Source code for pytket.utils.symbolic

# Copyright 2019-2024 Cambridge Quantum Computing
#
# 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
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"""Collection of methods to calculate symbolic statevectors and unitaries,
for symbolic circuits. This uses the sympy.physics.quantum module and produces
sympy objects. The implementations are slow and scale poorly, so this is
only suitable for very small (up to 5 qubit) circuits."""
from typing import Callable, Dict, List, Optional, Type, Union, cast

import numpy as np
import sympy
from sympy import (
    BlockDiagMatrix,
    BlockMatrix,
    Expr,
    Identity,
    ImmutableMatrix,
    Matrix,
    Mul,
    I,
    diag,
    eye,
    zeros,
)
from sympy.physics.quantum import gate as symgate
from sympy.physics.quantum import represent
from sympy.physics.quantum.tensorproduct import matrix_tensor_product
from sympy.physics.quantum.qapply import qapply
from sympy.physics.quantum.qubit import Qubit, matrix_to_qubit

from pytket.circuit import Circuit, Op, OpType

# gates that have an existing definition in sympy
_FIXED_GATE_MAP: Dict[OpType, Type[symgate.Gate]] = {
    OpType.H: symgate.HadamardGate,
    OpType.S: symgate.PhaseGate,
    OpType.CX: symgate.CNotGate,
    OpType.SWAP: symgate.SwapGate,
    OpType.T: symgate.TGate,
    OpType.X: symgate.XGate,
    OpType.Y: symgate.YGate,
    OpType.Z: symgate.ZGate,
}

ParamsType = List[Union[Expr, float]]
# Make sure the return matrix is Immutable https://github.com/sympy/sympy/issues/18733
SymGateFunc = Callable[[ParamsType], ImmutableMatrix]
SymGateMap = Dict[OpType, SymGateFunc]

# Begin matrix definitions for symbolic OpTypes
# matches internal TKET definitions
# see OpType documentation


def symb_controlled(target: SymGateFunc) -> SymGateFunc:
    return lambda x: ImmutableMatrix(BlockDiagMatrix(Identity(2), target(x)))


def symb_rz(params: ParamsType) -> ImmutableMatrix:
    return ImmutableMatrix(
        [
            [sympy.exp(-I * (sympy.pi / 2) * params[0]), 0],
            [0, sympy.exp(I * (sympy.pi / 2) * params[0])],
        ]
    )


def symb_rx(params: ParamsType) -> ImmutableMatrix:
    costerm = sympy.cos((sympy.pi / 2) * params[0])
    sinterm = -I * sympy.sin((sympy.pi / 2) * params[0])
    return ImmutableMatrix(
        [
            [costerm, sinterm],
            [sinterm, costerm],
        ]
    )


def symb_ry(params: ParamsType) -> ImmutableMatrix:
    costerm = sympy.cos((sympy.pi / 2) * params[0])
    sinterm = sympy.sin((sympy.pi / 2) * params[0])
    return ImmutableMatrix(
        [
            [costerm, -sinterm],
            [sinterm, costerm],
        ]
    )


def symb_u3(params: ParamsType) -> ImmutableMatrix:
    theta, phi, lam = params
    costerm = sympy.cos((sympy.pi / 2) * theta)
    sinterm = sympy.sin((sympy.pi / 2) * theta)
    return ImmutableMatrix(
        [
            [costerm, -sinterm * sympy.exp(I * sympy.pi * lam)],
            [
                sinterm * sympy.exp(I * sympy.pi * phi),
                costerm * sympy.exp(I * sympy.pi * (phi + lam)),
            ],
        ]
    )


def symb_u2(params: ParamsType) -> ImmutableMatrix:
    return symb_u3([0.5] + params)


def symb_u1(params: ParamsType) -> ImmutableMatrix:
    return symb_u3([0.0, 0.0] + params)


def symb_tk1(params: ParamsType) -> ImmutableMatrix:
    return symb_rz([params[0]]) * symb_rx([params[1]]) * symb_rz([params[2]])


def symb_tk2(params: ParamsType) -> ImmutableMatrix:
    return (
        symb_xxphase([params[0]])
        * symb_yyphase([params[1]])
        * symb_zzphase([params[2]])
    )


def symb_iswap(params: ParamsType) -> ImmutableMatrix:
    alpha = params[0]
    costerm = sympy.cos((sympy.pi / 2) * alpha)
    sinterm = sympy.sin((sympy.pi / 2) * alpha)
    return ImmutableMatrix(
        [
            [1, 0, 0, 0],
            [0, costerm, I * sinterm, 0],
            [0, I * sinterm, costerm, 0],
            [0, 0, 0, 1],
        ]
    )


def symb_phasediswap(params: ParamsType) -> ImmutableMatrix:
    p, alpha = params
    costerm = sympy.cos((sympy.pi / 2) * alpha)
    sinterm = I * sympy.sin((sympy.pi / 2) * alpha)
    phase = sympy.exp(2 * I * sympy.pi * p)
    return ImmutableMatrix(
        [
            [1, 0, 0, 0],
            [0, costerm, sinterm * phase, 0],
            [0, sinterm / phase, costerm, 0],
            [0, 0, 0, 1],
        ]
    )


def symb_xxphase(params: ParamsType) -> ImmutableMatrix:
    alpha = params[0]
    c = sympy.cos((sympy.pi / 2) * alpha)
    s = -I * sympy.sin((sympy.pi / 2) * alpha)
    return ImmutableMatrix(
        [
            [c, 0, 0, s],
            [0, c, s, 0],
            [0, s, c, 0],
            [s, 0, 0, c],
        ]
    )


def symb_yyphase(params: ParamsType) -> ImmutableMatrix:
    alpha = params[0]
    c = sympy.cos((sympy.pi / 2) * alpha)
    s = I * sympy.sin((sympy.pi / 2) * alpha)
    return ImmutableMatrix(
        [
            [c, 0, 0, s],
            [0, c, -s, 0],
            [0, -s, c, 0],
            [s, 0, 0, c],
        ]
    )


def symb_zzphase(params: ParamsType) -> ImmutableMatrix:
    alpha = params[0]
    t = sympy.exp(I * (sympy.pi / 2) * alpha)
    return ImmutableMatrix(diag(1 / t, t, t, 1 / t))


def symb_xxphase3(params: ParamsType) -> ImmutableMatrix:
    xxphase2 = symb_xxphase(params)
    res1 = matrix_tensor_product(xxphase2, eye(2))
    res2 = Matrix(
        BlockMatrix(
            [
                [xxphase2[:2, :2], zeros(2), xxphase2[:2, 2:], zeros(2)],
                [zeros(2), xxphase2[:2, :2], zeros(2), xxphase2[:2, 2:]],
                [xxphase2[2:, :2], zeros(2), xxphase2[2:, 2:], zeros(2)],
                [zeros(2), xxphase2[2:, :2], zeros(2), xxphase2[2:, 2:]],
            ]
        )
    )
    res3 = matrix_tensor_product(eye(2), xxphase2)
    res = ImmutableMatrix(res1 * res2 * res3)
    return res


def symb_phasedx(params: ParamsType) -> ImmutableMatrix:
    alpha, beta = params

    return symb_rz([beta]) * symb_rx([alpha]) * symb_rz([-beta])


def symb_eswap(params: ParamsType) -> ImmutableMatrix:
    alpha = params[0]
    c = sympy.cos((sympy.pi / 2) * alpha)
    s = -I * sympy.sin((sympy.pi / 2) * alpha)
    t = sympy.exp(-I * (sympy.pi / 2) * alpha)

    return ImmutableMatrix(
        [
            [t, 0, 0, 0],
            [0, c, s, 0],
            [0, s, c, 0],
            [0, 0, 0, t],
        ]
    )


def symb_fsim(params: ParamsType) -> ImmutableMatrix:
    alpha, beta = params
    c = sympy.cos(sympy.pi * alpha)
    s = -I * sympy.sin(sympy.pi * alpha)
    t = sympy.exp(-I * sympy.pi * beta)

    return ImmutableMatrix(
        [
            [1, 0, 0, 0],
            [0, c, s, 0],
            [0, s, c, 0],
            [0, 0, 0, t],
        ]
    )


def symb_gpi(params: ParamsType) -> ImmutableMatrix:
    t = sympy.exp(I * sympy.pi * params[0])

    return ImmutableMatrix(
        [
            [0, 1 / t],
            [t, 0],
        ]
    )


def symb_gpi2(params: ParamsType) -> ImmutableMatrix:
    t = sympy.exp(I * sympy.pi * params[0])
    c = 1 / sympy.sqrt(2)

    return c * ImmutableMatrix(
        [
            [1, -I / t],
            [-I * t, 1],
        ]
    )


def symb_aams(params: ParamsType) -> ImmutableMatrix:
    alpha, beta, gamma = params
    c = sympy.cos(sympy.pi / 2 * alpha)
    s = sympy.sin(sympy.pi / 2 * alpha)
    s1 = -I * sympy.exp(I * sympy.pi * (-beta - gamma)) * s
    s2 = -I * sympy.exp(I * sympy.pi * (-beta + gamma)) * s
    s3 = -I * sympy.exp(I * sympy.pi * (beta - gamma)) * s
    s4 = -I * sympy.exp(I * sympy.pi * (beta + gamma)) * s

    return ImmutableMatrix(
        [
            [c, 0, 0, s1],
            [0, c, s2, 0],
            [0, s3, c, 0],
            [s4, 0, 0, c],
        ]
    )


# end symbolic matrix definitions


[docs] class SymGateRegister: """Static class holding mapping from OpType to callable generating symbolic matrix. Allows users to add their own definitions, or override existing definitions.""" _g_map: SymGateMap = { OpType.Rx: symb_rx, OpType.Ry: symb_ry, OpType.Rz: symb_rz, OpType.TK1: symb_tk1, OpType.TK2: symb_tk2, OpType.U1: symb_u1, OpType.U2: symb_u2, OpType.U3: symb_u3, OpType.CRx: symb_controlled(symb_rx), OpType.CRy: symb_controlled(symb_ry), OpType.CRz: symb_controlled(symb_rz), OpType.CU1: symb_controlled(symb_u1), OpType.CU3: symb_controlled(symb_u3), OpType.ISWAP: symb_iswap, OpType.PhasedISWAP: symb_phasediswap, OpType.XXPhase: symb_xxphase, OpType.YYPhase: symb_yyphase, OpType.ZZPhase: symb_zzphase, OpType.XXPhase3: symb_xxphase3, OpType.PhasedX: symb_phasedx, OpType.ESWAP: symb_eswap, OpType.FSim: symb_fsim, OpType.GPI: symb_gpi, OpType.GPI2: symb_gpi2, OpType.AAMS: symb_aams, }
[docs] @classmethod def register_func(cls, typ: OpType, f: SymGateFunc, replace: bool = False) -> None: """Register a callable for an optype. :param typ: OpType to register :type typ: OpType :param f: Callable for generating symbolic matrix. :type f: SymGateFunc :param replace: Whether to replace existing entry, defaults to False :type replace: bool, optional """ if typ not in cls._g_map or replace: cls._g_map[typ] = f
[docs] @classmethod def get_func(cls, typ: OpType) -> SymGateFunc: """Get registered callable.""" return cls._g_map[typ]
[docs] @classmethod def is_registered(cls, typ: OpType) -> bool: """Check if type has a callable registered.""" return typ in cls._g_map
def _op_to_sympy_gate(op: Op, targets: List[int]) -> symgate.Gate: # convert Op to sympy gate if op.type in _FIXED_GATE_MAP: return _FIXED_GATE_MAP[op.type](*targets) if op.is_gate(): # check if symbolic definition is needed float_params = all(isinstance(p, float) for p in op.params) else: raise ValueError( f"Circuit can only contain unitary gates, operation {op} not valid." ) # pytket matrix basis indexing is in opposite order to sympy targets = targets[::-1] if (not float_params) and SymGateRegister.is_registered(op.type): u_mat = SymGateRegister.get_func(op.type)(op.params) else: try: # use internal tket unitary definition u_mat = ImmutableMatrix(op.get_unitary()) except RuntimeError as e: # to catch tket failure to get Op unitary # most likely due to symbolic parameters. raise ValueError( f"{op.type} is not supported for symbolic conversion." " Try registering your own symbolic matrix representation" " with SymGateRegister.func." ) from e gate = symgate.UGate(targets, u_mat) return gate
[docs] def circuit_to_symbolic_gates(circ: Circuit) -> Mul: """Generate a multiplication expression of sympy gates from Circuit :param circ: Input circuit :type circ: Circuit :raises ValueError: If circ does not match a unitary operation. :return: Symbolic gate multiplication expression. :rtype: Mul """ outmat = symgate.IdentityGate(0) nqb = circ.n_qubits qubit_map = {qb: nqb - 1 - i for i, qb in enumerate(circ.qubits)} for com in circ: op = com.op if op.type == OpType.Barrier: continue args = com.args try: targs = [qubit_map[q] for q in args] # type: ignore except KeyError as e: raise ValueError( f"Gates can only act on qubits. Operation {com} not valid." ) from e gate = _op_to_sympy_gate(op, targs) outmat = gate * outmat for i in range(len(qubit_map)): outmat = symgate.IdentityGate(i) * outmat return outmat * sympy.exp((circ.phase * sympy.pi * I))
[docs] def circuit_to_symbolic_unitary(circ: Circuit) -> ImmutableMatrix: """Generate a symbolic unitary from Circuit. Unitary matches pytket default ILO BasisOrder. :param circ: Input circuit :type circ: Circuit :return: Symbolic unitary. :rtype: ImmutableMatrix """ gates = circuit_to_symbolic_gates(circ) nqb = circ.n_qubits try: return cast(ImmutableMatrix, represent(gates, nqubits=circ.n_qubits)) except NotImplementedError: # sympy can't represent n>1 qubit unitaries very well # so if it fails we will just calculate columns using the statevectors # for all possible input basis states matrix_dim = 1 << nqb input_states = (Qubit(f"{i:0{nqb}b}") for i in range(matrix_dim)) outmat = Matrix([]) for col, input_state in enumerate(input_states): outmat = outmat.col_insert(col, represent(qapply(gates * input_state))) return ImmutableMatrix(outmat)
[docs] def circuit_apply_symbolic_qubit(circ: Circuit, input_qb: Expr) -> Qubit: """Apply circuit to an input state to calculate output symbolic state. :param circ: Input Circuit. :type circ: Circuit :param input_qb: Sympy Qubit expression corresponding to a state. :type input_qb: Expr :return: Output state after circuit acts on input_qb. :rtype: Qubit """ gates = circuit_to_symbolic_gates(circ) return cast(Qubit, qapply(gates * input_qb))
[docs] def circuit_apply_symbolic_statevector( circ: Circuit, input_state: Optional[Union[np.ndarray, ImmutableMatrix]] = None ) -> ImmutableMatrix: """Apply circuit to an optional input statevector to calculate output symbolic statevector. If no input statevector given, the all zero state is assumed. Statevector follows pytket default ILO BasisOrder. :param circ: Input Circuit. :type circ: Circuit :param input_state: Input statevector as a column vector, defaults to None. :type input_state: Optional[Union[np.ndarray, ImmutableMatrix]], optional :return: Symbolic state after circ acts on input_state. :rtype: ImmutableMatrix """ if input_state: input_qb = matrix_to_qubit(input_state) else: input_qb = Qubit("0" * circ.n_qubits) return cast( ImmutableMatrix, represent(circuit_apply_symbolic_qubit(circ, cast(Qubit, input_qb))), )