Functions
def	generate_circuit_ansatz (layers, inner_blocks, qbit_num)

def	generate_hamiltonian (n)

def	generate_hamiltonian_tmp (n)

Variables
dictionary	config

	eigval = np.real(eigvals[0])

	eigvec = eigvecs[:,0]

	entropy = VQE_Heisenberg.get_Second_Renyi_Entropy( parameters=parameters, qubit_list=qubit_list )

	entropy_exact_gs = VQE_Heisenberg.get_Second_Renyi_Entropy( parameters=np.array([]), qubit_list=[0,1], input_state=eigvec )

	flush

def	Hamiltonian = generate_hamiltonian_tmp( qbit_num )

	initial_state = np.zeros( (1 << qbit_num), dtype=np.complex128 )

int	inner_blocks = 1

	k

int	layers = 1000

	linewidth

int	normalized_entropy = entropy/page_entropy

int	normalized_entropy_exact_gs = entropy_exact_gs/page_entropy

	overlap = state_to_transform.transpose().conjugate() @ eigvecs

	overlap_norm = np.real(overlap * overlap.conjugate())

int	page_entropy = 2 * np.log(2.0) - 1.0/( pow(2, qbit_num-2*2+1) )

	param_num = VQE_Heisenberg.get_Parameter_Num()

	parameters = np.load( 'COSINE_1000x1_layers_Heisenberg_16_3point_zero_init_3overlap0.8602661822824491.npy' )

int	qbit_num = 16

list	qubit_list = [0,1]

def	squander_circuit = generate_circuit_ansatz( layers, inner_blocks, qbit_num)

	state_to_transform = initial_state.copy()

list	topology = []

	VQE_energy = VQE_Heisenberg.Optimization_Problem( parameters )

	VQE_Heisenberg = Variational_Quantum_Eigensolver(Hamiltonian, qbit_num, config)

	which

Function Documentation

◆ generate_circuit_ansatz()

def 16_qubit_trained_circuit_VQE.generate_circuit_ansatz	(	layers,
		inner_blocks,
		qbit_num
	)

Definition at line 49 of file 16_qubit_trained_circuit_VQE.py.

◆ generate_hamiltonian()

def 16_qubit_trained_circuit_VQE.generate_hamiltonian ( n )

Definition at line 35 of file 16_qubit_trained_circuit_VQE.py.

◆ generate_hamiltonian_tmp()

def 16_qubit_trained_circuit_VQE.generate_hamiltonian_tmp ( n )

Definition at line 20 of file 16_qubit_trained_circuit_VQE.py.

Variable Documentation

◆ config

dictionary 16_qubit_trained_circuit_VQE.config

Initial value:

 =  {"max_inner_iterations":800, 
      "batch_size": 128,
      "convergence_length": 20}

Definition at line 158 of file 16_qubit_trained_circuit_VQE.py.

◆ eigval

16_qubit_trained_circuit_VQE.eigval = np.real(eigvals[0])

Definition at line 151 of file 16_qubit_trained_circuit_VQE.py.

◆ eigvec

16_qubit_trained_circuit_VQE.eigvec = eigvecs[:,0]

Definition at line 152 of file 16_qubit_trained_circuit_VQE.py.

◆ entropy

16_qubit_trained_circuit_VQE.entropy = VQE_Heisenberg.get_Second_Renyi_Entropy( parameters=parameters, qubit_list=qubit_list )

Definition at line 199 of file 16_qubit_trained_circuit_VQE.py.

◆ entropy_exact_gs

16_qubit_trained_circuit_VQE.entropy_exact_gs = VQE_Heisenberg.get_Second_Renyi_Entropy( parameters=np.array([]), qubit_list=[0,1], input_state=eigvec )

Definition at line 184 of file 16_qubit_trained_circuit_VQE.py.