Summarise the given box."""
dom = str(box.dom).replace(' @ ', '@') if box.dom else ''
cod = str(box.cod).replace(' @ ', '@') if box.cod else ''
raw_summary = f'{box.name}_{dom}_{cod}'
# Escape special characters for sympy
return raw_summary.translate({ord(c): f'\\{c}' for c in ':, '})