delta = 1 # Level spacing
g = 1 # Interaction strength
#g /= 4
# Matrix elements
h_pq = np.identity(l)
for p in range(l):
h_pq[p, p] *= delta * (p - (p % 2)) / 2
h_pqrs = np.zeros((l, l, l, l))
for p in range(0, l - 1, 2):
for r in range(0, l - 1, 2):
h_pqrs[p, p + 1, r, r + 1] = -0.5 * g
# Prepare circuit list
pairing = SecondQuantizedHamiltonian(n, l, h_pq, h_pqrs)
grid_points = 500
x = np.linspace(0, 2 * np.pi, grid_points)
params = [[i] for i in x]
Es = np.zeros(grid_points)
legal = np.zeros(grid_points)
illegal = np.zeros(grid_points)
i = 0
for theta in tqdm(params):
vqe = VQE(pairing, ansatz='UCCD')
vqe.options['shots'] = 1000
vqe.options['count_states'] = True
vqe.options['backend'] = 'statevector_simulator'
Es[i] = vqe.expval()
odho = ODQD(n, l, grid_length, num_grid_points)
odho.setup_system(potential=HOPotential(omega), add_spin=True)
one_body = odho.h
one_body[np.absolute(one_body) < 1e-8] = 0
two_body = odho.u
two_body[np.absolute(two_body) < 1e-8] = 0
# Coupled Cluster
print('Reference energy:', odho.compute_reference_energy())
ccsd = CCSD(odho, verbose=False)
ccsd.compute_ground_state()
print('ECCSD =', ccsd.compute_energy())
# Prepare circuit list
H2 = SecondQuantizedHamiltonian(n, l)
H2.set_integrals(one_body, two_body, anti_symmetric=True)
H2.get_circuit()
circuit_list = H2.to_circuit_list(ptype='vqe')
ansatz = UnitaryCoupledCluster(n, l, 'S', 1)
og_params = ansatz.new_parameters(H2.h, H2.v)
print(ansatz.num_S)
print(ansatz.num_D)
print(len(og_params))
grid_points = 500
x = np.linspace(0, 2 * np.pi, grid_points)
params = [[i] for i in x]
Es = np.zeros(grid_points)
R = 0.7
print('For bond length {}'.format(R))
# Get psi4
h_pq, h_pqrs, Enuc, energies = get_H2_info(R)
# Save energies
cisd = energies['cisd']
ccsd = energies['ccsd']
fci = energies['fci']
hf = energies['hf']
# Prepare circuit list
H2 = SecondQuantizedHamiltonian(n,
l,
h_pq,
h_pqrs,
nuclear_repulsion=Enuc,
add_spin=True)
grid_points = 60
x = np.linspace(-0.1, 0.05, grid_points)
#params = [[i] for i in x]
params = []
for i in x:
for j in x:
params.append(np.array([i, j]))
Es = np.zeros(grid_points * grid_points)
shots = 1000
options = {'shots': shots}
i = 0
HFs = np.zeros_like(Rs)
Es = np.zeros_like(Rs)
VARs = np.zeros_like(Rs)
#vqe_coeffs = np.zeros((len(Rs),6))
#fci_coeffs = np.zeros((len(Rs),6))
i = 0
for R in tqdm(Rs):
h, v, Enuc, E = get_H2(R)
#fci_coeffs[i] = FCI(h,v)
FCIs[i] = E['fci']
HFs[i] = E['hf']
h2 = SecondQuantizedHamiltonian(n,
l,
h,
v,
nuclear_repulsion=Enuc,
add_spin=True)
h2.group_paulis(qwc=True, gc=True)
model = VQE(h2,
Minimizer('Cobyla', tol=1 / (10 * shots), disp=False),
'RYRZ',
options=options)
theta = model.optimize()
Es[i], VARs[i] = model.get_mean(theta, N=10000, M=10)
#vqe_coeffs[i] = model.get_state_coeffs(theta)
i += 1
np.save('RYRZ/bonds.npy', Rs)
h_pqrs = molecule.two_body_integrals
Enuc = molecule.nuclear_repulsion
fci_energy = molecule.fci_energy
print(fci_energy)
# OpenFermion Hamiltonian
molecular_hamiltonian = molecule.get_molecular_hamiltonian()
fermion_hamiltonian = get_fermion_operator(molecular_hamiltonian)
qubit_hamiltonian = jordan_wigner(fermion_hamiltonian)
qubit_hamiltonian.compress()
#print('The Jordan-Wigner Hamiltonian in canonical basis follows:\n{}'.format(qubit_hamiltonian))
circuit_list = qubit_hamiltonian
#h_pq, h_pqrs = molecular2sec_quant(h_pq,h_pqrs)
Model = SecondQuantizedHamiltonian(2,
4,
h_pq,
h_pqrs,
nuclear_repulsion=Enuc,
add_spin=True,
anti_symmetric=False)
#Model.get_circuit()
circuit_list2 = Model.circuit_list('vqe')
print('OepnFerm')
for i in circuit_list:
print(i)
print('New')
for i in circuit_list2:
print(i)
# Matrix elements
h_pq = np.identity(l)
for p in range(l):
h_pq[p, p] *= delta * (p - (p % 2)) / 2
h_pqrs = np.zeros((l, l, l, l))
for p in range(0, l - 1, 2):
for r in range(0, l - 1, 2):
h_pqrs[p, p + 1, r, r + 1] = -0.5 * g
UCCD = UnitaryCoupledCluster(n, l, 'D', 1)
theta = UCCD.new_parameters()
theta[0] = 5.829889373194686 # Hardcode good parameter
Pairing = SecondQuantizedHamiltonian(n, l)
Pairing.set_integrals(h_pq, h_pqrs)
Pairing.get_circuit()
circuit_list = Pairing.to_circuit_list(ptype='vqe')
all_shots = np.linspace(1000, 100000, 100)
Es = np.zeros(100)
legal = np.zeros(100)
illegal = np.zeros(100)
i = 0
for shot in tqdm(all_shots):
model = VQE(
n_qubits=l,
ansatz=UCCD,
circuit_list=circuit_list,
energies['ccsd'] = h2_molecule.ccsd_energy
#print('electron:',h2_molecule.n_electrons)
return one_body, two_body, Enuc, energies
h, v, Enuc, E = get_H2_info(0.7)
fci = E['fci']
hf = E['hf']
print('HF energy:', hf)
print('FCI energy:', fci)
mol = SecondQuantizedHamiltonian(2,
4,
h,
v,
nuclear_repulsion=Enuc,
add_spin=True)
options = {
'shots': 1000,
'optimization_level': 1,
#'device':'ibmq_london',
#'layout':[1,0,2,3],
#'noise_model':True,
#'basis_gates':True,
#'coupling_map':True,
#'seed':1,
'print': True
}
#options = {'shots':10000,'print':True}
from quantum_circuit import QuantumCircuit, SecondQuantizedHamiltonian, PairingHamiltonian, CircuitList, PauliString, X
l = 4 # number of spin orbitals / number of qubits
n = 2 # Number of occupied spin orbitals
Rs = [0.4, 0.74, 1.0, 1.6, 2.2, 2.8]
fci = np.zeros_like(Rs)
hf = np.zeros_like(Rs)
vqe_factors = np.zeros_like(Rs)
for i, R in enumerate(Rs):
h, v, Enuc, E = get_h2_matrix(R)
fci[i] = E['fci']
hf[i] = E['hf']
h2 = SecondQuantizedHamiltonian(n,
l,
h,
v,
nuclear_repulsion=Enuc,
add_spin=True)
for p in h2.circuit_list('vqe'):
if len(p) == 0:
print('factor:', p.factor)
vqe_factors[i] = p.factor
np.save('fci.npy', fci)
np.save('hf.npy', hf)
np.save('vqe_factors.npy', vqe_factors)
fci_coeffs = np.zeros((len(omegas), 6))
Es_ideal = np.zeros_like(omegas)
VARs_ideal = np.zeros_like(omegas)
vqe_coeffs_ideal = np.zeros((len(omegas), 6))
Es_noisy = np.zeros_like(omegas)
VARs_noisy = np.zeros_like(omegas)
vqe_coeffs_noisy = np.zeros((len(omegas), 6))
i = 0
for omega in tqdm(omegas):
h, v, E = get_qdot_matrix(n, l, omega)
ev, vv = FCI(n, l, h, v, ret_all=True)
FCIs[i] = ev[0]
HFs[i] = E[0].real
fci_coeffs[i] = vv[:, 0].real
h2 = SecondQuantizedHamiltonian(n, l, h, v, anti_symmetric=True)
h2.group_paulis(qwc=True, gc=True)
# Ideal
model = VQE(h2,
Minimizer('Cobyla', tol=1 / (100 * shots), disp=False),
'UCCSD',
options=option_ideal)
theta = model.optimize()
Es_ideal[i], VARs_ideal[i] = model.get_mean(theta, N=10000, M=10)
vqe_coeffs_ideal[i] = model.get_state_coeff(theta)
# Noisy
model = VQE(h2,
Minimizer('Cobyla', tol=1 / (100 * shots), disp=False),
'UCCSD',
options=option_noisy)
h_pq[p, p] *= delta * (p - (p % 2)) / 2
h_pqrs = np.zeros((l, l, l, l))
for p in range(0, l - 1, 2):
for r in range(0, l - 1, 2):
h_pqrs[p, p + 1, r, r + 1] = -0.5 * g
def pairing_ansatz(qc, qb, n_simulation):
for qbit in range(0, n_simulation, 2):
qc.h(qb[qbit])
qc.cx(qb[qbit], qb[qbit + 1])
return qc
n_work = 6
Emax = 2
t = 0.49 * np.pi
rho = 10
print('Setting up Hamiltonian')
pairing_model = SecondQuantizedHamiltonian(n, l, h_pq, h_pqrs, exp=True)
print('Setting up QPE class')
qpe = QPE(pairing_model, pairing_ansatz, n_work, Emax, t=t, rho=rho)
print('Running...')
qpe.estimate()
plt.plot(qpe.x, qpe.y)
plt.show()
from quantum_circuit import SecondQuantizedHamiltonian
from optimizer import Minimizer
from vqe import VQE
l = 4 # number of spin orbitals / number of qubits
n = 2 # Number of occupied spin orbitals
omega = 1
h, v, E = get_qdot_matrix(n, l, omega)
print(E, FCI(n, l, h, v))
qdot = SecondQuantizedHamiltonian(n, l, h, v, anti_symmetric=True)
qdot.group_paulis()
options = {
'shots': 10000,
'print': True,
'device': 'ibmq_london',
'noise_model': True,
'meas_fit': True,
'coupling_map': True,
'layout': [1, 0, 2, 3],
'basis_gates': True
}
model = VQE(qdot,
Minimizer('Cobyla'),
'RYPAIRING',
