qml.templates.subroutines.AllSinglesDoubles

class AllSinglesDoubles(weights, wires, hf_state, singles=None, doubles=None, do_queue=True, id=None)[source]

Bases: pennylane.operation.Operation

Builds a quantum circuit to prepare correlated states of molecules by applying all SingleExcitation and DoubleExcitation operations to the initial Hartree-Fock state.

The template initializes the \(n\)-qubit system to encode the input Hartree-Fock state and applies the particle-conserving SingleExcitation and DoubleExcitation operations which are implemented as Givens rotations that act on the subspace of two and four qubits, respectively. The total number of excitation gates and the indices of the qubits they act on are obtained using the excitations() function.

For example, the quantum circuit for the case of two electrons and six qubits is sketched in the figure below:


../../_images/all_singles_doubles.png

In this case, we have four single and double excitations that preserve the total-spin projection of the Hartree-Fock state. The SingleExcitation gate \(G\) act on the qubits [0, 2], [0, 4], [1, 3], [1, 5] as indicated by the squares, while the DoubleExcitation operation \(G^{(2)}\) is applied to the qubits [0, 1, 2, 3], [0, 1, 2, 5], [0, 1, 2, 4], [0, 1, 4, 5].

The resulting unitary conserves the number of particles and prepares the \(n\)-qubit system in a superposition of the initial Hartree-Fock state and other states encoding multiply-excited configurations.

Parameters
  • weights (tensor_like) – size (len(singles) + len(doubles),) tensor containing the angles entering the SingleExcitation and DoubleExcitation operations, in that order

  • wires (Iterable) – wires that the template acts on

  • hf_state (array[int]) – Length len(wires) occupation-number vector representing the Hartree-Fock state. hf_state is used to initialize the wires.

  • singles (Sequence[Sequence]) – sequence of lists with the indices of the two qubits the SingleExcitation operations act on

  • doubles (Sequence[Sequence]) – sequence of lists with the indices of the four qubits the DoubleExcitation operations act on

Notice that:

  1. The number of wires has to be equal to the number of spin orbitals included in the active space.

  2. The single and double excitations can be generated with the function excitations(). See example below.

An example of how to use this template is shown below:

import pennylane as qml
import numpy as np

electrons = 2
qubits = 4

# Define the HF state
hf_state = qml.qchem.hf_state(electrons, qubits)

# Generate all single and double excitations
singles, doubles = qml.qchem.excitations(electrons, qubits)

# Define the device
dev = qml.device('default.qubit', wires=qubits)

wires = range(qubits)

@qml.qnode(dev)
def circuit(weights, hf_state, singles, doubles):
    qml.templates.AllSinglesDoubles(weights, wires, hf_state, singles, doubles)
    return qml.expval(qml.PauliZ(0))

# Evaluate the QNode for a given set of parameters
params = np.random.normal(0, np.pi, len(singles) + len(doubles))
circuit(params, hf_state, singles=singles, doubles=doubles)

base_name

Get base name of the operator.

basis

The basis of an operation, or for controlled gates, of the target operation.

control_wires

For operations that are controlled, returns the set of control wires.

eigvals

Eigenvalues of an instantiated operator.

generator

Generator of the operation.

grad_method

Gradient computation method.

grad_recipe

Gradient recipe for the parameter-shift method.

hash

returns an integer hash uniquely representing the operator

id

String for the ID of the operator.

inverse

Boolean determining if the inverse of the operation was requested.

is_composable_rotation

True if composing multiple copies of the operation results in an addition (or alternative accumulation) of parameters.

is_self_inverse

True if the operation is its own inverse.

is_symmetric_over_all_wires

True if the operation is the same if you exchange the order of wires.

is_symmetric_over_control_wires

True if the operation is the same if you exchange the order of all but the last wire.

matrix

Matrix representation of an instantiated operator in the computational basis.

name

Get and set the name of the operator.

num_params

num_wires

par_domain

parameters

Current parameter values.

single_qubit_rot_angles

The parameters required to implement a single-qubit gate as an equivalent Rot gate, up to a global phase.

string_for_inverse

wires

Wires of this operator.

base_name

Get base name of the operator.

basis = None

The basis of an operation, or for controlled gates, of the target operation. If not None, should take a value of "X", "Y", or "Z".

For example, X and CNOT have basis = "X", whereas ControlledPhaseShift and RZ have basis = "Z".

Type

str or None

control_wires

For operations that are controlled, returns the set of control wires.

Returns

The set of control wires of the operation.

Return type

Wires

eigvals
generator

Generator of the operation.

A length-2 list [generator, scaling_factor], where

  • generator is an existing PennyLane operation class or \(2\times 2\) Hermitian array that acts as the generator of the current operation

  • scaling_factor represents a scaling factor applied to the generator operation

For example, if \(U(\theta)=e^{i0.7\theta \sigma_x}\), then \(\sigma_x\), with scaling factor \(s\), is the generator of operator \(U(\theta)\):

generator = [PauliX, 0.7]

Default is [None, 1], indicating the operation has no generator.

grad_method

Gradient computation method.

  • 'A': analytic differentiation using the parameter-shift method.

  • 'F': finite difference numerical differentiation.

  • None: the operation may not be differentiated.

Default is 'F', or None if the Operation has zero parameters.

grad_recipe = None

Gradient recipe for the parameter-shift method.

This is a tuple with one nested list per operation parameter. For parameter \(\phi_k\), the nested list contains elements of the form \([c_i, a_i, s_i]\) where \(i\) is the index of the term, resulting in a gradient recipe of

\[\frac{\partial}{\partial\phi_k}f = \sum_{i} c_i f(a_i \phi_k + s_i).\]

If None, the default gradient recipe containing the two terms \([c_0, a_0, s_0]=[1/2, 1, \pi/2]\) and \([c_1, a_1, s_1]=[-1/2, 1, -\pi/2]\) is assumed for every parameter.

Type

tuple(Union(list[list[float]], None)) or None

hash

returns an integer hash uniquely representing the operator

Type

int

id

String for the ID of the operator.

inverse

Boolean determining if the inverse of the operation was requested.

is_composable_rotation = None

True if composing multiple copies of the operation results in an addition (or alternative accumulation) of parameters.

For example, qml.RZ is a composable rotation. Applying qml.RZ(0.1, wires=0) followed by qml.RZ(0.2, wires=0) is equivalent to performing a single rotation qml.RZ(0.3, wires=0).

If set to None, the operation will be ignored during compilation transforms that merge adjacent rotations.

Type

bool or None

is_self_inverse = None

True if the operation is its own inverse.

If None, all instances of the given operation will be ignored during compilation transforms involving inverse cancellation.

Type

bool or None

is_symmetric_over_all_wires = None

True if the operation is the same if you exchange the order of wires.

For example, qml.CZ(wires=[0, 1]) has the same effect as qml.CZ(wires=[1, 0]) due to symmetry of the operation.

If None, all instances of the operation will be ignored during compilation transforms that check for wire symmetry.

Type

bool or None

is_symmetric_over_control_wires = None

True if the operation is the same if you exchange the order of all but the last wire.

For example, qml.Toffoli(wires=[0, 1, 2]) has the same effect as qml.Toffoli(wires=[1, 0, 2]), but neither are the same as qml.Toffoli(wires=[0, 2, 1]).

If None, all instances of the operation will be ignored during compilation transforms that check for control-wire symmetry.

Type

bool or None

matrix
name

Get and set the name of the operator.

num_params = 1
num_wires = -1
par_domain = 'A'
parameters

Current parameter values.

single_qubit_rot_angles

The parameters required to implement a single-qubit gate as an equivalent Rot gate, up to a global phase.

Returns

A list of values \([\phi, \theta, \omega]\) such that \(RZ(\omega) RY(\theta) RZ(\phi)\) is equivalent to the original operation.

Return type

tuple[float, float, float]

string_for_inverse = '.inv'
wires

Wires of this operator.

Returns

wires

Return type

Wires

adjoint([do_queue])

Create an operation that is the adjoint of this one.

decomposition(*params, wires)

Returns a template decomposing the operation into other quantum operations.

expand()

Returns a tape containing the decomposed operations, rather than a list.

get_parameter_shift(idx[, shift])

Multiplier and shift for the given parameter, based on its gradient recipe.

inv()

Inverts the operation, such that the inverse will be used for the computations by the specific device.

queue([context])

Append the operator to the Operator queue.

shape(singles, doubles)

Returns the expected shape of the tensor that contains the circuit parameters.

adjoint(do_queue=False)

Create an operation that is the adjoint of this one.

Adjointed operations are the conjugated and transposed version of the original operation. Adjointed ops are equivalent to the inverted operation for unitary gates.

Parameters

do_queue – Whether to add the adjointed gate to the context queue.

Returns

The adjointed operation.

static decomposition(*params, wires)

Returns a template decomposing the operation into other quantum operations.

expand()[source]

Returns a tape containing the decomposed operations, rather than a list.

Returns

Returns a quantum tape that contains the operations decomposition, or if not implemented, simply the operation itself.

Return type

JacobianTape

get_parameter_shift(idx, shift=1.5707963267948966)

Multiplier and shift for the given parameter, based on its gradient recipe.

Parameters

idx (int) – parameter index

Returns

list of multiplier, coefficient, shift for each term in the gradient recipe

Return type

list[[float, float, float]]

inv()

Inverts the operation, such that the inverse will be used for the computations by the specific device.

This method concatenates a string to the name of the operation, to indicate that the inverse will be used for computations.

Any subsequent call of this method will toggle between the original operation and the inverse of the operation.

Returns

operation to be inverted

Return type

Operator

queue(context=<class 'pennylane.queuing.QueuingContext'>)

Append the operator to the Operator queue.

static shape(singles, doubles)[source]

Returns the expected shape of the tensor that contains the circuit parameters.

Parameters
  • singles (Sequence[Sequence]) – sequence of lists with the indices of the two qubits the SingleExcitation operations act on

  • doubles (Sequence[Sequence]) – sequence of lists with the indices of the four qubits the DoubleExcitation operations act on

Returns

shape of the tensor containing the circuit parameters

Return type

tuple(int)