def convert_to_wpauli_list(term):
if term[0] == complex(0):
separated_ham = 0 * WeightedPauliOperator.from_list(
paulis=[Pauli.from_label('I' * num_qubits)])
else:
separated_ham = WeightedPauliOperator.from_list([term[1]], [term[0]])
return separated_ham
def Gen_rand_1_ham(num_terms, num_qubits):
wop = 0*WeightedPauliOperator.from_list(paulis = [Pauli.from_label('I'*num_qubits)])
ham = wop
for i in range(0,num_terms):
pauli = random_pauli(num_qubits)
wpauli = WeightedPauliOperator.from_list(paulis=[pauli], weights=[1.0])
ham = ham + wpauli
return ham
def Gen_rand_rand_ham(num_terms, num_qubits):
wop = 0*WeightedPauliOperator.from_list(paulis = [Pauli.from_label('I'*num_qubits)])
ham = wop
pauli_list = []
i = 0
while i < num_terms:
pauli = random_pauli(num_qubits)
if pauli_list.count(pauli) == 0:
wpauli = WeightedPauliOperator.from_list(paulis=[pauli], weights=[np.random.uniform(0,1)])
ham = ham + wpauli
pauli_list.append(pauli)
i = i+1
return ham
def test_negation_operator(self):
""" negation operator test """
paulis = [Pauli.from_label(x) for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']]
coeffs = [0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op1 = WeightedPauliOperator.from_list(paulis, coeffs)
coeffs = [-0.2, -0.6, -0.8, 0.2, 0.6, 0.8]
op2 = WeightedPauliOperator.from_list(paulis, coeffs)
self.assertNotEqual(op1, op2)
self.assertEqual(op1, -op2)
self.assertEqual(-op1, op2)
op1 = op1 * -1.0
self.assertEqual(op1, op2)
def split_into_paulis(ham):
ham_details = ham.print_details()
ham_list = ham_details.split('\n')
pauli_list = [0] * (len(ham_list) - 1
) #exclude last entry of ham list bc is just blank
name_list = [0] * (len(ham_list) - 1)
weight_list = [0] * (len(ham_list) - 1)
for counter in range(0, len(ham_list) - 1, 1):
pauli = Pauli.from_label(ham_list[counter][:4])
name_list[counter] = WeightedPauliOperator.from_list(
[pauli]).print_details()
weight_list[counter] = complex(ham_list[counter][6:-1])
pauli_list[counter] = WeightedPauliOperator.from_list([pauli])
return weight_list, pauli_list, name_list
def test_chop(self):
""" chop test """
paulis = [
Pauli.from_label(x)
for x in ['IIXX', 'ZZXX', 'ZZZZ', 'XXZZ', 'XXXX', 'IXXX']
]
coeffs = [0.2, 0.3, 0.4, 0.5, 0.6, 0.7]
op = WeightedPauliOperator.from_list(paulis, coeffs)
grouped_op = op_converter.to_tpb_grouped_weighted_pauli_operator(
op, TPBGroupedWeightedPauliOperator.sorted_grouping)
original_num_basis = len(grouped_op.basis)
chopped_grouped_op = grouped_op.chop(0.35, copy=True)
self.assertLessEqual(len(chopped_grouped_op.basis), 3)
self.assertLessEqual(len(chopped_grouped_op.basis), original_num_basis)
# ZZXX group is remove
for b, _ in chopped_grouped_op.basis:
self.assertFalse(b.to_label() == 'ZZXX')
chopped_grouped_op = grouped_op.chop(0.55, copy=True)
self.assertLessEqual(len(chopped_grouped_op.basis), 1)
self.assertLessEqual(len(chopped_grouped_op.basis), original_num_basis)
for b, _ in chopped_grouped_op.basis:
self.assertFalse(b.to_label() == 'ZZXX')
self.assertFalse(b.to_label() == 'ZZZZ')
self.assertFalse(b.to_label() == 'XXZZ')
def setUp(self):
super().setUp()
seed = 0
np.random.seed(seed)
aqua_globals.random_seed = seed
self.num_qubits = 3
paulis = [
Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ',
repeat=self.num_qubits)
]
weights = np.random.random(len(paulis))
self.qubit_op = WeightedPauliOperator.from_list(paulis, weights)
self.var_form = RYRZ(self.qubit_op.num_qubits, 1)
qasm_simulator = BasicAer.get_backend('qasm_simulator')
self.quantum_instance_qasm = QuantumInstance(qasm_simulator,
shots=65536,
seed_simulator=seed,
seed_transpiler=seed)
statevector_simulator = BasicAer.get_backend('statevector_simulator')
self.quantum_instance_statevector = QuantumInstance(
statevector_simulator,
shots=1,
seed_simulator=seed,
seed_transpiler=seed)
def setUp(self):
super().setUp()
seed = 0
aqua_globals.random_seed = seed
self.num_qubits = 3
paulis = [
Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ',
repeat=self.num_qubits)
]
weights = aqua_globals.random.random(len(paulis))
self.qubit_op = WeightedPauliOperator.from_list(paulis, weights)
warnings.filterwarnings('ignore', category=DeprecationWarning)
self.var_form = RYRZ(self.qubit_op.num_qubits, 1)
warnings.filterwarnings('always', category=DeprecationWarning)
qasm_simulator = BasicAer.get_backend('qasm_simulator')
self.quantum_instance_qasm = QuantumInstance(qasm_simulator,
shots=65536,
seed_simulator=seed,
seed_transpiler=seed)
statevector_simulator = BasicAer.get_backend('statevector_simulator')
self.quantum_instance_statevector = \
QuantumInstance(statevector_simulator, shots=1,
seed_simulator=seed, seed_transpiler=seed)
def output_dressed_ham(self):
i = 0
term_sums = [0] * 4**self.num_qubits
sum_term = self.zero_term
other_sum_term = self.zero_term
for term in self.ham_term_list:
for descendant in term['descendants']:
weight, pauli, name = split_into_paulis(descendant)
term_sums[int(base_4_map(
name[0]))] = np.real(term_sums[int(base_4_map(
name[0]))]) + np.real(weight[0] * self.constants[i])
other_sum_term = other_sum_term + np.real(
weight[0] * self.constants[i]) * pauli[0]
i = i + 1
for i, entry in enumerate(term_sums):
if abs(entry) > 0.000001:
pauli_num = quaternary(i)
pauli_name = create_term(pauli_num, self.num_qubits)
pauli = Pauli.from_label(pauli_name)
wpauli = WeightedPauliOperator.from_list(paulis=[pauli])
sum_term = entry * wpauli + sum_term
print(sum_term.print_details())
mat = to_matrix_operator(sum_term)
print(mat.print_details())
#mat_2 = to_matrix_operator(other_sum_term)
#print(mat_2.print_details())
print(term_sums)
def test_sorted_grouping(self):
"""Test with color grouping approach."""
num_qubits = 2
paulis = [
Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ', repeat=num_qubits)
]
weights = aqua_globals.random.random(len(paulis))
op = WeightedPauliOperator.from_list(paulis, weights)
grouped_op = op_converter.to_tpb_grouped_weighted_pauli_operator(
op, TPBGroupedWeightedPauliOperator.sorted_grouping)
# check all paulis are still existed.
for g_p in grouped_op.paulis:
passed = False
for pauli in op.paulis:
if pauli[1] == g_p[1]:
passed = pauli[0] == g_p[0]
break
self.assertTrue(
passed, "non-existed paulis in grouped_paulis: {}".format(
g_p[1].to_label()))
# check the number of basis of grouped
# one should be less than and equal to the original one.
self.assertGreaterEqual(len(op.basis), len(grouped_op.basis))
def test_simplify(self):
""" simplify test """
pauli_a = 'IXYZ'
pauli_b = 'IXYZ'
coeff_a = 0.5
coeff_b = -0.5
pauli_term_a = [coeff_a, Pauli.from_label(pauli_a)]
pauli_term_b = [coeff_b, Pauli.from_label(pauli_b)]
op_a = WeightedPauliOperator(paulis=[pauli_term_a])
op_b = WeightedPauliOperator(paulis=[pauli_term_b])
new_op = op_a + op_b
new_op.simplify()
self.assertEqual(0, len(new_op.paulis),
"{}".format(new_op.print_details()))
self.assertTrue(new_op.is_empty())
paulis = [
Pauli.from_label(x)
for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']
]
coeffs = [0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op1 = WeightedPauliOperator.from_list(paulis, coeffs)
for i, pauli in enumerate(paulis):
tmp_op = WeightedPauliOperator(paulis=[[-coeffs[i], pauli]])
op1 += tmp_op
op1.simplify()
self.assertEqual(len(paulis) - (i + 1), len(op1.paulis))
def test_chop_complex(self):
""" chop complex test """
paulis = [
Pauli.from_label(x)
for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']
]
coeffs = [
0.2 + -0.5j, 0.6 - 0.3j, 0.8 - 0.6j, -0.5 + -0.2j, -0.3 + 0.6j,
-0.6 + 0.8j
]
op = WeightedPauliOperator.from_list(paulis, coeffs)
ori_op = op.copy()
for threshold, num_paulis in zip([0.4, 0.7, 0.9], [6, 2, 0]):
op = ori_op.copy()
op1 = op.chop(threshold=threshold, copy=True)
self.assertEqual(len(op.paulis), 6,
"\n{}".format(op.print_details()))
self.assertEqual(len(op1.paulis), num_paulis,
"\n{}".format(op1.print_details()))
op1 = op.chop(threshold=threshold, copy=False)
self.assertEqual(len(op.paulis), num_paulis,
"\n{}".format(op.print_details()))
self.assertEqual(len(op1.paulis), num_paulis,
"\n{}".format(op1.print_details()))
def __init__(self,
operator,
optimizer,
var_form = None,
max_evals_grouped = 1,
aux_operators = None,
callback = None,
auto_conversion = True,
initial_point = None,
ham_list = None,
operator_list = None,
nonzero_terms = None,
starting_point = False,
expecs = None,
expec_mode = False,
dir_to_bracket = False,
ham_term_list = None,
ham_energy_list = None,
base_3_list = None):
super().__init__(
operator = operator,
var_form = var_form,
optimizer = optimizer,
initial_point = initial_point,
max_evals_grouped = max_evals_grouped,
aux_operators = aux_operators,
callback = callback,
auto_conversion = auto_conversion
)
self.num_qubits = operator.num_qubits
if expecs == None and expec_mode == True:
expecs = pd.read_csv('{}_qubit_pauli_values.csv'.format(self.num_qubits)) #this file is required unless you pass in the expecation values (in order) manually
expecs = expecs.to_dict()
if expec_mode == True:
self.expecs = expecs
else:
self.expecs = []
if operator_list is not None:
self.op_list = operator_list
else:
self.op_list = var_form.operator_pool.pool
if initial_point is not None:
self.param_list = initial_point
else:
self.param_list = [0]*len(self.op_list)
self.starting_point = starting_point
if starting_point:
self.ham_list = ham_list
self.nonzero_terms = nonzero_terms
self.zero_term = 0*WeightedPauliOperator.from_list(paulis = [Pauli.from_label('I'*self.num_qubits)])
self.empt_term = self.zero_term - self.zero_term
self.dir_to_bracket = dir_to_bracket
self.ham_term_list = ham_term_list
self.ham_energy_list = ham_energy_list
self.base_3_list = base_3_list
def anti_commuting_part(
self, operator: WeightedPauliOperator) -> WeightedPauliOperator:
result = WeightedPauliOperator([])
for c, p in self._hamiltonian.paulis:
part = WeightedPauliOperator.from_list(paulis=[p], weights=[c])
if part.anticommute_with(operator):
result += part
return result
def drop_z_2_symmetry_ops(self, inplace: bool = True):
f_op = WeightedPauliOperator.from_list(
paulis=[Pauli.from_label('X' * self.num_qubits)], weights=[1.0])
new_ops = list(filter(lambda op: f_op.commute_with(op), self.pool))
if inplace:
self._pool = new_ops
else:
res = ADAPTQAOAPool.from_operator_list(new_ops)
return res
def Generate_roto_op(op, *args, **kwargs):
parameter = kwargs['parameter']
ham = kwargs['ham']
energy_step_tol = kwargs['energy_step_tol']
Iden = WeightedPauliOperator.from_list(
paulis=[Pauli.from_label('I' * ham.num_qubits)], weights=[1.0])
psi = np.cos(parameter) * Iden + 1j * np.sin(parameter) * op
psi_star = np.cos(parameter) * Iden - 1j * np.sin(parameter) * op
return ((psi) * ham * (psi_star)).chop(threshold=energy_step_tol,
copy=True)
def test_equal_operator(self):
""" equal operator test """
paulis = [Pauli.from_label(x) for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']]
coeffs = [0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op1 = WeightedPauliOperator.from_list(paulis, coeffs)
coeffs = [0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op2 = WeightedPauliOperator.from_list(paulis, coeffs)
coeffs = [-0.2, -0.6, -0.8, 0.2, 0.6, 0.8]
op3 = WeightedPauliOperator.from_list(paulis, coeffs)
coeffs = [-0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op4 = WeightedPauliOperator.from_list(paulis, coeffs)
self.assertEqual(op1, op2)
self.assertNotEqual(op1, op3)
self.assertNotEqual(op1, op4)
self.assertNotEqual(op3, op4)
def split_into_paulis(ham):
"""
Used to split the given hamiltonian into lists of constituent parts:
weight_list: list of complex floats that are the weights of terms in the hamiltonian
pauli_list: a list of the Weighted_pauli_operator representations of the pauli strings in the hamiltonian
(does not include weights)
name_list: a list of strings that correspond to the names of the operators in the hamiltonian
"""
num_qubits = ham.num_qubits
ham_details = ham.print_details()
ham_list = ham_details.split('\n')
pauli_list = [0] * (len(ham_list) - 1
) #exclude last entry of ham list bc is just blank
name_list = [0] * (len(ham_list) - 1)
weight_list = [0] * (len(ham_list) - 1)
if len(ham_list) > 2:
for counter in range(0, len(ham_list), 1):
if ham_list[counter][num_qubits + 2:] == '':
break
if ham_list[counter][num_qubits + 1:] == '0':
name_list[counter] = 'I' * num_qubits
weight_list[counter] = complex(0)
pauli_list[counter] = 0 * WeightedPauliOperator.from_list(
paulis=[Pauli.from_label('I' * num_qubits)])
else:
pauli = Pauli.from_label(ham_list[counter][:num_qubits])
name_list[counter] = ham_list[counter][:num_qubits]
weight_list[counter] = complex(ham.paulis[counter][0])
pauli_list[counter] = WeightedPauliOperator.from_list([pauli])
else:
if ham_list[0][num_qubits + 1:-1] == '0':
name_list[0] = 'I' * num_qubits
weight_list[0] = complex(0)
pauli_list[0] = 0 * WeightedPauliOperator.from_list(
paulis=[Pauli.from_label('I' * num_qubits)])
else:
pauli = Pauli.from_label(ham_list[0][:num_qubits])
name_list[0] = ham_list[0][:num_qubits]
weight_list[0] = complex(ham.paulis[0][0])
pauli_list[0] = WeightedPauliOperator.from_list([pauli])
return weight_list, pauli_list, name_list
def test_evolve(self, expansion_mode, evo_time, num_time_slices):
expansion_orders = [1, 2, 3, 4] if expansion_mode == 'suzuki' else [1]
num_qubits = 2
paulis = [
Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ', repeat=num_qubits)
]
weights = np.random.random(len(paulis))
pauli_op = WeightedPauliOperator.from_list(paulis, weights)
matrix_op = op_converter.to_matrix_operator(pauli_op)
state_in = Custom(num_qubits, state='random')
# get the exact state_out from raw matrix multiplication
state_out_exact = matrix_op.evolve(
state_in=state_in.construct_circuit('vector'),
evo_time=evo_time,
num_time_slices=0)
# self.log.debug('exact:\n{}'.format(state_out_exact))
self.log.debug('Under {} expansion mode:'.format(expansion_mode))
for expansion_order in expansion_orders:
# assure every time the operator from the original one
if expansion_mode == 'suzuki':
self.log.debug(
'With expansion order {}:'.format(expansion_order))
state_out_matrix = matrix_op.evolve(
state_in=state_in.construct_circuit('vector'),
evo_time=evo_time,
num_time_slices=num_time_slices,
expansion_mode=expansion_mode,
expansion_order=expansion_order)
quantum_registers = QuantumRegister(pauli_op.num_qubits, name='q')
qc = QuantumCircuit(quantum_registers)
qc += state_in.construct_circuit('circuit', quantum_registers)
qc += pauli_op.copy().evolve(
evo_time=evo_time,
num_time_slices=num_time_slices,
quantum_registers=quantum_registers,
expansion_mode=expansion_mode,
expansion_order=expansion_order,
)
state_out_circuit = self.quantum_instance_statevector.execute(
qc).get_statevector(qc)
self.log.debug(
'The fidelity between exact and matrix: {}'.format(
state_fidelity(state_out_exact, state_out_matrix)))
self.log.debug(
'The fidelity between exact and circuit: {}'.format(
state_fidelity(state_out_exact, state_out_circuit)))
f_mc = state_fidelity(state_out_matrix, state_out_circuit)
self.log.debug(
'The fidelity between matrix and circuit: {}'.format(f_mc))
self.assertAlmostEqual(f_mc, 1)
def setUp(self):
super().setUp()
seed = 0
aqua_globals.random_seed = seed
self.num_qubits = 2
m_size = np.power(2, self.num_qubits)
matrix = aqua_globals.random.rand(m_size, m_size)
self.mat_op = MatrixOperator(matrix=matrix)
paulis = [Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ', repeat=self.num_qubits)]
weights = aqua_globals.random.random_sample(len(paulis))
self.pauli_op = WeightedPauliOperator.from_list(paulis, weights)
def test_from_to_file(self):
""" from to file test """
paulis = [Pauli.from_label(x) for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']]
weights = [0.2 + -1j * 0.8, 0.6 + -1j * 0.6, 0.8 + -1j * 0.2,
-0.2 + -1j * 0.8, -0.6 - -1j * 0.6, -0.8 - -1j * 0.2]
op = WeightedPauliOperator.from_list(paulis, weights)
file_path = self._get_resource_path('temp_op.json')
op.to_file(file_path)
self.assertTrue(os.path.exists(file_path))
load_op = WeightedPauliOperator.from_file(file_path)
self.assertEqual(op, load_op)
os.remove(file_path)
def test_instruction() -> None:
# TKET-446
qreg = QuantumRegister(3)
paulis = list(map(Pauli.from_label, ["XXI", "YYI", "ZZZ"]))
weights = [0.3, 0.5 + 1j * 0.2, -0.4]
op = WeightedPauliOperator.from_list(paulis, weights)
evolution_circ = op.evolve(None,
1.2,
num_time_slices=1,
quantum_registers=qreg)
tk_circ = qiskit_to_tk(evolution_circ)
cmds = tk_circ.get_commands()
assert len(cmds) == 1
assert cmds[0].op.type == OpType.CircBox
def retrieve_op_list(number, rev = False, num_qubits = 4):
adapt_op_df = pd.read_csv('load_adapt_roto_2_op_df.csv')
adapt_op_dict = adapt_op_df.to_dict()
op_label_list = list(adapt_op_dict['Ham_{}'.format(number)])
op_list = []
for label in op_label_list:
op_name = adapt_op_dict['Ham_{}'.format(number)][label]
print(op_name)
op = Pauli.from_label(op_name[:num_qubits])
op = WeightedPauliOperator.from_list([op])
op_list.append(op)
if rev:
return reverse(op_list)
return op_list
def retrieve_ham(number, num_qubits = 4):
adapt_data_df = pd.read_csv('load_adapt_roto_2_data_df.csv')
adapt_data_dict = adapt_data_df.to_dict()
Ham_list = adapt_data_dict['hamiltonian']
Ham = Ham_list[number]
single_ham_list = Ham.split('\n')
pauli_list = [0]*(len(single_ham_list)-1)
weight_list = [0]*(len(single_ham_list)-1)
for counter2 in range(0, len(single_ham_list)-1,1):
pauli_list[counter2] = Pauli.from_label(single_ham_list[counter2][:num_qubits])
weight_list[counter2] = complex(single_ham_list[counter2][num_qubits:])
qubit_op = WeightedPauliOperator.from_list(pauli_list,weight_list)
return qubit_op
def test_chop_real(self):
""" chop real test """
paulis = [Pauli(x) for x in ['IXYZ', 'XXZY', 'IIZZ', 'XXYY', 'ZZXX', 'YYYY']]
coeffs = [0.2, 0.6, 0.8, -0.2, -0.6, -0.8]
op = WeightedPauliOperator.from_list(paulis, coeffs)
ori_op = op.copy()
for threshold, num_paulis in zip([0.4, 0.7, 0.9], [4, 2, 0]):
op = ori_op.copy()
op1 = op.chop(threshold=threshold, copy=True)
self.assertEqual(len(op.paulis), 6, "\n{}".format(op.print_details()))
self.assertEqual(len(op1.paulis), num_paulis, "\n{}".format(op1.print_details()))
op1 = op.chop(threshold=threshold, copy=False)
self.assertEqual(len(op.paulis), num_paulis, "\n{}".format(op.print_details()))
self.assertEqual(len(op1.paulis), num_paulis, "\n{}".format(op1.print_details()))
def first_vqe_kwargs(self) -> Dict:
# This works for now, but always produces one extra parameter. -George, so we'll need to change this for rotoadapt too.
id_op = WeightedPauliOperator.from_list(paulis=[Pauli.from_label('I' * self.operator_pool.num_qubits)],
weights=[1.0])
var_form = self.variational_form([id_op])
self._operator_selector._quantum_instance = self.quantum_instance
return {
'operator': self.hamiltonian,
'var_form': var_form,
'optimizer': DummyOptimizer(),
'initial_point': np.array([np.pi]),
'max_evals_grouped': self.max_evals_grouped,
'aux_operators': self.aux_operators,
'callback': self.callback,
'auto_conversion': self.auto_conversion
}
def test_unsorted_grouping(self):
"""Test with normal grouping approach."""
num_qubits = 4
paulis = [Pauli.from_label(pauli_label)
for pauli_label in itertools.product('IXYZ', repeat=num_qubits)]
weights = aqua_globals.random.random_sample(len(paulis))
op = WeightedPauliOperator.from_list(paulis, weights)
grouped_op = op_converter.to_tpb_grouped_weighted_pauli_operator(
op, TPBGroupedWeightedPauliOperator.unsorted_grouping)
for g_p in grouped_op.paulis:
passed = False
for pauli in op.paulis:
if pauli[1] == g_p[1]:
passed = pauli[0] == g_p[0]
break
self.assertTrue(passed,
"non-existed paulis in grouped_paulis: {}".format(g_p[1].to_label()))
self.assertGreaterEqual(len(op.basis), len(grouped_op.basis))
def test_evaluate_single_pauli_statevector(self):
""" evaluate single pauli statevector test """
# X
op = WeightedPauliOperator.from_list([Pauli.from_label('X')])
qr = QuantumRegister(1, name='q')
wave_function = QuantumCircuit(qr)
# + 1 eigenstate
wave_function.h(qr[0])
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(1.0, actual_value[0].real, places=5)
# - 1 eigenstate
wave_function = QuantumCircuit(qr)
wave_function.x(qr[0])
wave_function.h(qr[0])
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(-1.0, actual_value[0].real, places=5)
# Y
op = WeightedPauliOperator.from_list([Pauli.from_label('Y')])
qr = QuantumRegister(1, name='q')
wave_function = QuantumCircuit(qr)
# + 1 eigenstate
wave_function.h(qr[0])
wave_function.s(qr[0])
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(1.0, actual_value[0].real, places=5)
# - 1 eigenstate
wave_function = QuantumCircuit(qr)
wave_function.x(qr[0])
wave_function.h(qr[0])
wave_function.s(qr[0])
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(-1.0, actual_value[0].real, places=5)
# Z
op = WeightedPauliOperator.from_list([Pauli.from_label('Z')])
qr = QuantumRegister(1, name='q')
wave_function = QuantumCircuit(qr)
# + 1 eigenstate
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(1.0, actual_value[0].real, places=5)
# - 1 eigenstate
wave_function = QuantumCircuit(qr)
wave_function.x(qr[0])
circuits = op.construct_evaluation_circuit(wave_function=wave_function,
statevector_mode=True)
result = self.quantum_instance_statevector.execute(circuits)
actual_value = op.evaluate_with_result(result=result,
statevector_mode=True)
self.assertAlmostEqual(-1.0, actual_value[0].real, places=5)
adapt_data_df = pd.read_csv('load_adapt_data_df.csv')
adapt_data_dict = adapt_data_df.to_dict()
Ham_list = adapt_data_dict['hamiltonian']
counter = 0
counter2 = 0
num_hams = 10
pauli_meta_list = [0]*num_hams
weight_meta_list = [0]*num_hams
Exact_energy_dict = {'Ham_1':[],'Ham_2':[],'Ham_3':[],'Ham_4':[],'Ham_5':[],'Ham_6':[],'Ham_7':[],'Ham_8':[],'Ham_9':[]}
for counter in range(0,num_hams,1):
Ham = Ham_list[counter]
single_ham_list = Ham.split('\n')
pauli_list = [0]*(len(single_ham_list)-1)
weight_list = [0]*(len(single_ham_list)-1)
for counter2 in range(0, len(single_ham_list)-1,1):
pauli_list[counter2] = Pauli.from_label(single_ham_list[counter2][:4])
weight_list[counter2] = complex(single_ham_list[counter2][6:-1])
pauli_meta_list[counter] = pauli_list
weight_meta_list[counter] = weight_list
qubit_op = WeightedPauliOperator.from_list(pauli_list,weight_list)
Exact_result = ExactEigensolver(qubit_op, k = 16).run()
Exact_energy_dict['Ham_{}'.format(counter)] = Exact_result['energies']
print('E', Exact_result)
Exact_energy_df = pd.DataFrame(Exact_energy_dict)
Exact_energy_df_file = open("exact_energy_df.csv", "w+")
Exact_energy_df.to_csv('exact_energy_df.csv')
Exact_energy_df_file.close()
exact_dict = {'2': [], '3': [], '4': [], '5': [], '6': [], '7': [], '8': [], '9': [], '10': []}
num_qubits = 4
#test = random_diagonal_hermitian(2)
#print(test.print_details())
#mat = to_matrix_operator(test)
#print(mat.print_details())
for i in range(0,1):
k = 0
runtime_sum = 0
exact_time_sum = 0
vqeruntime_sum = 0
print('num_qubits', num_qubits)
while k < runs:
initial_state = Zero(num_qubits)
op_list = []
wop = 0*WeightedPauliOperator.from_list(paulis=[Pauli.from_label('I'*num_qubits)], weights=[1.0])
#mat = np.random.uniform(0, 1, size=(2**num_qubits, 2**num_qubits)) + 1j * np.random.uniform(0, 1, size=(2**num_qubits, 2**num_qubits))
#mat = np.conjugate(np.transpose(mat)) + mat
#ham = to_weighted_pauli_operator(MatrixOperator(mat)) #creates random hamiltonian from random matrix "mat"
ham = get_h_4_hamiltonian(0.25, 2, "jw")
#ham = retrieve_ham(0, num_qubits = num_qubits)
print('old_ham', ham.print_details())
#ham = get_h_4_hamiltonian(0.5,2,'jw')
#op_list = retrieve_op_list(0, rev = True, num_qubits = num_qubits)
#for op in op_list:
# print(op.print_details())
op_list = [WeightedPauliOperator.from_list([Pauli.from_label('IIXX')]), WeightedPauliOperator.from_list([Pauli.from_label('XXXY')])]
#op_list = [WeightedPauliOperator.from_list([Pauli.from_label('YYZZ')],[1.0]),
# WeightedPauliOperator.from_list([Pauli.from_label('XXXY')], [1.0]),
# WeightedPauliOperator.from_list([Pauli.from_label('IIYZ')], [1.0])]
