def generate(self, inputParams):
src = """0.7080240949826064
- 1.248846801817026 0^ 0
- 1.248846801817026 1^ 1
- 0.4796778151607899 2^ 2
- 0.4796778151607899 3^ 3
+ 0.33667197218932576 0^ 1^ 1 0
+ 0.0908126658307406 0^ 1^ 3 2
+ 0.09081266583074038 0^ 2^ 0 2
+ 0.331213646878486 0^ 2^ 2 0
+ 0.09081266583074038 0^ 3^ 1 2
+ 0.331213646878486 0^ 3^ 3 0
+ 0.33667197218932576 1^ 0^ 0 1
+ 0.0908126658307406 1^ 0^ 2 3
+ 0.09081266583074038 1^ 2^ 0 3
+ 0.331213646878486 1^ 2^ 2 1
+ 0.09081266583074038 1^ 3^ 1 3
+ 0.331213646878486 1^ 3^ 3 1
+ 0.331213646878486 2^ 0^ 0 2
+ 0.09081266583074052 2^ 0^ 2 0
+ 0.331213646878486 2^ 1^ 1 2
+ 0.09081266583074052 2^ 1^ 3 0
+ 0.09081266583074048 2^ 3^ 1 0
+ 0.34814578469185886 2^ 3^ 3 2
+ 0.331213646878486 3^ 0^ 0 3
+ 0.09081266583074052 3^ 0^ 2 1
+ 0.331213646878486 3^ 1^ 1 3
+ 0.09081266583074052 3^ 1^ 3 1
+ 0.09081266583074048 3^ 2^ 0 1
+ 0.34814578469185886 3^ 2^ 2 3"""
inputParams['rdm-source'] = src
return xacc.getObservable('fermion', src)
def runVqeGradientDescent(gradientStrategy):
# Get access to the desired QPU and
# allocate some qubits to run on
qpu = xacc.getAccelerator('qpp')
# Construct the Hamiltonian as an XACC PauliOperator
ham = xacc.getObservable('pauli', '1.0 Y0')
# Ansatz circuit:
xacc.qasm('''.compiler xasm
.circuit ansatz
.qbit q
.parameters t0, t1, t2, t3
// State-prep
Ry(q[0], pi/4);
Ry(q[1], pi/3);
Ry(q[2], pi/7);
// Parametrized gates (layer 1)
Rz(q[0], t0);
Rz(q[1], t1);
CX(q[0], q[1]);
CX(q[1], q[2]);
// Parametrized gates (layer 2)
Ry(q[1], t2);
Rx(q[2], t3);
CX(q[0], q[1]);
CX(q[1], q[2]);
''')
# We need 4 qubits
buffer = xacc.qalloc(4)
ansatz_circuit = xacc.getCompiled('ansatz')
initParams = [0.432, -0.123, 0.543, 0.233]
opt = xacc.getOptimizer(
'mlpack',
{
# Using gradient descent:
'mlpack-optimizer': 'gd',
'initial-parameters': initParams,
'mlpack-step-size': 0.01,
'mlpack-max-iter': 200
})
# Create the VQE algorithm with the requested gradient strategy
vqe = xacc.getAlgorithm(
'vqe', {
'ansatz': ansatz_circuit,
'accelerator': qpu,
'observable': ham,
'optimizer': opt,
'gradient_strategy': gradientStrategy
})
vqe.execute(buffer)
energies = buffer.getInformation('params-energy')
return energies
# Simple 1-qubit demonstration of the Quatum Imaginary Time Evolution/QLanczos algorithm
# Reference: https://www.nature.com/articles/s41567-019-0704-4
# Target H = 1/sqrt(2)(X + Z)
# Expected minimum value: -1.0
import xacc, sys, numpy as np
import matplotlib.pyplot as plt
# Get access to the desired QPU and
# allocate some qubits to run on
qpu = xacc.getAccelerator('qpp')
# Construct the Hamiltonian as an XACC PauliOperator
ham = xacc.getObservable('pauli', '0.70710678118 X0 + 0.70710678118 Z0')
# See Fig. 2 (e) of https://www.nature.com/articles/s41567-019-0704-4
# Horizontal axis: 0 -> 2.5
# The number of Trotter steps
nbSteps = 25
# The Trotter step size
stepSize = 0.1
# Create the QITE algorithm
qite = xacc.getAlgorithm('qite', {
'accelerator': qpu,
'observable': ham,
'step-size': stepSize,
'steps': nbSteps
})
# We just need 1 qubit
qiteBuffer = xacc.qalloc(1)
import xacc
import sys
import numpy as np
# Get access to the desired QPU and
# allocate some qubits to run on
qpu = xacc.getAccelerator('tnqvm', {'vqe-mode': True})
buffer = xacc.qalloc(4)
nahHamStr = '(0.0816923,0) Z2 Z3 + (0.11747,0) Z1 Z3 + (-0.00944179,0) Z1 Y2 Y3 + (0.101934,0) Z0 Z3 + (0.0229208,0) Y0 Y1 Z2 + (0.158901,0) Z0 Z2 + (0.0229208,0) Z0 X2 X3 + (-0.387818,0) Z3 + (0.0323625,0) X2 X3 + (0.0816923,0) Z0 Z1 + (-0.00944179,0) Z1 X2 X3 + (-0.00944179,0) X0 X1 Z3 + (0.0323625,0) Y2 Y3 + (0.0202421,0) X0 X1 Y2 Y3 + (0.0149387,0) Z0 + (0.0149387,0) Z2 + (-0.387818,0) Z1 + (0.0323625,0) Y0 Y1 + (-0.00944179,0) Y0 Y1 Z3 + (0.0229208,0) X0 X1 Z2 + (0.101934,0) Z1 Z2 + (0.0323625,0) X0 X1 + (0.0229208,0) Z0 Y2 Y3 + (-159.403,0) + (0.0202421,0) Y0 Y1 Y2 Y3 + (0.0202421,0) X0 X1 X2 X3 + (0.0202421,0) Y0 Y1 X2 X3'
ham = xacc.getObservable('pauli', nahHamStr)
@xacc.qpu(algo='vqe', accelerator=qpu, observable=ham)
def ansatz(q, x):
X(q[0])
X(q[2])
ucc3(q, x[0], x[1], x[2])
ansatz(buffer, [0.0, 0.0, 0.0])
print('Energy = ', buffer.getInformation('opt-val'))
print('Opt Angles = ', buffer.getInformation('opt-params'))
def execute(self, inputParams):
xacc_opts = inputParams['XACC']
acc_name = xacc_opts['accelerator']
qpu = xacc.getAccelerator(acc_name, xacc_opts)
if 'verbose' in xacc_opts and xacc_opts['verbose']:
xacc.set_verbose(True)
if 'Benchmark' not in inputParams:
xacc.error('Invalid benchmark input - must have Benchmark description')
if 'Observable' not in inputParams:
xacc.error('Invalid benchmark input - must have Observable description')
if 'Ansatz' not in inputParams:
xacc.error('Invalid benchmark input - must have Ansatz circuit description')
if 'Decorators' in inputParams:
if 'readout_error' in inputParams['Decorators']:
qpu = xacc.getAcceleratorDecorator('ro-error', qpu)
H = None
if inputParams['Observable']['name'] == 'pauli':
obs_str = inputParams['Observable']['obs_str']
H = xacc.getObservable('pauli', obs_str)
elif inputParams['Observable']['name'] == 'fermion':
obs_str = inputParams['Observable']['obs_str']
H = xacc.getObservable('fermion', obs_str)
elif inputParams['Observable']['name'] == 'psi4':
opts = {'basis':inputParams['Observable']['basis'], 'geometry':inputParams['Observable']['geometry']}
if 'fo' in inputParams['Observable'] and 'ao' in inputParams['Observable']:
opts['frozen-spin-orbitals'] = ast.literal_eval(inputParams['Observable']['fo'])
opts['active-spin-orbitals'] = ast.literal_eval(inputParams['Observable']['ao'])
H = xacc.getObservable('psi4', opts)
#print('Ham: ', H.toString())
buffer = xacc.qalloc(H.nBits())
optimizer = None
if 'Optimizer' in inputParams:
# check that values that can be ints/floats are
opts = inputParams['Optimizer']
for k,v in inputParams['Optimizer'].items():
try:
i = int(v)
opts[k] = i
continue
except:
pass
try:
f = float(v)
opts[k] = f
continue
except:
pass
optimizer = xacc.getOptimizer(inputParams['Optimizer']['name'] if 'Optimizer' in inputParams else 'nlopt', opts)
else:
optimizer = xacc.getOptimizer('nlopt')
provider = xacc.getIRProvider('quantum')
if 'source' in inputParams['Ansatz']:
# here assume this is xasm always
src = inputParams['Ansatz']['source']
xacc.qasm(src)
# get the name of the circuit
circuit_name = None
for l in src.split('\n'):
if '.circuit' in l:
circuit_name = l.split(' ')[1]
ansatz = xacc.getCompiled(circuit_name)
else:
ansatz = provider.createInstruction(inputParams['Ansatz']['ansatz'])
ansatz = xacc.asComposite(ansatz)
alg = xacc.getAlgorithm(inputParams['Benchmark']['algorithm'], {
'ansatz': ansatz,
'accelerator': qpu,
'observable': H,
'optimizer': optimizer,
})
alg.execute(buffer)
return buffer
import xacc
xacc.set_verbose(True)
accelerator = xacc.getAccelerator("qpp")
buffer = xacc.qalloc(4)
optimizer = xacc.getOptimizer('nlopt', {'nlopt-optimizer': 'l-bfgs'})
pool = "multi-qubit-qaoa"
nLayers = 2
subAlgo_qaoa = "QAOA"
H = xacc.getObservable(
'pauli',
'-5.0 - 0.5 Z0 - 1.0 Z2 + 0.5 Z3 + 1.0 Z0 Z1 + 2.0 Z0 Z2 + 0.5 Z1 Z2 + 2.5 Z2 Z3'
)
adapt = xacc.getAlgorithm(
'adapt', {
'accelerator': accelerator,
'observable': H,
'optimizer': optimizer,
'pool': pool,
'maxiter': nLayers,
'sub-algorithm': subAlgo_qaoa
})
adapt.execute(buffer)
# Simple 3-qubit demonstration of the Quatum Imaginary Time Evolution algorithm
# for Deuteron H3 Hamiltonian
# Reference: https://arxiv.org/pdf/1912.06226.pdf
# Expected minimum value: -2.04482
import xacc, sys, numpy as np
import matplotlib.pyplot as plt
# Get access to the desired QPU and
# allocate some qubits to run on
qpu = xacc.getAccelerator('qpp')
# Construct the H3 Hamiltonian
ham = xacc.getObservable(
'pauli',
'5.907 - 2.1433 X0X1 - 2.1433 Y0Y1 + .21829 Z0 - 6.125 Z1 + 9.625 - 9.625 Z2 - 3.91 X1 X2 - 3.91 Y1 Y2'
)
xacc.qasm('''.compiler xasm
.circuit prep
.qbit q
X(q[0]);
''')
prep_circuit = xacc.getCompiled('prep')
# We need 3 qubits for this case (H3)
buffer = xacc.qalloc(3)
# Horizontal axis: 0 -> 0.3 (step = 0.05)
# The number of Trotter steps
nbSteps = 6
qpu = xacc.getAccelerator('tnqvm', {'vqe-mode': True})
buffer = xacc.qalloc(4)
geom = '''
0 1
Na 0.000000 0.0 0.0
H 0.0 0.0 1.914388
symmetry c1
'''
fo = [0, 1, 2, 3, 4, 10, 11, 12, 13, 14]
ao = [5, 9, 15, 19]
H = xacc.getObservable(
'psi4-frozen-core', {
'basis': 'sto-3g',
'geometry': geom,
'frozen-spin-orbitals': fo,
'active-spin-orbitals': ao
})
@xacc.qpu(algo='vqe', accelerator=qpu, observable=H)
def ansatz(q, x):
X(q[0])
X(q[2])
ucc1(q, x[0])
print(ansatz.getFunction().toString())
print(ansatz.getFunction().getVariables())
import xacc
accelerator = xacc.getAccelerator("qpp")
H = xacc.getObservable(
'pauli',
'0.2976 + 0.3593 Z0 - 0.4826 Z1 + 0.5818 Z0 Z1 + 0.0896 X0 X1 + 0.0896 Y0 Y1'
)
expansion = 'Cioslowski'
order = 2
provider = xacc.getIRProvider('quantum')
ansatz = provider.createComposite('initial-state')
ansatz.addInstruction(provider.createInstruction('X', [0]))
buffer = xacc.qalloc(2)
qcmx = xacc.getAlgorithm(
'qcmx', {
'accelerator': accelerator,
'observable': H,
'ansatz': ansatz,
'cmx-order': order,
'expansion-type': expansion
})
qcmx.execute(buffer)
print('Energy = ', buffer.getInformation('opt-val'))
def fromOptions(self, inputParams):
import numpy as np, sys, io, os
from pyscf import gto, scf, dft, tddft
from pyscf.lib import logger
mol = gto.mole.Mole()
sys.argv = ['']
mol.atom = inputParams['geometry']
mol.basis = inputParams['basis']
if 'verbose' in inputParams and inputParams['verbose']:
mol.build()
else:
mol.build(verbose=logger.QUIET)
scf_wfn = scf.RHF(mol) # needs to be changed for open-shells
scf_wfn.conv_tol = 1e-8
scf_wfn.kernel() # runs RHF calculations
scf_e = scf_wfn.e_tot
E_nucl = mol.energy_nuc()
# Get MO coefficients from SCF wavefunction
# ==> ERIs <==
# Create instance of MintsHelper class:
nbf = mol.nao # number of basis functions
nso = 2 * nbf # number of spin orbitals
# Assuming RHF for now, easy to generalize later
nalpha = (scf_wfn.mo_occ == 2).sum()
nbeta = (scf_wfn.mo_occ == 2).sum()
nocc = nalpha + nbeta # number of occupied orbitals
nvirt = 2 * nbf - nocc # number of virtual orbitals
list_occ_alpha = scf_wfn.mo_occ
list_occ_beta = scf_wfn.mo_occ
# Get orbital energies
eps_a = scf_wfn.mo_energy
eps_b = scf_wfn.mo_energy
eps = np.append(eps_a, eps_b)
# Get orbital coefficients:
Ca = scf_wfn.mo_coeff
Cb = scf_wfn.mo_coeff
C = np.block([[Ca, np.zeros_like(Cb)], [np.zeros_like(Ca), Cb]])
# Get the two electron integrals using MintsHelper
Ints = mol.intor('int2e_sph')
def spin_block_tei(I):
"""
Function that spin blocks two-electron integrals
Using np.kron, we project I into the space of the 2x2 identity, tranpose the result
and project into the space of the 2x2 identity again. This doubles the size of each axis.
The result is our two electron integral tensor in the spin orbital form.
"""
identity = np.eye(2)
I = np.kron(identity, I)
return np.kron(identity, I.T)
# Spin-block the two electron integral array
I_spinblock = spin_block_tei(Ints)
# Converts chemist's notation to physicist's notation, and antisymmetrize
# (pq | rs) ---> <pr | qs>
# Physicist's notation
tmp = I_spinblock.transpose(0, 2, 1, 3)
# Antisymmetrize:
# <pr||qs> = <pr | qs> - <pr | sq>
gmo = tmp - tmp.transpose(0, 1, 3, 2)
gmo = np.einsum('pqrs, sS -> pqrS', gmo, C)
gmo = np.einsum('pqrS, rR -> pqRS', gmo, C)
gmo = np.einsum('pqRS, qQ -> pQRS', gmo, C)
gmo = np.einsum('pQRS, pP -> PQRS', gmo, C)
# -------- 0-body term:
Hamiltonian_0body = E_nucl
# -------- 1-body term:
# Ca*
# Build core Hamiltonian
T = mol.intor_symmetric('int1e_kin')
V = mol.intor_symmetric('int1e_nuc')
H_core_ao = T + V
# -- check which one more efficient (matmul vs einsum)
# H_core_mo = np.matmul(Ca.T,np.matmul(H_core_ao,Ca)))
#
H_core_mo = np.einsum('ij, jk, kl -> il', Ca.T, H_core_ao, Ca)
H_core_mo_alpha = H_core_mo
H_core_mo_beta = H_core_mo
# ---- this version breaks is we permuted SCF eigvecs
# Hamiltonian_1body = np.block([
# [ H_core_mo_alpha , np.zeros_like(H_core_mo_alpha)],
# [np.zeros_like(H_core_mo_beta) , H_core_mo_beta ]])
#
# --- th is version is safer than above (H_1b is permutted correctly if eigvecs are permutted)
Hamiltonian_1body_ao = np.block([[H_core_ao,
np.zeros_like(H_core_ao)],
[np.zeros_like(H_core_ao),
H_core_ao]])
Hamiltonian_1body = np.einsum('ij, jk, kl -> il', C.T,
Hamiltonian_1body_ao, C)
Hamiltonian_2body = gmo
if 'frozen-spin-orbitals' in inputParams and 'active-spin-orbitals' in inputParams:
MSO_frozen_list = inputParams['frozen-spin-orbitals']
MSO_active_list = inputParams['active-spin-orbitals']
n_frozen = len(MSO_frozen_list)
n_active = len(MSO_active_list)
else:
MSO_frozen_list = []
MSO_active_list = range(Hamiltonian_1body.shape[0])
n_frozen = 0
n_active = len(MSO_active_list)
# ----- 0-body frozen-core:
Hamiltonian_fc_0body = E_nucl
for a in range(n_frozen):
ia = MSO_frozen_list[a]
Hamiltonian_fc_0body += Hamiltonian_1body[ia, ia]
for b in range(a):
ib = MSO_frozen_list[b]
Hamiltonian_fc_0body += gmo[ia, ib, ia, ib]
f_str = str(Hamiltonian_fc_0body)
pos_or_neg = lambda x: ' + ' if x > 0. else ' - '
# --- 1-body frozen-core:
Hamiltonian_fc_1body = np.zeros((n_active, n_active))
Hamiltonian_fc_1body_tmp = np.zeros((n_active, n_active))
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
Hamiltonian_fc_1body[p, q] = Hamiltonian_1body[ip, iq]
#Hamiltonian_fc_1body_tmp[p,q] = Hamiltonian_1body[ip,iq]
for a in range(n_frozen):
ia = MSO_frozen_list[a]
Hamiltonian_fc_1body[p, q] += gmo[ia, ip, ia, iq]
if abs(Hamiltonian_fc_1body[p, q]) > 1e-12:
f_str += pos_or_neg(Hamiltonian_fc_1body[p, q]) + str(
abs(Hamiltonian_fc_1body[p, q])) + ' ' + str(
p) + '^ ' + str(q)
# ------- 2-body frozen-core:
Hamiltonian_fc_2body = np.zeros(
(n_active, n_active, n_active, n_active))
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
for r in range(n_active):
ir = MSO_active_list[r]
for ss in range(n_active):
iss = MSO_active_list[ss]
#Hamiltonian_fc_2body[p,q,r,ss]= 0.25* gmo[ip,iq,ir,iss]
Hamiltonian_fc_2body[p, q, r, ss] = gmo[ip, iq, ir,
iss]
#Hamiltonian_fc_2body[p,q,r,ss]= 0.25* gmo[ip,iq,iss,ir]
Hamiltonian_fc_2body_tmp = 0.25 * Hamiltonian_fc_2body.transpose(
0, 1, 3, 2)
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
for r in range(n_active):
ir = MSO_active_list[r]
for ss in range(n_active):
if abs(Hamiltonian_fc_2body_tmp[p, q, r, ss]) > 1e-12:
f_str += pos_or_neg(
Hamiltonian_fc_2body_tmp[p, q, r, ss]) + str(
abs(Hamiltonian_fc_2body_tmp[p, q, r, ss])
) + ' ' + str(p) + '^ ' + str(q) + '^ ' + str(
r) + ' ' + str(ss)
self.observable = xacc.getObservable('fermion', f_str)
self.asPauli = xacc.transformToPauli('jw', self.observable)
def fromOptions(self, inputParams):
import numpy as np
import psi4
psi4.core.be_quiet()
g = inputParams['geometry']
basis = inputParams['basis']
moleculeGeom = psi4.geometry(g)
psi4.set_options({
'basis': basis,
'scf_type': 'pk',
'mp2_type': 'conv',
'e_convergence': 1e-8,
'd_convergence': 1e-8
})
scf_e, scf_wfn = psi4.energy('scf', return_wfn=True)
E_nucl = moleculeGeom.nuclear_repulsion_energy()
# Get MO coefficients from SCF wavefunction
# ==> ERIs <==
# Create instance of MintsHelper class:
mints = psi4.core.MintsHelper(scf_wfn.basisset())
nbf = mints.nbf() # number of basis functions
nso = 2 * nbf # number of spin orbitals
nalpha = scf_wfn.nalpha() # number of alpha electrons
nbeta = scf_wfn.nbeta() # number of beta electrons
nocc = nalpha + nbeta # number of occupied orbitals
nvirt = 2 * nbf - nocc # number of virtual orbitals
list_occ_alpha = np.asarray(scf_wfn.occupation_a())
list_occ_beta = np.asarray(scf_wfn.occupation_b())
# Get orbital energies
eps_a = np.asarray(scf_wfn.epsilon_a())
eps_b = np.asarray(scf_wfn.epsilon_b())
eps = np.append(eps_a, eps_b)
# Get orbital coefficients:
Ca = np.asarray(scf_wfn.Ca())
Cb = np.asarray(scf_wfn.Cb())
C = np.block([[Ca, np.zeros_like(Cb)], [np.zeros_like(Ca), Cb]])
# Get the two electron integrals using MintsHelper
Ints = np.asarray(mints.ao_eri())
def spin_block_tei(I):
"""
Function that spin blocks two-electron integrals
Using np.kron, we project I into the space of the 2x2 identity, tranpose the result
and project into the space of the 2x2 identity again. This doubles the size of each axis.
The result is our two electron integral tensor in the spin orbital form.
"""
identity = np.eye(2)
I = np.kron(identity, I)
return np.kron(identity, I.T)
# Spin-block the two electron integral array
I_spinblock = spin_block_tei(Ints)
# Converts chemist's notation to physicist's notation, and antisymmetrize
# (pq | rs) ---> <pr | qs>
# Physicist's notation
tmp = I_spinblock.transpose(0, 2, 1, 3)
# Antisymmetrize:
# <pr||qs> = <pr | qs> - <pr | sq>
gao = tmp - tmp.transpose(0, 1, 3, 2)
gmo = np.einsum(
'pQRS, pP -> PQRS',
np.einsum(
'pqRS, qQ -> pQRS',
np.einsum('pqrS, rR -> pqRS',
np.einsum('pqrs, sS -> pqrS', gao, C), C), C), C)
# -------- 0-body term:
Hamiltonian_0body = E_nucl
# -------- 1-body term:
# Ca*
# Build core Hamiltonian
T = np.asarray(mints.ao_kinetic())
V = np.asarray(mints.ao_potential())
H_core_ao = T + V
# -- check which one more efficient (matmul vs einsum)
# H_core_mo = np.matmul(Ca.T,np.matmul(H_core_ao,Ca)))
H_core_mo = np.einsum('ij, jk, kl -> il', Ca.T, H_core_ao, Ca)
H_core_mo_alpha = H_core_mo
H_core_mo_beta = H_core_mo
# ---- this version breaks is we permuted SCF eigvecs
# Hamiltonian_1body = np.block([
# [ H_core_mo_alpha , np.zeros_like(H_core_mo_alpha)],
# [np.zeros_like(H_core_mo_beta) , H_core_mo_beta ]])
#
# --- th is version is safer than above (H_1b is permutted correctly if eigvecs are permutted)
Hamiltonian_1body_ao = np.block([[H_core_ao,
np.zeros_like(H_core_ao)],
[np.zeros_like(H_core_ao),
H_core_ao]])
Hamiltonian_1body = np.einsum('ij, jk, kl -> il', C.T,
Hamiltonian_1body_ao, C)
Hamiltonian_2body = gmo
if 'frozen-spin-orbitals' in inputParams and 'active-spin-orbitals' in inputParams:
MSO_frozen_list = inputParams['frozen-spin-orbitals']
MSO_active_list = inputParams['active-spin-orbitals']
n_frozen = len(MSO_frozen_list)
n_active = len(MSO_active_list)
else:
MSO_frozen_list = []
MSO_active_list = range(Hamiltonian_1body.shape[0])
n_frozen = 0
n_active = len(MSO_active_list)
# ----- 0-body frozen-core:
Hamiltonian_fc_0body = E_nucl
for a in range(n_frozen):
ia = MSO_frozen_list[a]
Hamiltonian_fc_0body += Hamiltonian_1body[ia, ia]
for b in range(a):
ib = MSO_frozen_list[b]
Hamiltonian_fc_0body += gmo[ia, ib, ia, ib]
f_str = str(Hamiltonian_fc_0body)
pos_or_neg = lambda x: ' + ' if x > 0. else ' - '
# --- 1-body frozen-core:
Hamiltonian_fc_1body = np.zeros((n_active, n_active))
Hamiltonian_fc_1body_tmp = np.zeros((n_active, n_active))
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
Hamiltonian_fc_1body[p, q] = Hamiltonian_1body[ip, iq]
#Hamiltonian_fc_1body_tmp[p,q] = Hamiltonian_1body[ip,iq]
for a in range(n_frozen):
ia = MSO_frozen_list[a]
Hamiltonian_fc_1body[p, q] += gmo[ia, ip, ia, iq]
if abs(Hamiltonian_fc_1body[p, q]) > 1e-12:
f_str += pos_or_neg(Hamiltonian_fc_1body[p, q]) + str(
abs(Hamiltonian_fc_1body[p, q])) + ' ' + str(
p) + '^ ' + str(q)
# ------- 2-body frozen-core:
Hamiltonian_fc_2body = np.zeros(
(n_active, n_active, n_active, n_active))
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
for r in range(n_active):
ir = MSO_active_list[r]
for ss in range(n_active):
iss = MSO_active_list[ss]
#Hamiltonian_fc_2body[p,q,r,ss]= 0.25* gmo[ip,iq,ir,iss]
Hamiltonian_fc_2body[p, q, r, ss] = gmo[ip, iq, ir,
iss]
#Hamiltonian_fc_2body[p,q,r,ss]= 0.25* gmo[ip,iq,iss,ir]
Hamiltonian_fc_2body_tmp = 0.25 * Hamiltonian_fc_2body.transpose(
0, 1, 3, 2)
for p in range(n_active):
ip = MSO_active_list[p]
for q in range(n_active):
iq = MSO_active_list[q]
for r in range(n_active):
ir = MSO_active_list[r]
for ss in range(n_active):
if abs(Hamiltonian_fc_2body_tmp[p, q, r, ss]) > 1e-12:
f_str += pos_or_neg(
Hamiltonian_fc_2body_tmp[p, q, r, ss]) + str(
abs(Hamiltonian_fc_2body_tmp[p, q, r, ss])
) + ' ' + str(p) + '^ ' + str(q) + '^ ' + str(
r) + ' ' + str(ss)
self.observable = xacc.getObservable('fermion', f_str)
self.asPauli = xacc.transformToPauli('jw', self.observable)
import xacc
# This example demonstrates how one might create
# a new XACC InstructionVisitor in Python,
# this demo shows a Visitor that counts the
# number of each gate seen in the IR Tree.
H = xacc.getObservable('pauli', '')
for i,j in [[0,1], [1,2], [2,0]]:
H += 0.5 * xacc.getObservable('pauli', '1.0 I - Z{} Z{}'.format(i,j))
qaoa_ansatz = xacc.createComposite('qaoa')
qaoa_ansatz.expand({'nbQubits':H.nBits(),
'nbSteps':1,
'cost-ham':H,
'parameter-scheme':'Standard'})
print(qaoa_ansatz.toString())
class CountGatesOfTypePyVisitor(xacc.quantum.AllGateVisitor):
def __init__(self):
xacc.quantum.AllGateVisitor.__init__(self)
self.count_dict = {}
def visit(self, node):
if node.name() in self.count_dict:
self.count_dict[node.name()] += 1
else:
self.count_dict[node.name()] = 1
my_visitor = CountGatesOfTypePyVisitor()
def generate(self, inputParams):
src = """-159.505
- 0.714932 0^ 0
+ 0.091683 0^ 1
+ 0.091683 1^ 0
+ 0.173443 1^ 1
- 0.714932 2^ 2
+ 0.091683 2^ 3
+ 0.091683 3^ 2
+ 0.173443 3^ 3
- 0.0816923 0^ 1^ 0 1
+ 0.0816923 0^ 1^ 1 0
- 0.158901 0^ 2^ 0 2
+ 0.0229208 0^ 2^ 0 3
+ 0.0229208 0^ 2^ 1 2
- 0.0202421 0^ 2^ 1 3
+ 0.158901 0^ 2^ 2 0
- 0.0229208 0^ 2^ 2 1
- 0.0229208 0^ 2^ 3 0
+ 0.0202421 0^ 2^ 3 1
+ 0.0229208 0^ 3^ 0 2
- 0.101934 0^ 3^ 0 3
- 0.0202421 0^ 3^ 1 2
- 0.00944179 0^ 3^ 1 3
- 0.0229208 0^ 3^ 2 0
+ 0.0202421 0^ 3^ 2 1
+ 0.101934 0^ 3^ 3 0
+ 0.00944179 0^ 3^ 3 1
+ 0.0816923 1^ 0^ 0 1
- 0.0816923 1^ 0^ 1 0
+ 0.0229208 1^ 2^ 0 2
- 0.0202421 1^ 2^ 0 3
- 0.101934 1^ 2^ 1 2
- 0.00944179 1^ 2^ 1 3
- 0.0229208 1^ 2^ 2 0
+ 0.101934 1^ 2^ 2 1
+ 0.0202421 1^ 2^ 3 0
+ 0.00944179 1^ 2^ 3 1
- 0.0202421 1^ 3^ 0 2
- 0.00944179 1^ 3^ 0 3
- 0.00944179 1^ 3^ 1 2
- 0.11747 1^ 3^ 1 3
+ 0.0202421 1^ 3^ 2 0
+ 0.00944179 1^ 3^ 2 1
+ 0.00944179 1^ 3^ 3 0
+ 0.11747 1^ 3^ 3 1
+ 0.158901 2^ 0^ 0 2
- 0.0229208 2^ 0^ 0 3
- 0.0229208 2^ 0^ 1 2
+ 0.0202421 2^ 0^ 1 3
- 0.158901 2^ 0^ 2 0
+ 0.0229208 2^ 0^ 2 1
+ 0.0229208 2^ 0^ 3 0
- 0.0202421 2^ 0^ 3 1
- 0.0229208 2^ 1^ 0 2
+ 0.0202421 2^ 1^ 0 3
+ 0.101934 2^ 1^ 1 2
+ 0.00944179 2^ 1^ 1 3
+ 0.0229208 2^ 1^ 2 0
- 0.101934 2^ 1^ 2 1
- 0.0202421 2^ 1^ 3 0
- 0.00944179 2^ 1^ 3 1
- 0.0816923 2^ 3^ 2 3
+ 0.0816923 2^ 3^ 3 2
- 0.0229208 3^ 0^ 0 2
+ 0.101934 3^ 0^ 0 3
+ 0.0202421 3^ 0^ 1 2
+ 0.00944179 3^ 0^ 1 3
+ 0.0229208 3^ 0^ 2 0
- 0.0202421 3^ 0^ 2 1
- 0.101934 3^ 0^ 3 0
- 0.00944179 3^ 0^ 3 1
+ 0.0202421 3^ 1^ 0 2
+ 0.00944179 3^ 1^ 0 3
+ 0.00944179 3^ 1^ 1 2
+ 0.11747 3^ 1^ 1 3
- 0.0202421 3^ 1^ 2 0
- 0.00944179 3^ 1^ 2 1
- 0.00944179 3^ 1^ 3 0
- 0.11747 3^ 1^ 3 1
+ 0.0816923 3^ 2^ 2 3
- 0.0816923 3^ 2^ 3 2
"""
inputParams['rdm-source'] = src
return xacc.getObservable("fermion", src)
import xacc
import numpy as np
qpu = xacc.getAccelerator('qpp')
ham = xacc.getObservable('pauli', '-5.0 - 0.5 Z0 + 1.0 Z0Z1')
nbQubits = 2
steps = 1
buffer = xacc.qalloc(nbQubits)
nbTotalParams = 4
# The optimizer: nlopt
opt = xacc.getOptimizer('nlopt', { 'initial-parameters': np.random.rand(nbTotalParams)} )
# Create the QAOA algorithm
qaoa = xacc.getAlgorithm('QAOA', {
'accelerator': qpu,
'observable': ham,
'optimizer': opt,
'steps': steps,
'parameter-scheme': 'Extend'})
# Run
result = qaoa.execute(buffer)
print('Min value = ', buffer.getInformation('opt-val'))
print('Opt-params = ', buffer.getInformation('opt-params'))
# Get the circuit
qaoa_ansatz_std = xacc.createComposite('qaoa')
qaoa_ansatz_std.expand({'nbQubits': nbQubits, 'nbSteps': steps, 'cost-ham': ham,
'parameter-scheme':'Extend'})
print('Extend parameterized QAOA circuit:')
print(qaoa_ansatz_std)
def generate(self, inputParams):
src = """-159.505
- 0.714932 0^ 0
+ 0.101963 0^ 1
+ 0.091683 0^ 2
+ 0.101963 1^ 0
- 0.079975 1^ 1
- 0.123414 1^ 2
+ 0.091683 2^ 0
- 0.123414 2^ 1
+ 0.173443 2^ 2
- 0.714932 3^ 3
+ 0.101963 3^ 4
+ 0.091683 3^ 5
+ 0.101963 4^ 3
- 0.079975 4^ 4
- 0.123414 4^ 5
+ 0.091683 5^ 3
- 0.123414 5^ 4
+ 0.173443 5^ 5
- 0.0597498 0^ 1^ 0 1
- 0.00895403 0^ 1^ 0 2
+ 0.0597498 0^ 1^ 1 0
+ 0.0140516 0^ 1^ 1 2
+ 0.00895403 0^ 1^ 2 0
- 0.0140516 0^ 1^ 2 1
- 0.00895403 0^ 2^ 0 1
- 0.0816923 0^ 2^ 0 2
+ 0.00895403 0^ 2^ 1 0
- 0.00421023 0^ 2^ 1 2
+ 0.0816923 0^ 2^ 2 0
+ 0.00421023 0^ 2^ 2 1
- 0.158901 0^ 3^ 0 3
+ 0.0254908 0^ 3^ 0 4
+ 0.0229208 0^ 3^ 0 5
+ 0.0254908 0^ 3^ 1 3
- 0.0112333 0^ 3^ 1 4
- 0.0129455 0^ 3^ 1 5
+ 0.0229208 0^ 3^ 2 3
- 0.0129455 0^ 3^ 2 4
- 0.0202421 0^ 3^ 2 5
+ 0.158901 0^ 3^ 3 0
- 0.0254908 0^ 3^ 3 1
- 0.0229208 0^ 3^ 3 2
- 0.0254908 0^ 3^ 4 0
+ 0.0112333 0^ 3^ 4 1
+ 0.0129455 0^ 3^ 4 2
- 0.0229208 0^ 3^ 5 0
+ 0.0129455 0^ 3^ 5 1
+ 0.0202421 0^ 3^ 5 2
+ 0.0254908 0^ 4^ 0 3
- 0.0709831 0^ 4^ 0 4
- 0.0218996 0^ 4^ 0 5
- 0.0112333 0^ 4^ 1 3
- 0.00883391 0^ 4^ 1 4
+ 0.00677708 0^ 4^ 1 5
- 0.0129455 0^ 4^ 2 3
- 0.0072745 0^ 4^ 2 4
+ 0.00277645 0^ 4^ 2 5
- 0.0254908 0^ 4^ 3 0
+ 0.0112333 0^ 4^ 3 1
+ 0.0129455 0^ 4^ 3 2
+ 0.0709831 0^ 4^ 4 0
+ 0.00883391 0^ 4^ 4 1
+ 0.0072745 0^ 4^ 4 2
+ 0.0218996 0^ 4^ 5 0
- 0.00677708 0^ 4^ 5 1
- 0.00277645 0^ 4^ 5 2
+ 0.0229208 0^ 5^ 0 3
- 0.0218996 0^ 5^ 0 4
- 0.101934 0^ 5^ 0 5
- 0.0129455 0^ 5^ 1 3
+ 0.00677708 0^ 5^ 1 4
- 0.00143379 0^ 5^ 1 5
- 0.0202421 0^ 5^ 2 3
+ 0.00277645 0^ 5^ 2 4
- 0.00944179 0^ 5^ 2 5
- 0.0229208 0^ 5^ 3 0
+ 0.0129455 0^ 5^ 3 1
+ 0.0202421 0^ 5^ 3 2
+ 0.0218996 0^ 5^ 4 0
- 0.00677708 0^ 5^ 4 1
- 0.00277645 0^ 5^ 4 2
+ 0.101934 0^ 5^ 5 0
+ 0.00143379 0^ 5^ 5 1
+ 0.00944179 0^ 5^ 5 2
+ 0.0597498 1^ 0^ 0 1
+ 0.00895403 1^ 0^ 0 2
- 0.0597498 1^ 0^ 1 0
- 0.0140516 1^ 0^ 1 2
- 0.00895403 1^ 0^ 2 0
+ 0.0140516 1^ 0^ 2 1
+ 0.0140516 1^ 2^ 0 1
- 0.00421023 1^ 2^ 0 2
- 0.0140516 1^ 2^ 1 0
- 0.0821053 1^ 2^ 1 2
+ 0.00421023 1^ 2^ 2 0
+ 0.0821053 1^ 2^ 2 1
+ 0.0254908 1^ 3^ 0 3
- 0.0112333 1^ 3^ 0 4
- 0.0129455 1^ 3^ 0 5
- 0.0709831 1^ 3^ 1 3
- 0.00883391 1^ 3^ 1 4
- 0.0072745 1^ 3^ 1 5
- 0.0218996 1^ 3^ 2 3
+ 0.00677708 1^ 3^ 2 4
+ 0.00277645 1^ 3^ 2 5
- 0.0254908 1^ 3^ 3 0
+ 0.0709831 1^ 3^ 3 1
+ 0.0218996 1^ 3^ 3 2
+ 0.0112333 1^ 3^ 4 0
+ 0.00883391 1^ 3^ 4 1
- 0.00677708 1^ 3^ 4 2
+ 0.0129455 1^ 3^ 5 0
+ 0.0072745 1^ 3^ 5 1
- 0.00277645 1^ 3^ 5 2
- 0.0112333 1^ 4^ 0 3
- 0.00883391 1^ 4^ 0 4
+ 0.00677708 1^ 4^ 0 5
- 0.00883391 1^ 4^ 1 3
- 0.110544 1^ 4^ 1 4
+ 0.0138874 1^ 4^ 1 5
+ 0.00677708 1^ 4^ 2 3
+ 0.0138874 1^ 4^ 2 4
- 0.0165034 1^ 4^ 2 5
+ 0.0112333 1^ 4^ 3 0
+ 0.00883391 1^ 4^ 3 1
- 0.00677708 1^ 4^ 3 2
+ 0.00883391 1^ 4^ 4 0
+ 0.110544 1^ 4^ 4 1
- 0.0138874 1^ 4^ 4 2
- 0.00677708 1^ 4^ 5 0
- 0.0138874 1^ 4^ 5 1
+ 0.0165034 1^ 4^ 5 2
- 0.0129455 1^ 5^ 0 3
+ 0.00677708 1^ 5^ 0 4
- 0.00143379 1^ 5^ 0 5
- 0.0072745 1^ 5^ 1 3
+ 0.0138874 1^ 5^ 1 4
- 0.0986087 1^ 5^ 1 5
+ 0.00277645 1^ 5^ 2 3
- 0.0165034 1^ 5^ 2 4
- 0.00369882 1^ 5^ 2 5
+ 0.0129455 1^ 5^ 3 0
+ 0.0072745 1^ 5^ 3 1
- 0.00277645 1^ 5^ 3 2
- 0.00677708 1^ 5^ 4 0
- 0.0138874 1^ 5^ 4 1
+ 0.0165034 1^ 5^ 4 2
+ 0.00143379 1^ 5^ 5 0
+ 0.0986087 1^ 5^ 5 1
+ 0.00369882 1^ 5^ 5 2
+ 0.00895403 2^ 0^ 0 1
+ 0.0816923 2^ 0^ 0 2
- 0.00895403 2^ 0^ 1 0
+ 0.00421023 2^ 0^ 1 2
- 0.0816923 2^ 0^ 2 0
- 0.00421023 2^ 0^ 2 1
- 0.0140516 2^ 1^ 0 1
+ 0.00421023 2^ 1^ 0 2
+ 0.0140516 2^ 1^ 1 0
+ 0.0821053 2^ 1^ 1 2
- 0.00421023 2^ 1^ 2 0
- 0.0821053 2^ 1^ 2 1
+ 0.0229208 2^ 3^ 0 3
- 0.0129455 2^ 3^ 0 4
- 0.0202421 2^ 3^ 0 5
- 0.0218996 2^ 3^ 1 3
+ 0.00677708 2^ 3^ 1 4
+ 0.00277645 2^ 3^ 1 5
- 0.101934 2^ 3^ 2 3
- 0.00143379 2^ 3^ 2 4
- 0.00944179 2^ 3^ 2 5
- 0.0229208 2^ 3^ 3 0
+ 0.0218996 2^ 3^ 3 1
+ 0.101934 2^ 3^ 3 2
+ 0.0129455 2^ 3^ 4 0
- 0.00677708 2^ 3^ 4 1
+ 0.00143379 2^ 3^ 4 2
+ 0.0202421 2^ 3^ 5 0
- 0.00277645 2^ 3^ 5 1
+ 0.00944179 2^ 3^ 5 2
- 0.0129455 2^ 4^ 0 3
- 0.0072745 2^ 4^ 0 4
+ 0.00277645 2^ 4^ 0 5
+ 0.00677708 2^ 4^ 1 3
+ 0.0138874 2^ 4^ 1 4
- 0.0165034 2^ 4^ 1 5
- 0.00143379 2^ 4^ 2 3
- 0.0986087 2^ 4^ 2 4
- 0.00369882 2^ 4^ 2 5
+ 0.0129455 2^ 4^ 3 0
- 0.00677708 2^ 4^ 3 1
+ 0.00143379 2^ 4^ 3 2
+ 0.0072745 2^ 4^ 4 0
- 0.0138874 2^ 4^ 4 1
+ 0.0986087 2^ 4^ 4 2
- 0.00277645 2^ 4^ 5 0
+ 0.0165034 2^ 4^ 5 1
+ 0.00369882 2^ 4^ 5 2
- 0.0202421 2^ 5^ 0 3
+ 0.00277645 2^ 5^ 0 4
- 0.00944179 2^ 5^ 0 5
+ 0.00277645 2^ 5^ 1 3
- 0.0165034 2^ 5^ 1 4
- 0.00369882 2^ 5^ 1 5
- 0.00944179 2^ 5^ 2 3
- 0.00369882 2^ 5^ 2 4
- 0.11747 2^ 5^ 2 5
+ 0.0202421 2^ 5^ 3 0
- 0.00277645 2^ 5^ 3 1
+ 0.00944179 2^ 5^ 3 2
- 0.00277645 2^ 5^ 4 0
+ 0.0165034 2^ 5^ 4 1
+ 0.00369882 2^ 5^ 4 2
+ 0.00944179 2^ 5^ 5 0
+ 0.00369882 2^ 5^ 5 1
+ 0.11747 2^ 5^ 5 2
+ 0.158901 3^ 0^ 0 3
- 0.0254908 3^ 0^ 0 4
- 0.0229208 3^ 0^ 0 5
- 0.0254908 3^ 0^ 1 3
+ 0.0112333 3^ 0^ 1 4
+ 0.0129455 3^ 0^ 1 5
- 0.0229208 3^ 0^ 2 3
+ 0.0129455 3^ 0^ 2 4
+ 0.0202421 3^ 0^ 2 5
- 0.158901 3^ 0^ 3 0
+ 0.0254908 3^ 0^ 3 1
+ 0.0229208 3^ 0^ 3 2
+ 0.0254908 3^ 0^ 4 0
- 0.0112333 3^ 0^ 4 1
- 0.0129455 3^ 0^ 4 2
+ 0.0229208 3^ 0^ 5 0
- 0.0129455 3^ 0^ 5 1
- 0.0202421 3^ 0^ 5 2
- 0.0254908 3^ 1^ 0 3
+ 0.0112333 3^ 1^ 0 4
+ 0.0129455 3^ 1^ 0 5
+ 0.0709831 3^ 1^ 1 3
+ 0.00883391 3^ 1^ 1 4
+ 0.0072745 3^ 1^ 1 5
+ 0.0218996 3^ 1^ 2 3
- 0.00677708 3^ 1^ 2 4
- 0.00277645 3^ 1^ 2 5
+ 0.0254908 3^ 1^ 3 0
- 0.0709831 3^ 1^ 3 1
- 0.0218996 3^ 1^ 3 2
- 0.0112333 3^ 1^ 4 0
- 0.00883391 3^ 1^ 4 1
+ 0.00677708 3^ 1^ 4 2
- 0.0129455 3^ 1^ 5 0
- 0.0072745 3^ 1^ 5 1
+ 0.00277645 3^ 1^ 5 2
- 0.0229208 3^ 2^ 0 3
+ 0.0129455 3^ 2^ 0 4
+ 0.0202421 3^ 2^ 0 5
+ 0.0218996 3^ 2^ 1 3
- 0.00677708 3^ 2^ 1 4
- 0.00277645 3^ 2^ 1 5
+ 0.101934 3^ 2^ 2 3
+ 0.00143379 3^ 2^ 2 4
+ 0.00944179 3^ 2^ 2 5
+ 0.0229208 3^ 2^ 3 0
- 0.0218996 3^ 2^ 3 1
- 0.101934 3^ 2^ 3 2
- 0.0129455 3^ 2^ 4 0
+ 0.00677708 3^ 2^ 4 1
- 0.00143379 3^ 2^ 4 2
- 0.0202421 3^ 2^ 5 0
+ 0.00277645 3^ 2^ 5 1
- 0.00944179 3^ 2^ 5 2
- 0.0597498 3^ 4^ 3 4
- 0.00895403 3^ 4^ 3 5
+ 0.0597498 3^ 4^ 4 3
+ 0.0140516 3^ 4^ 4 5
+ 0.00895403 3^ 4^ 5 3
- 0.0140516 3^ 4^ 5 4
- 0.00895403 3^ 5^ 3 4
- 0.0816923 3^ 5^ 3 5
+ 0.00895403 3^ 5^ 4 3
- 0.00421023 3^ 5^ 4 5
+ 0.0816923 3^ 5^ 5 3
+ 0.00421023 3^ 5^ 5 4
- 0.0254908 4^ 0^ 0 3
+ 0.0709831 4^ 0^ 0 4
+ 0.0218996 4^ 0^ 0 5
+ 0.0112333 4^ 0^ 1 3
+ 0.00883391 4^ 0^ 1 4
- 0.00677708 4^ 0^ 1 5
+ 0.0129455 4^ 0^ 2 3
+ 0.0072745 4^ 0^ 2 4
- 0.00277645 4^ 0^ 2 5
+ 0.0254908 4^ 0^ 3 0
- 0.0112333 4^ 0^ 3 1
- 0.0129455 4^ 0^ 3 2
- 0.0709831 4^ 0^ 4 0
- 0.00883391 4^ 0^ 4 1
- 0.0072745 4^ 0^ 4 2
- 0.0218996 4^ 0^ 5 0
+ 0.00677708 4^ 0^ 5 1
+ 0.00277645 4^ 0^ 5 2
+ 0.0112333 4^ 1^ 0 3
+ 0.00883391 4^ 1^ 0 4
- 0.00677708 4^ 1^ 0 5
+ 0.00883391 4^ 1^ 1 3
+ 0.110544 4^ 1^ 1 4
- 0.0138874 4^ 1^ 1 5
- 0.00677708 4^ 1^ 2 3
- 0.0138874 4^ 1^ 2 4
+ 0.0165034 4^ 1^ 2 5
- 0.0112333 4^ 1^ 3 0
- 0.00883391 4^ 1^ 3 1
+ 0.00677708 4^ 1^ 3 2
- 0.00883391 4^ 1^ 4 0
- 0.110544 4^ 1^ 4 1
+ 0.0138874 4^ 1^ 4 2
+ 0.00677708 4^ 1^ 5 0
+ 0.0138874 4^ 1^ 5 1
- 0.0165034 4^ 1^ 5 2
+ 0.0129455 4^ 2^ 0 3
+ 0.0072745 4^ 2^ 0 4
- 0.00277645 4^ 2^ 0 5
- 0.00677708 4^ 2^ 1 3
- 0.0138874 4^ 2^ 1 4
+ 0.0165034 4^ 2^ 1 5
+ 0.00143379 4^ 2^ 2 3
+ 0.0986087 4^ 2^ 2 4
+ 0.00369882 4^ 2^ 2 5
- 0.0129455 4^ 2^ 3 0
+ 0.00677708 4^ 2^ 3 1
- 0.00143379 4^ 2^ 3 2
- 0.0072745 4^ 2^ 4 0
+ 0.0138874 4^ 2^ 4 1
- 0.0986087 4^ 2^ 4 2
+ 0.00277645 4^ 2^ 5 0
- 0.0165034 4^ 2^ 5 1
- 0.00369882 4^ 2^ 5 2
+ 0.0597498 4^ 3^ 3 4
+ 0.00895403 4^ 3^ 3 5
- 0.0597498 4^ 3^ 4 3
- 0.0140516 4^ 3^ 4 5
- 0.00895403 4^ 3^ 5 3
+ 0.0140516 4^ 3^ 5 4
+ 0.0140516 4^ 5^ 3 4
- 0.00421023 4^ 5^ 3 5
- 0.0140516 4^ 5^ 4 3
- 0.0821053 4^ 5^ 4 5
+ 0.00421023 4^ 5^ 5 3
+ 0.0821053 4^ 5^ 5 4
- 0.0229208 5^ 0^ 0 3
+ 0.0218996 5^ 0^ 0 4
+ 0.101934 5^ 0^ 0 5
+ 0.0129455 5^ 0^ 1 3
- 0.00677708 5^ 0^ 1 4
+ 0.00143379 5^ 0^ 1 5
+ 0.0202421 5^ 0^ 2 3
- 0.00277645 5^ 0^ 2 4
+ 0.00944179 5^ 0^ 2 5
+ 0.0229208 5^ 0^ 3 0
- 0.0129455 5^ 0^ 3 1
- 0.0202421 5^ 0^ 3 2
- 0.0218996 5^ 0^ 4 0
+ 0.00677708 5^ 0^ 4 1
+ 0.00277645 5^ 0^ 4 2
- 0.101934 5^ 0^ 5 0
- 0.00143379 5^ 0^ 5 1
- 0.00944179 5^ 0^ 5 2
+ 0.0129455 5^ 1^ 0 3
- 0.00677708 5^ 1^ 0 4
+ 0.00143379 5^ 1^ 0 5
+ 0.0072745 5^ 1^ 1 3
- 0.0138874 5^ 1^ 1 4
+ 0.0986087 5^ 1^ 1 5
- 0.00277645 5^ 1^ 2 3
+ 0.0165034 5^ 1^ 2 4
+ 0.00369882 5^ 1^ 2 5
- 0.0129455 5^ 1^ 3 0
- 0.0072745 5^ 1^ 3 1
+ 0.00277645 5^ 1^ 3 2
+ 0.00677708 5^ 1^ 4 0
+ 0.0138874 5^ 1^ 4 1
- 0.0165034 5^ 1^ 4 2
- 0.00143379 5^ 1^ 5 0
- 0.0986087 5^ 1^ 5 1
- 0.00369882 5^ 1^ 5 2
+ 0.0202421 5^ 2^ 0 3
- 0.00277645 5^ 2^ 0 4
+ 0.00944179 5^ 2^ 0 5
- 0.00277645 5^ 2^ 1 3
+ 0.0165034 5^ 2^ 1 4
+ 0.00369882 5^ 2^ 1 5
+ 0.00944179 5^ 2^ 2 3
+ 0.00369882 5^ 2^ 2 4
+ 0.11747 5^ 2^ 2 5
- 0.0202421 5^ 2^ 3 0
+ 0.00277645 5^ 2^ 3 1
- 0.00944179 5^ 2^ 3 2
+ 0.00277645 5^ 2^ 4 0
- 0.0165034 5^ 2^ 4 1
- 0.00369882 5^ 2^ 4 2
- 0.00944179 5^ 2^ 5 0
- 0.00369882 5^ 2^ 5 1
- 0.11747 5^ 2^ 5 2
+ 0.00895403 5^ 3^ 3 4
+ 0.0816923 5^ 3^ 3 5
- 0.00895403 5^ 3^ 4 3
+ 0.00421023 5^ 3^ 4 5
- 0.0816923 5^ 3^ 5 3
- 0.00421023 5^ 3^ 5 4
- 0.0140516 5^ 4^ 3 4
+ 0.00421023 5^ 4^ 3 5
+ 0.0140516 5^ 4^ 4 3
+ 0.0821053 5^ 4^ 4 5
- 0.00421023 5^ 4^ 5 3
- 0.0821053 5^ 4^ 5 4
"""
return xacc.getObservable("fermion", src)
import xacc
# Get access to the desired QPU and
# allocate some qubits to run on
qpu = xacc.getAccelerator('tnqvm', {'vqe-mode': True})
buffer = xacc.qalloc(4)
geom = '''
H 0.000000 0.0 0.0
H 0.0 0.0 .7474
'''
H = xacc.getObservable('pyscf', {'basis': 'sto-3g', 'geometry': geom})
@xacc.qpu(algo='vqe', accelerator=qpu, observable=H)
def ansatz(q, x):
X(q[0])
X(q[2])
ucc1(q, x[0])
ansatz(buffer, 0.0)
print('Energy = ', buffer.getInformation('opt-val'))
print('Opt Angles = ', buffer.getInformation('opt-params'))
(-0.174072892497,-0) 1^ 3^ 1 3 + (-0.0454063328691,-0) 0^ 2^ 1 3 +
(0.120200490713,0) 0^ 1^ 1 0 + (0.0454063328691,0) 0^ 2^ 3 1 +
(0.174072892497,0) 1^ 3^ 3 1 + (0.165606823582,0) 2^ 1^ 1 2 +
(-0.0454063328691,-0) 2^ 1^ 3 0 + (-0.120200490713,-0) 2^ 3^ 2 3 +
(0.120200490713,0) 2^ 3^ 3 2 + (-0.168335986252,-0) 0^ 2^ 0 2 +
(0.120200490713,0) 3^ 2^ 2 3 + (-0.120200490713,-0) 3^ 2^ 3 2 +
(0.0454063328691,0) 1^ 3^ 2 0 + (-1.2488468038,-0) 0^ 0 +
(0.0454063328691,0) 3^ 1^ 0 2 + (-0.168335986252,-0) 2^ 0^ 2 0 +
(0.165606823582,0) 3^ 0^ 0 3 + (-0.0454063328691,-0) 2^ 0^ 3 1 +
(0.0454063328691,0) 2^ 0^ 1 3 + (-1.2488468038,-0) 2^ 2 +
(0.0454063328691,0) 2^ 1^ 0 3 + (0.174072892497,0) 3^ 1^ 1 3 +
(-0.479677813134,-0) 1^ 1 + (-0.174072892497,-0) 3^ 1^ 3 1 +
(0.0454063328691,0) 3^ 0^ 1 2 + (-0.165606823582,-0) 3^ 0^ 3 0 +
(0.0454063328691,0) 0^ 3^ 2 1 + (-0.165606823582,-0) 2^ 1^ 2 1 +
(-0.120200490713,-0) 0^ 1^ 0 1 + (-0.120200490713,-0) 1^ 0^ 1 0 + (0.7080240981,0)
'''
H = xacc.getObservable('fermion', opstr)
adapt = xacc.getAlgorithm(
'adapt', {
'accelerator': qpu,
'optimizer': optimizer,
'observable': H,
'n-electrons': 2,
'maxiter': 2,
'sub-algorithm': 'vqe',
'pool': 'qubit-pool'
})
# execute
adapt.execute(buffer)
# and allocate some qubits for execution on each
qpu = xacc.getAccelerator('aer', {
'shots': 1024,
'backend': 'ibmq_johannesburg',
'readout_error': True
})
tnqvm = xacc.getAccelerator('tnqvm')
buffer = xacc.qalloc(2)
tnqvmBuffer = xacc.qalloc(2)
# Turn on readout error correction by decorating
# the local-ibm accelerator
qpu = xacc.getAcceleratorDecorator('ro-error', qpu)
# Construct the Hamiltonian
ham = xacc.getObservable(
'pauli', '5.907 - 2.1433 X0X1 - 2.1433 Y0Y1 + .21829 Z0 - 6.125 Z1')
# Define the ansatz and decorate it to indicate
# you'd like to run VQE
@xacc.qpu(algo='energy', accelerator=qpu, observable=ham)
def ansatz(buffer, t0):
X(buffer[0])
Ry(buffer[1], t0)
CNOT(buffer[1], buffer[0])
# Execute angle sweep on Local-IBM
[ansatz(buffer, t) for t in np.linspace(-np.pi, np.pi, nAngles)]
# Get theoretical values by overriding the
import xacc
opstr = '''(0.174073,0) Z2 Z3 +
(0.1202,0) Z1 Z3 +
(0.165607,0) Z1 Z2 +
(0.165607,0) Z0 Z3 +
(0.1202,0) Z0 Z2 +
(-0.0454063,0) Y0 Y1 X2 X3 +
(-0.220041,0) Z3 +
(-0.106477,0) +
(0.17028,0) Z0 +
(-0.220041,0) Z2 +
(0.17028,0) Z1 +
(-0.0454063,0) X0 X1 Y2 Y3 +
(0.0454063,0) X0 Y1 Y2 X3 +
(0.168336,0) Z0 Z1 +
(0.0454063,0) Y0 X1 X2 Y3'''
op = xacc.getObservable('pauli', opstr)
qpu = xacc.getAccelerator('tnqvm')
@xacc.qpu(algo='vqe', accelerator=qpu, observable=op)
def ansatz_vqe(q, t0, t1):
uccsd(q, {"ne": 2, "nq": 4})
print(ansatz_vqe.getFunction().toString())
buffer = xacc.qalloc(4)
ansatz_vqe(buffer, 0., 0.)
def generate(self, inputParams):
return xacc.getObservable(
'pauli',
'5.907 - 2.1433 X0X1 - 2.1433 Y0Y1 + .21829 Z0 - 6.125 Z1')
