pyqpanda3.vqcircuit.vqcircuit.VQCircuit Class Reference

Public Member Functions
None	__init__ (self, bool pre_split=...)
	init(self: vqcircuit.VQCircuit, pre_split: bool = True) -> None
	Param (self, *args, **kwargs)
	Param(*args, **kwargs) Overloaded function.
VQCircuit	append (self, VQCircuit sub_vqc, placeholder_map)
	append(self: vqcircuit.VQCircuit, sub_vqc: vqcircuit.VQCircuit, placeholder_map: list[tuple[QPanda3::VQCParamSystem::ParamExpression, QPanda3::VQCParamSystem::ParamExpression]]) -> vqcircuit.VQCircuit
str	display_ansatz (self)
	display_ansatz(self: vqcircuit.VQCircuit) -> str
list[int]	get_Param_dims (self)
	get_Param_dims(self: vqcircuit.VQCircuit) -> list[int]
ResGradients	get_gradients (self, numpy.ndarray[numpy.float64] params, observable, DiffMethod diff_method)
	get_gradients(*args, **kwargs) Overloaded function.
ResNGradients	get_gradients (self, numpy.ndarray[numpy.float64] params, observable, int param_group_total, DiffMethod diff_method)
	get_gradients(*args, **kwargs) Overloaded function.
ResGradientsAndExpectation	get_gradients_and_expectation (self, numpy.ndarray[numpy.float64] params, observable, DiffMethod diff_method)
	get_gradients_and_expectation(*args, **kwargs) Overloaded function.
ResNResGradientsAndExpectation	get_gradients_and_expectation (self, numpy.ndarray[numpy.float64] params, observable, int param_group_total, DiffMethod diff_method)
	get_gradients_and_expectation(*args, **kwargs) Overloaded function.
int	mutable_parameter_total (self)
	mutable_parameter_total(self: vqcircuit.VQCircuit) -> int
None	set_Param (self, list[int] dim_size_s, list[str] dim_label_s)
	set_Param(*args, **kwargs) Overloaded function.
None	set_Param (self, list[int] dim_size_s)
	set_Param(*args, **kwargs) Overloaded function.
	__call__ (self, *args, **kwargs)
	call(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64]) -> QPanda3::VQCircuitResultOld
VQCircuit	__lshift__ (self, qgate)
	lshift(*args, **kwargs) Overloaded function.
VQCircuit	__lshift__ (self, qcircuit)
	lshift(*args, **kwargs) Overloaded function.
VQCircuit	__lshift__ (self, vqgate)
	lshift(*args, **kwargs) Overloaded function.

Constructor & Destructor Documentation

__init__()

None pyqpanda3.vqcircuit.vqcircuit.VQCircuit.__init__	(		self,
		bool	pre_split = ... )

init(self: vqcircuit.VQCircuit, pre_split: bool = True) -> None

Constructs a new instance of the VariationalQuantumCircuit class.

This constructor initializes a new empty instance of the VariationalQuantumCircuit class, ready for further configuration and use.

Member Function Documentation

__call__()

pyqpanda3.vqcircuit.vqcircuit.VQCircuit.__call__	(		self,
		*	args,
		**	kwargs )

call(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64]) -> QPanda3::VQCircuitResultOld

Applies parameter values to the variational quantum circuit and evaluates it.

This method applies the provided parameter values (data) to the variational quantum circuit, considering the specified dimension sizes (dim_size_s). operator (<<). The variational quantum gate to be inserted is specified as the parameter vqgate.It then evaluates the circuit and returns the result as a VQCircuitResult object.

Parameters

params

a numpy.ndarray object with all params to generate QCircuit objects

__lshift__() [1/3]

VQCircuit pyqpanda3.vqcircuit.vqcircuit.VQCircuit.__lshift__	(		self,
			qcircuit )

lshift(*args, **kwargs) Overloaded function.

1. lshift(self: vqcircuit.VQCircuit, qgate: QPanda3::QGate) -> vqcircuit.VQCircuit

Inserts a quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of quantum gates into the variational quantum circuit using the stream insertion operator (<<). The quantum

Parameters

qgate

the quantum gate will be inserted to the variational quantum circuit,the qgate is with fixed params or without pparams gate to be inserted is specified as the parameter qgate.

1. lshift(self: vqcircuit.VQCircuit, qcircuit: QPanda3::QCircuit) -> vqcircuit.VQCircuit

Inserts a quantum circuit into the variational quantum circuit.

This operator overload allows for the insertion of a complete quantum circuit into the variational quantum circuit using the stream insertion operator (<<). The quantum circuit to be inserted is specified as the parameter qcircuit

Parameters

qcircuit

the quantum qcircuit will be inserted to the variational quantum circuit,its gates are with fixed params or without params gate to be inserted.

1. lshift(self: vqcircuit.VQCircuit, vqgate: QPanda3::VariationalQuantumGate) -> vqcircuit.VQCircuit

Inserts a variational quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of a variational quantum gate into the variational quantum circuit using the stream insertion operator (<<). The variational quantum gate to be inserted is specified as the parameter vqgate.

Parameters

vqgate

a variational quantum gate object

__lshift__() [2/3]

VQCircuit pyqpanda3.vqcircuit.vqcircuit.VQCircuit.__lshift__	(		self,
			qgate )

lshift(*args, **kwargs) Overloaded function.

1. lshift(self: vqcircuit.VQCircuit, qgate: QPanda3::QGate) -> vqcircuit.VQCircuit

Inserts a quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of quantum gates into the variational quantum circuit using the stream insertion operator (<<). The quantum

Parameters

qgate

the quantum gate will be inserted to the variational quantum circuit,the qgate is with fixed params or without pparams gate to be inserted is specified as the parameter qgate.

1. lshift(self: vqcircuit.VQCircuit, qcircuit: QPanda3::QCircuit) -> vqcircuit.VQCircuit

Inserts a quantum circuit into the variational quantum circuit.

This operator overload allows for the insertion of a complete quantum circuit into the variational quantum circuit using the stream insertion operator (<<). The quantum circuit to be inserted is specified as the parameter qcircuit

Parameters

qcircuit

the quantum qcircuit will be inserted to the variational quantum circuit,its gates are with fixed params or without params gate to be inserted.

1. lshift(self: vqcircuit.VQCircuit, vqgate: QPanda3::VariationalQuantumGate) -> vqcircuit.VQCircuit

Inserts a variational quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of a variational quantum gate into the variational quantum circuit using the stream insertion operator (<<). The variational quantum gate to be inserted is specified as the parameter vqgate.

Parameters

vqgate

a variational quantum gate object

__lshift__() [3/3]

VQCircuit pyqpanda3.vqcircuit.vqcircuit.VQCircuit.__lshift__	(		self,
			vqgate )

lshift(*args, **kwargs) Overloaded function.

1. lshift(self: vqcircuit.VQCircuit, qgate: QPanda3::QGate) -> vqcircuit.VQCircuit

Inserts a quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of quantum gates into the variational quantum circuit using the stream insertion operator (<<). The quantum

Parameters

qgate

the quantum gate will be inserted to the variational quantum circuit,the qgate is with fixed params or without pparams gate to be inserted is specified as the parameter qgate.

1. lshift(self: vqcircuit.VQCircuit, qcircuit: QPanda3::QCircuit) -> vqcircuit.VQCircuit

Inserts a quantum circuit into the variational quantum circuit.

This operator overload allows for the insertion of a complete quantum circuit into the variational quantum circuit using the stream insertion operator (<<). The quantum circuit to be inserted is specified as the parameter qcircuit

Parameters

qcircuit

the quantum qcircuit will be inserted to the variational quantum circuit,its gates are with fixed params or without params gate to be inserted.

1. lshift(self: vqcircuit.VQCircuit, vqgate: QPanda3::VariationalQuantumGate) -> vqcircuit.VQCircuit

Inserts a variational quantum gate into the variational quantum circuit.

This operator overload allows for the insertion of a variational quantum gate into the variational quantum circuit using the stream insertion operator (<<). The variational quantum gate to be inserted is specified as the parameter vqgate.

Parameters

vqgate

a variational quantum gate object

append()

VQCircuit pyqpanda3.vqcircuit.vqcircuit.VQCircuit.append	(		self,
		VQCircuit	sub_vqc,
			placeholder_map )

append(self: vqcircuit.VQCircuit, sub_vqc: vqcircuit.VQCircuit, placeholder_map: list[tuple[QPanda3::VQCParamSystem::ParamExpression, QPanda3::VQCParamSystem::ParamExpression]]) -> vqcircuit.VQCircuit

Appends a sub-VQCircuit to the current VQCircuit with a placeholder map.

This method appends the given sub_vqc to the current VQCircuit instance. The placeholder_map is used to map parameters in the sub_vqc to the parameters in the current VQCircuit.

Add all quantum gates in a VQCircuit object subvqc to a VQCircuit object self. The addition process only re-maps and sets the placeholder. If the variable parameter of a quantum gate is in the form of an expression, during the addition process, it still retains its expression form, but the placeholder that constitutes the expression changes from a placeholder of subvqc to a placeholder of self. When self updates the value of the placeholder, subvqc is not affected.

Parameters

self	The current VQCircuit instance.
sub_vqc	The sub-VQCircuit to be appended.
placeholder_map	A list of tuples where each tuple contains two ParamExpression objects. The first element is the parameter from the sub_vqc, and the second element is the corresponding parameter in the current VQCircuit.

Returns

The current VQCircuit instance with the sub_vqc appended.

display_ansatz()

str pyqpanda3.vqcircuit.vqcircuit.VQCircuit.display_ansatz

(

self

)

display_ansatz(self: vqcircuit.VQCircuit) -> str

Displays the structure of the ansatz (variational quantum circuit).

This method prints or otherwise displays the structure and components of the variational quantum circuit (ansatz) to the user.

get_gradients() [1/2]

ResGradients pyqpanda3.vqcircuit.vqcircuit.VQCircuit.get_gradients	(		self,
		numpy.ndarray[numpy.float64]	params,
			observable,
		DiffMethod	diff_method )

get_gradients(*args, **kwargs) Overloaded function.

1. get_gradients(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResGradients

Retrieve the gradients of the expectation value with respect to the parameters.

This function computes the gradients of the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value gradients are computed.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResGradients object containing the computed gradients.

1. get_gradients(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, param_group_total: int, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResNGradients

Retrieve the gradients of the expectation value with respect to the parameters.

This function computes the gradients of the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value gradients are computed.
param_group_total	The total number of parameter groups.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResNGradients object containing the computed gradients.

get_gradients() [2/2]

ResNGradients pyqpanda3.vqcircuit.vqcircuit.VQCircuit.get_gradients	(		self,
		numpy.ndarray[numpy.float64]	params,
			observable,
		int	param_group_total,
		DiffMethod	diff_method )

get_gradients(*args, **kwargs) Overloaded function.

1. get_gradients(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResGradients

Retrieve the gradients of the expectation value with respect to the parameters.

This function computes the gradients of the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value gradients are computed.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResGradients object containing the computed gradients.

1. get_gradients(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, param_group_total: int, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResNGradients

Retrieve the gradients of the expectation value with respect to the parameters.

This function computes the gradients of the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value gradients are computed.
param_group_total	The total number of parameter groups.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResNGradients object containing the computed gradients.

get_gradients_and_expectation() [1/2]

ResGradientsAndExpectation pyqpanda3.vqcircuit.vqcircuit.VQCircuit.get_gradients_and_expectation	(		self,
		numpy.ndarray[numpy.float64]	params,
			observable,
		DiffMethod	diff_method )

get_gradients_and_expectation(*args, **kwargs) Overloaded function.

1. get_gradients_and_expectation(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResGradientsAndExpectation

Retrieve the gradients of the expectation value and the expectation value itself with respect to the parameters.

this function computes both the gradients of the expectation value and the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value and its gradients are computed.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResGradientsAndExpectation object containing the computed gradients and expectation value.

1. get_gradients_and_expectation(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, param_group_total: int, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResNResGradientsAndExpectation

Retrieve the gradients of the expectation value and the expectation value itself with respect to the parameters.

This function computes both the gradients of the expectation value and the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value and its gradients are computed.
param_group_total	The total number of parameter groups.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResNResGradientsAndExpectation object containing the computed gradients and expectation value.

get_gradients_and_expectation() [2/2]

ResNResGradientsAndExpectation pyqpanda3.vqcircuit.vqcircuit.VQCircuit.get_gradients_and_expectation	(		self,
		numpy.ndarray[numpy.float64]	params,
			observable,
		int	param_group_total,
		DiffMethod	diff_method )

get_gradients_and_expectation(*args, **kwargs) Overloaded function.

1. get_gradients_and_expectation(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResGradientsAndExpectation

Retrieve the gradients of the expectation value and the expectation value itself with respect to the parameters.

this function computes both the gradients of the expectation value and the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value and its gradients are computed.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResGradientsAndExpectation object containing the computed gradients and expectation value.

1. get_gradients_and_expectation(self: vqcircuit.VQCircuit, params: numpy.ndarray[numpy.float64], observable: QPanda3::Hamiltonian, param_group_total: int, diff_method: vqcircuit.DiffMethod) -> vqcircuit.ResNResGradientsAndExpectation

Retrieve the gradients of the expectation value and the expectation value itself with respect to the parameters.

This function computes both the gradients of the expectation value and the expectation value of a given Hamiltonian with respect to the specified parameters using the specified differentiation method.

Parameters

params	An array of parameter values.
observable	The Hamiltonian for which the expectation value and its gradients are computed.
param_group_total	The total number of parameter groups.
diff_method	The differentiation method to use for computing gradients.

Returns

A ResNResGradientsAndExpectation object containing the computed gradients and expectation value.

get_Param_dims()

list[int] pyqpanda3.vqcircuit.vqcircuit.VQCircuit.get_Param_dims

(

self

)

get_Param_dims(self: vqcircuit.VQCircuit) -> list[int]

Retrieves the dimension information of the Param object.

Returns

returns a vector of size_t values representing the dimension sizes associated with the Param object.

mutable_parameter_total()

int pyqpanda3.vqcircuit.vqcircuit.VQCircuit.mutable_parameter_total

(

self

)

mutable_parameter_total(self: vqcircuit.VQCircuit) -> int

Get the total number of mutable parameters.

This function returns the total number of parameters used.

Returns

The total number of mutable parameters.

Param()

pyqpanda3.vqcircuit.vqcircuit.VQCircuit.Param	(		self,
		*	args,
		**	kwargs )

Param(*args, **kwargs) Overloaded function.

1. Param(self: vqcircuit.VQCircuit, idxs: list[int], emement_label: str) -> QPanda3::VQCParamSystem::ParamExpression

Retrieves the multi-dimensional array indices and associates a label with the corresponding parameter.

This method takes a vector of indices (idxs) specifying a position in a multi-dimensional array, along with a label string (element_label) to identify the parameter at that position.It returns the provided indices and internally associates the label with the corresponding parameter.

Parameters

idxs	a vector of indices specifying a position in a multi-dimensional array
emement_label	a label string to identify the parameter

Returns

th position in the multi-dimensional array

1. Param(self: vqcircuit.VQCircuit, idxs: list[int]) -> QPanda3::VQCParamSystem::ParamExpression

Retrieves the multi-dimensional array indices and associates a label with the corresponding parameter.

This method takes a vector of indices (idxs) specifying a position in a multi-dimensional array, along with a label string (element_label) to identify the parameter at that position.It returns the provided indices and internally associates the label with the corresponding parameter.

Parameters

idxs	a vector of indices specifying a position in a multi-dimensional array

Returns

th position in the multi-dimensional array

1. Param(self: vqcircuit.VQCircuit, emement_label: str) -> QPanda3::VQCParamSystem::ParamExpression

Retrieves the multidimensional array index for a variable parameter with a specified label.

This method takes a label string for a variable parameter and returns the corresponding multidimensional array index.

Parameters

emement_label

a label string to identify the parameter

Returns

th position in the multi-dimensional array

set_Param() [1/2]

None pyqpanda3.vqcircuit.vqcircuit.VQCircuit.set_Param	(		self,
		list[int]	dim_size_s )

set_Param(*args, **kwargs) Overloaded function.

1. set_Param(self: vqcircuit.VQCircuit, dim_size_s: list[int], dim_label_s: list[str]) -> None

Sets the dimension sizes and labels for the Param object.

This method allows the user to specify both the dimension sizes and corresponding labels for the Param object.

Parameters

dim_size_s	a vector with dim's sizes
dim_label_s	a vector with dim's labels

1. set_Param(self: vqcircuit.VQCircuit, dim_size_s: list[int]) -> None

Sets the dimension sizes for the Param object.

This method allows the user to specify the dimension sizes for the Param object using a vector of size_t values.

Parameters

dim_size_s

a vector with dim's sizes

set_Param() [2/2]

None pyqpanda3.vqcircuit.vqcircuit.VQCircuit.set_Param	(		self,
		list[int]	dim_size_s,
		list[str]	dim_label_s )

set_Param(*args, **kwargs) Overloaded function.

1. set_Param(self: vqcircuit.VQCircuit, dim_size_s: list[int], dim_label_s: list[str]) -> None

Sets the dimension sizes and labels for the Param object.

This method allows the user to specify both the dimension sizes and corresponding labels for the Param object.

Parameters

dim_size_s	a vector with dim's sizes
dim_label_s	a vector with dim's labels

1. set_Param(self: vqcircuit.VQCircuit, dim_size_s: list[int]) -> None

Sets the dimension sizes for the Param object.

This method allows the user to specify the dimension sizes for the Param object using a vector of size_t values.

Parameters

dim_size_s

a vector with dim's sizes

---

The documentation for this class was generated from the following file:

• pyqpanda3/vqcircuit/vqcircuit.pyi