Classes
class	qgd_Variational_Quantum_Eigensolver_Base
	A QGD Python interface class for the decomposition of N-qubit unitaries into U3 and CNOT gates. More...

Functions
def	__init__ (self, Hamiltonian, qbit_num, config=None, accelerator_num=0, backend=None, density_noise=None)
	Constructor of the class. More...

def	_normalize_density_noise_spec (density_noise)

def	_normalize_vqe_backend_name (backend)

def	apply_to (self, parameters_mtx, state_to_be_transformed)

def	describe_density_bridge (self)
	Return reviewable metadata for the currently supported density bridge. More...

def	Generate_Circuit (self, layers, inner_blocks=1)
	Call to generate the circuit ansatz. More...

def	get_Circuit (self)
	Call to retrieve the incorporated quantum circuit (Squander format) More...

def	get_Optimized_Parameters (self)
	Call to get the optimized parameters set in numpy array. More...

def	get_Parameter_Num (self)
	Call to get the number of free parameters in the gate structure used for the decomposition. More...

def	get_Qbit_Num (self)
	Call to get the number of qubits in the circuit. More...

def	get_Qiskit_Circuit (self)
	Export the unitary decomposition into Qiskit format. More...

def	get_Second_Renyi_Entropy (self, parameters=None, input_state=None, qubit_list=None)
	Call to get the second RÃ©nyi entropy. More...

def	Optimization_Problem (self, parameters)
	Call to evaluate the VQE energy. More...

def	Optimization_Problem_Grad (self, parameters)
	Call to evaluate the VQE energy. More...

def	set_Ansatz (self, ansatz_new)
	Call to set the ansatz type. More...

def	set_Density_Matrix_Noise (self, density_noise)
	Configure ordered fixed local-noise insertions for the density backend. More...

def	set_Gate_Structure (self, Gate_structure)
	Call to set custom gate structure to used in the decomposition. More...

def	set_Gate_Structure_from_Binary (self, filename)
	Call to set custom layers to the gate structure that are intended to be used in the decomposition from a binary file created from SQUANDER. More...

def	set_Initial_State (self, initial_state)
	Call to get the number of free parameters in the gate structure used for the decomposition. More...

def	set_Optimization_Tolerance (self, tolerance)

def	set_Optimized_Parameters (self, new_params)
	Call to set the parameters which are used as a starting point in the optimization. More...

def	set_Optimizer (self, alg)
	Call to set the optimizer used in the VQE process. More...

def	set_Project_Name (self, project_name)
	Call to set the name of the SQUANDER project. More...

def	Start_Optimization (self)
	Call to start solving the VQE problem to get the approximation for the ground state. More...

Variables
	_DENSITY_NOISE_CHANNEL_SPECS

	_VQE_BACKEND_CONFIG_KEY

	_VQE_BACKEND_NAME_TO_CODE

	_VQE_DEFAULT_BACKEND

	backend

	density_noise

	qbit_num

Function Documentation

◆ init()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.__init__	(	self,
		Hamiltonian,
		qbit_num,
		config = `None`,
		accelerator_num = `0`,
		backend = `None`,
		density_noise = `None`
	)

Constructor of the class.

Parameters

Umtx	The unitary matrix to be decomposed.
config	Dictionary describing optimization hyperparameters.
accelerator_num	Optional accelerator identifier.
backend	Optional backend selector. Supported values are "state_vector" and "density_matrix". When omitted, the VQE keeps the legacy state-vector behavior. Explicit `backend="density_matrix"` activates the supported exact noisy mixed-state energy path for the Phase 2 anchor workflow.
density_noise	Optional ordered list of fixed local density-noise insertions. Each entry must define a channel, target qubit, after_gate_index, and fixed noise value. The canonical Phase 2 local-noise channels are `local_depolarizing`, `amplitude_damping`, and `phase_damping`; the aliases `depolarizing` and `dephasing` normalize to the local canonical names. Phase 2 only supports this surface together with `backend="density_matrix"` on the supported `HEA` anchor circuit.

Returns: An instance of the class

Definition at line 175 of file qgd_Variational_Quantum_Eigensolver_Base.py.

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◆ _normalize_density_noise_spec()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base._normalize_density_noise_spec ( density_noise )

private

Definition at line 68 of file qgd_Variational_Quantum_Eigensolver_Base.py.

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◆ _normalize_vqe_backend_name()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base._normalize_vqe_backend_name ( backend )

private

Definition at line 48 of file qgd_Variational_Quantum_Eigensolver_Base.py.

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◆ apply_to()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.apply_to	(	self,
		parameters_mtx,
		state_to_be_transformed
	)

Definition at line 345 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ describe_density_bridge()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.describe_density_bridge ( self )

Return reviewable metadata for the currently supported density bridge.

Returns: A dictionary describing the generated source, ordered bridge operations, and fixed local-noise insertions used by the density path.

Definition at line 404 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ Generate_Circuit()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.Generate_Circuit	(	self,
		layers,
		inner_blocks = `1`
	)

Call to generate the circuit ansatz.

Parameters

layers	The number of layers. The depth of the generated circuit is 2*layers+1 (U3-CNOT-U3-CNOT...CNOT)
inner_blocks	The number of U3-CNOT repetition within a single layer

Definition at line 264 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Circuit()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Circuit ( self )

Call to retrieve the incorporated quantum circuit (Squander format)

Returns: Return with a Qiskit compatible quantum circuit.

Definition at line 354 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Optimized_Parameters()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Optimized_Parameters ( self )

Call to get the optimized parameters set in numpy array.

Returns: Returns with the optimized parameters

Definition at line 218 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Parameter_Num()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Parameter_Num ( self )

Call to get the number of free parameters in the gate structure used for the decomposition.

Definition at line 336 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Qbit_Num()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Qbit_Num ( self )

Call to get the number of qubits in the circuit.

Returns: Returns with the number of qubits

Definition at line 329 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Qiskit_Circuit()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Qiskit_Circuit ( self )

Export the unitary decomposition into Qiskit format.

Returns: Return with a Qiskit compatible quantum circuit.

Definition at line 364 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ get_Second_Renyi_Entropy()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.get_Second_Renyi_Entropy	(	self,
		parameters = `None`,
		input_state = `None`,
		qubit_list = `None`
	)

Call to get the second RÃ©nyi entropy.

Parameters

parameters	A float64 numpy array
input_state	A complex array storing the input state. If None \|0> is created.
qubit_list	A subset of qubits for which the RÃ©nyi entropy should be calculated. Returns with the calculated entropy

Definition at line 288 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ Optimization_Problem()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.Optimization_Problem	(	self,
		parameters
	)

Call to evaluate the VQE energy.

Parameters

parameters A float64 numpy array. The number of parameters can be retrieved with method get_Parameter_Num

Definition at line 271 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ Optimization_Problem_Grad()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.Optimization_Problem_Grad	(	self,
		parameters
	)

Call to evaluate the VQE energy.

Parameters

parameters A float64 numpy array. The number of parameters can be retrieved with method get_Parameter_Num

Definition at line 278 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ set_Ansatz()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.set_Ansatz	(	self,
		ansatz_new
	)

Call to set the ansatz type.

Currently imp

Parameters

ansatz_new String of the ansatz . Possible values: "HEA" (hardware efficient ansatz with U3 and CNOT gates).

Definition at line 256 of file qgd_Variational_Quantum_Eigensolver_Base.py.

◆ set_Density_Matrix_Noise()

def squander.VQA.qgd_Variational_Quantum_Eigensolver_Base.set_Density_Matrix_Noise	(	self,
		density_noise
	)

Configure ordered fixed local-noise insertions for the density backend.

Parameters

density_noise A list of dictionaries with channel, target, after_gate_index, and noise value metadata. The supported required Phase 2 local-noise vocabulary is local_depolarizing, amplitude_damping, and phase_damping; depolarizing and dephasing are accepted aliases that normalize to the canonical local names. Phase 2 treats this as a mixed-state-only surface and rejects it on state_vector workflows. The supported positive path is the exact noisy HEA anchor workflow on the density_matrix backend.