def test_apply_spinful_fermionop(self):
"""
Make sure the spin-orbital reordering is working by comparing
apply operation
"""
wfn = Wavefunction([[2, 0, 2]])
wfn.set_wfn(strategy='random')
wfn.normalize()
cirq_wf = to_cirq(wfn).reshape((-1, 1))
op_to_apply = FermionOperator()
test_state = copy.deepcopy(wfn)
test_state.set_wfn('zero')
for p, q, r, s in product(range(2), repeat=4):
op = FermionOperator(
((2 * p, 1), (2 * q + 1, 1), (2 * r + 1, 0), (2 * s, 0)),
coefficient=numpy.random.randn())
op_to_apply += op + hermitian_conjugated(op)
test_state += wfn.apply(op + hermitian_conjugated(op))
opmat = get_sparse_operator(op_to_apply, n_qubits=4).toarray()
new_state_cirq = opmat @ cirq_wf
# this part is because we need to pass a normalized wavefunction
norm_constant = new_state_cirq.conj().T @ new_state_cirq
new_state_cirq /= numpy.sqrt(norm_constant)
new_state_wfn = from_cirq(new_state_cirq.flatten(), thresh=1.0E-12)
new_state_wfn.scale(numpy.sqrt(norm_constant))
self.assertTrue(
numpy.allclose(test_state.get_coeff((2, 0)),
new_state_wfn.get_coeff((2, 0))))
def test_evolve_spinful_fermionop(self):
"""
Make sure the spin-orbital reordering is working by comparing
time evolution
"""
wfn = Wavefunction([[2, 0, 2]])
wfn.set_wfn(strategy='random')
wfn.normalize()
cirq_wf = to_cirq(wfn).reshape((-1, 1))
op_to_apply = FermionOperator()
for p, q, r, s in product(range(2), repeat=4):
op = FermionOperator(
((2 * p, 1), (2 * q + 1, 1), (2 * r + 1, 0), (2 * s, 0)),
coefficient=numpy.random.randn())
op_to_apply += op + hermitian_conjugated(op)
opmat = get_sparse_operator(op_to_apply, n_qubits=4).toarray()
dt = 0.765
new_state_cirq = scipy.linalg.expm(-1j * dt * opmat) @ cirq_wf
new_state_wfn = from_cirq(new_state_cirq.flatten(), thresh=1.0E-12)
test_state = wfn.time_evolve(dt, op_to_apply)
self.assertTrue(
numpy.allclose(test_state.get_coeff((2, 0)),
new_state_wfn.get_coeff((2, 0))))
def fermion_generator(self) -> openfermion.FermionOperator:
"""The FermionOperator G such that the gate's unitary is exp(-i t G)
with exponent t using the Jordan-Wigner transformation."""
half_generator = sum((
w * G
for w, G in zip(self.weights, self.fermion_generator_components())),
openfermion.FermionOperator())
return half_generator + openfermion.hermitian_conjugated(half_generator)
def operations(self, qubits: Sequence[cirq.Qid]) -> cirq.OP_TREE:
"""Returns qubit operators based on STO-3G and UCCSD ansatz"""
_symbols = list(self.params())
_ucc_operator = self._fermionic_operators # self._get_fermionic_operators()
for i, fo in enumerate(_ucc_operator[::2]):
# Jordan-Wigner transform each fermionic operator + its Hermitian conjugate
qo_list = list(of.jordan_wigner(fo - of.hermitian_conjugated(fo)))
yield IGeneralizedUCCSD.qubit_to_gate_operators(
qubit_operators=qo_list, qubits=qubits, par=_symbols[i])
def test_qubitop_to_dict_io(self):
# Given
qubit_op = QubitOperator(((0, 'Y'), (1, 'X'), (2, 'Z'), (4, 'X')), 3.j)
qubit_op += hermitian_conjugated(qubit_op)
# When
qubitop_dict = convert_qubitop_to_dict(qubit_op)
recreated_qubit_op = convert_dict_to_qubitop(qubitop_dict)
# Then
self.assertEqual(recreated_qubit_op, qubit_op)
def test_double_excitation_matches_fermionic_evolution(exponent):
gate = ofc.DoubleExcitation ** exponent
op = openfermion.FermionOperator('3^ 2^ 1 0')
op += openfermion.hermitian_conjugated(op)
matrix_op = openfermion.get_sparse_operator(op)
time_evol_op = scipy.linalg.expm(-1j * matrix_op * exponent * numpy.pi)
time_evol_op = time_evol_op.todense()
cirq.testing.assert_allclose_up_to_global_phase(
cirq.unitary(gate), time_evol_op, atol=1e-7)
def test_double_excitation_matches_fermionic_evolution(half_turns):
gate = DoubleExcitation ** half_turns
op = openfermion.FermionOperator('3^ 2^ 1 0')
op += openfermion.hermitian_conjugated(op)
matrix_op = openfermion.get_sparse_operator(op)
time_evol_op = scipy.linalg.expm(-1j * matrix_op * half_turns * numpy.pi)
time_evol_op = time_evol_op.todense()
cirq.testing.assert_allclose_up_to_global_phase(
gate.matrix(), time_evol_op, atol=1e-7)
def test_interaction_op_to_dict_io(self):
# Given
test_op = FermionOperator("1^ 2^ 3 4")
test_op += hermitian_conjugated(test_op)
interaction_op = get_interaction_operator(test_op)
interaction_op.constant = 0.0
# When
interaction_op_dict = convert_interaction_op_to_dict(interaction_op)
recreated_interaction_op = convert_dict_to_interaction_op(
interaction_op_dict)
# Then
self.assertEqual(recreated_interaction_op, interaction_op)
def test_interaction_operator_io(self):
# Given
test_op = FermionOperator("1^ 2^ 3 4")
test_op += hermitian_conjugated(test_op)
interaction_op = get_interaction_operator(test_op)
interaction_op.constant = 0.0
# When
save_interaction_operator(interaction_op, "interaction_op.json")
loaded_op = load_interaction_operator("interaction_op.json")
# Then
self.assertEqual(interaction_op, loaded_op)
os.remove("interaction_op.json")
def test_generalized_doubles():
generator = generate_antisymm_generator(2)
nso = generator.shape[0]
for p, q, r, s in product(range(nso), repeat=4):
if p < q and s < r:
assert np.isclose(generator[p, q, r, s], -generator[q, p, r, s])
ul, vl, one_body_residual, ul_ops, vl_ops, one_body_op = \
doubles_factorization_svd(generator)
generator_mat = np.reshape(np.transpose(generator, [0, 3, 1, 2]),
(nso**2, nso**2)).astype(np.float)
one_body_residual_test = -np.einsum('pqrq->pr', generator)
assert np.allclose(generator_mat, generator_mat.T)
assert np.allclose(one_body_residual, one_body_residual_test)
tgenerator_mat = np.zeros_like(generator_mat)
for row_gem, col_gem in product(range(nso**2), repeat=2):
p, s = row_gem // nso, row_gem % nso
q, r = col_gem // nso, col_gem % nso
tgenerator_mat[row_gem, col_gem] = generator[p, q, r, s]
assert np.allclose(tgenerator_mat, generator_mat)
u, sigma, vh = np.linalg.svd(generator_mat)
fop = copy.deepcopy(one_body_op)
fop2 = copy.deepcopy(one_body_op)
fop3 = copy.deepcopy(one_body_op)
fop4 = copy.deepcopy(one_body_op)
for ll in range(len(sigma)):
ul.append(np.sqrt(sigma[ll]) * u[:, ll].reshape((nso, nso)))
ul_ops.append(
get_fermion_op(np.sqrt(sigma[ll]) * u[:, ll].reshape((nso, nso))))
vl.append(np.sqrt(sigma[ll]) * vh[ll, :].reshape((nso, nso)))
vl_ops.append(
get_fermion_op(np.sqrt(sigma[ll]) * vh[ll, :].reshape((nso, nso))))
Smat = ul[ll] + vl[ll]
Dmat = ul[ll] - vl[ll]
S = ul_ops[ll] + vl_ops[ll]
Sd = of.hermitian_conjugated(S)
D = ul_ops[ll] - vl_ops[ll]
Dd = of.hermitian_conjugated(D)
op1 = S + 1j * of.hermitian_conjugated(S)
op2 = S - 1j * of.hermitian_conjugated(S)
op3 = D + 1j * of.hermitian_conjugated(D)
op4 = D - 1j * of.hermitian_conjugated(D)
assert np.isclose(
of.normal_ordered(of.commutator(
op1, of.hermitian_conjugated(op1))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op2, of.hermitian_conjugated(op2))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op3, of.hermitian_conjugated(op3))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op4, of.hermitian_conjugated(op4))).induced_norm(), 0)
fop3 += (1 / 8) * ((S**2 - Sd**2) - (D**2 - Dd**2))
fop4 += (1 / 16) * ((op1**2 + op2**2) - (op3**2 + op4**2))
op1mat = Smat + 1j * Smat.T
op2mat = Smat - 1j * Smat.T
op3mat = Dmat + 1j * Dmat.T
op4mat = Dmat - 1j * Dmat.T
assert np.allclose(of.commutator(op1mat, op1mat.conj().T), 0)
assert np.allclose(of.commutator(op2mat, op2mat.conj().T), 0)
assert np.allclose(of.commutator(op3mat, op3mat.conj().T), 0)
assert np.allclose(of.commutator(op4mat, op4mat.conj().T), 0)
# check that we have normal operators and that the outer product
# of their eigenvalues is imaginary. Also check vv is unitary
if not np.isclose(sigma[ll], 0):
assert np.isclose(
of.normal_ordered(get_fermion_op(op1mat) - op1).induced_norm(),
0)
assert np.isclose(
of.normal_ordered(get_fermion_op(op2mat) - op2).induced_norm(),
0)
assert np.isclose(
of.normal_ordered(get_fermion_op(op3mat) - op3).induced_norm(),
0)
assert np.isclose(
of.normal_ordered(get_fermion_op(op4mat) - op4).induced_norm(),
0)
ww, vv = np.linalg.eig(op1mat)
eye = np.eye(nso)
assert np.allclose(np.outer(ww, ww).real, 0)
assert np.allclose(vv.conj().T @ vv, eye)
ww, vv = np.linalg.eig(op2mat)
assert np.allclose(np.outer(ww, ww).real, 0)
assert np.allclose(vv.conj().T @ vv, eye)
ww, vv = np.linalg.eig(op3mat)
assert np.allclose(np.outer(ww, ww).real, 0)
assert np.allclose(vv.conj().T @ vv, eye)
ww, vv = np.linalg.eig(op4mat)
assert np.allclose(np.outer(ww, ww).real, 0)
assert np.allclose(vv.conj().T @ vv, eye)
fop2 += 0.25 * ul_ops[ll] * vl_ops[ll]
fop2 += 0.25 * vl_ops[ll] * ul_ops[ll]
fop2 += -0.25 * of.hermitian_conjugated(
vl_ops[ll]) * of.hermitian_conjugated(ul_ops[ll])
fop2 += -0.25 * of.hermitian_conjugated(
ul_ops[ll]) * of.hermitian_conjugated(vl_ops[ll])
fop += vl_ops[ll] * ul_ops[ll]
true_fop = get_fermion_op(generator)
assert np.isclose(of.normal_ordered(fop - true_fop).induced_norm(), 0)
assert np.isclose(of.normal_ordered(fop2 - true_fop).induced_norm(), 0)
assert np.isclose(of.normal_ordered(fop3 - true_fop).induced_norm(), 0)
assert np.isclose(of.normal_ordered(fop4 - true_fop).induced_norm(), 0)
def test_random_evolution():
sdim = 2
nele = 2
generator = generate_antisymm_generator(2 * sdim)
nso = generator.shape[0]
for p, q, r, s in product(range(nso), repeat=4):
if p < q and s < r:
assert np.isclose(generator[p, q, r, s], -generator[q, p, r, s])
generator_mat = np.reshape(np.transpose(generator, [0, 3, 1, 2]),
(nso**2, nso**2)).astype(np.float)
_, sigma, _ = np.linalg.svd(generator_mat)
ul, vl, _, ul_ops, vl_ops, _ = \
doubles_factorization_svd(generator)
rwf = fqe.get_number_conserving_wavefunction(nele, sdim)
# rwf = fqe.Wavefunction([[nele, 0, sdim]])
rwf.set_wfn(strategy='random')
rwf.normalize()
sigma_idx = np.where(sigma > 1.0E-13)[0]
for ll in sigma_idx:
Smat = ul[ll] + vl[ll]
Dmat = ul[ll] - vl[ll]
S = ul_ops[ll] + vl_ops[ll]
D = ul_ops[ll] - vl_ops[ll]
op1 = S + 1j * of.hermitian_conjugated(S)
op2 = S - 1j * of.hermitian_conjugated(S)
op3 = D + 1j * of.hermitian_conjugated(D)
op4 = D - 1j * of.hermitian_conjugated(D)
op1mat = Smat + 1j * Smat.T
op2mat = Smat - 1j * Smat.T
op3mat = Dmat + 1j * Dmat.T
op4mat = Dmat - 1j * Dmat.T
o1_rwf = rwf.time_evolve(1 / 16, 1j * op1**2)
ww, vv = np.linalg.eig(op1mat)
assert np.allclose(vv @ np.diag(ww) @ vv.conj().T, op1mat)
trwf = evolve_fqe_givens_unrestricted(rwf, vv.conj().T)
v_pq = np.outer(ww, ww)
for p, q in product(range(nso), repeat=2):
fop = of.FermionOperator(((p, 1), (p, 0), (q, 1), (q, 0)),
coefficient=-v_pq[p, q].imag)
trwf = trwf.time_evolve(1 / 16, fop)
trwf = evolve_fqe_givens_unrestricted(trwf, vv)
assert np.isclose(fqe.vdot(o1_rwf, trwf), 1)
o_rwf = rwf.time_evolve(1 / 16, 1j * op2**2)
ww, vv = np.linalg.eig(op2mat)
assert np.allclose(vv @ np.diag(ww) @ vv.conj().T, op2mat)
trwf = evolve_fqe_givens_unrestricted(rwf, vv.conj().T)
v_pq = np.outer(ww, ww)
for p, q in product(range(nso), repeat=2):
fop = of.FermionOperator(((p, 1), (p, 0), (q, 1), (q, 0)),
coefficient=-v_pq[p, q].imag)
trwf = trwf.time_evolve(1 / 16, fop)
trwf = evolve_fqe_givens_unrestricted(trwf, vv)
assert np.isclose(fqe.vdot(o_rwf, trwf), 1)
o_rwf = rwf.time_evolve(-1 / 16, 1j * op3**2)
ww, vv = np.linalg.eig(op3mat)
assert np.allclose(vv @ np.diag(ww) @ vv.conj().T, op3mat)
trwf = evolve_fqe_givens_unrestricted(rwf, vv.conj().T)
v_pq = np.outer(ww, ww)
for p, q in product(range(nso), repeat=2):
fop = of.FermionOperator(((p, 1), (p, 0), (q, 1), (q, 0)),
coefficient=-v_pq[p, q].imag)
trwf = trwf.time_evolve(-1 / 16, fop)
trwf = evolve_fqe_givens_unrestricted(trwf, vv)
assert np.isclose(fqe.vdot(o_rwf, trwf), 1)
o_rwf = rwf.time_evolve(-1 / 16, 1j * op4**2)
ww, vv = np.linalg.eig(op4mat)
assert np.allclose(vv @ np.diag(ww) @ vv.conj().T, op4mat)
trwf = evolve_fqe_givens_unrestricted(rwf, vv.conj().T)
v_pq = np.outer(ww, ww)
for p, q in product(range(nso), repeat=2):
fop = of.FermionOperator(((p, 1), (p, 0), (q, 1), (q, 0)),
coefficient=-v_pq[p, q].imag)
trwf = trwf.time_evolve(-1 / 16, fop)
trwf = evolve_fqe_givens_unrestricted(trwf, vv)
assert np.isclose(fqe.vdot(o_rwf, trwf), 1)
def test_build_hamiltonian_paths(self):
"""Check that all cases of hamiltonian objects are built
"""
self.assertRaises(TypeError, build_hamiltonian, 0)
with self.subTest(name='general'):
ops = FermionOperator('1^ 4^ 0 3', 1.0) \
+ FermionOperator('0^ 5^ 3 2^ 4^ 1 7 6', 1.2) \
+ FermionOperator('1^ 6', -0.3)
ops += hermitian_conjugated(ops)
self.assertIsInstance(build_hamiltonian(ops),
general_hamiltonian.General)
with self.subTest(name='sparse'):
ops = FermionOperator('5^ 1^ 3^ 2 0 1', 1.0 - 1.j) \
+ FermionOperator('1^ 0^ 2^ 3 1 5', 1.0 + 1.j)
self.assertIsInstance(build_hamiltonian(ops),
sparse_hamiltonian.SparseHamiltonian)
with self.subTest(name='diagonal'):
ops = FermionOperator('1^ 1', 1.0) \
+ FermionOperator('2^ 2', 2.0) \
+ FermionOperator('3^ 3', 3.0) \
+ FermionOperator('4^ 4', 4.0)
self.assertIsInstance(build_hamiltonian(ops),
diagonal_hamiltonian.Diagonal)
with self.subTest(name='gso'):
ops = FermionOperator()
for i in range(4):
for j in range(4):
opstr = str(i) + '^ ' + str(j)
coeff = complex((i + 1) * (j + 1) * 0.1)
ops += FermionOperator(opstr, coeff)
self.assertIsInstance(build_hamiltonian(ops),
gso_hamiltonian.GSOHamiltonian)
with self.subTest(name='restricted'):
ops = FermionOperator()
for i in range(0, 3, 2):
for j in range(0, 3, 2):
coeff = complex((i + 1) * (j + 1) * 0.1)
opstr = str(i) + '^ ' + str(j)
ops += FermionOperator(opstr, coeff)
opstr = str(i + 1) + '^ ' + str(j + 1)
ops += FermionOperator(opstr, coeff)
self.assertIsInstance(build_hamiltonian(ops),
restricted_hamiltonian.RestrictedHamiltonian)
with self.subTest(name='sso'):
ops = FermionOperator()
for i in range(0, 3, 2):
for j in range(0, 3, 2):
coeff = complex((i + 1) * (j + 1) * 0.1)
opstr = str(i) + '^ ' + str(j)
ops += FermionOperator(opstr, coeff)
opstr = str(i + 1) + '^ ' + str(j + 1)
coeff *= 1.5
ops += FermionOperator(opstr, coeff)
self.assertIsInstance(build_hamiltonian(ops),
sso_hamiltonian.SSOHamiltonian)
with self.subTest(name='diagonal_coulomb'):
ops = FermionOperator()
for i in range(4):
for j in range(4):
opstring = str(i) + '^ ' + str(j) + '^ ' + str(
i) + ' ' + str(j)
ops += FermionOperator(opstring, 0.001 * (i + 1) * (j + 1))
self.assertIsInstance(build_hamiltonian(ops),
diagonal_coulomb.DiagonalCoulomb)
def multi_particle_ucc(h, reference=0, trotter_order=1, trotter_steps=1):
"""
UCC-style ansatz that doesn't preserve anything (i.e. uses all basis
states). This is basically an implementation of create_arbitrary_state
(however, theta will not match the coefficients in the superposition)
built on pyquil.paulis.exponentiate_map.
One idea is to use lowering and raising operators and "check operators"
instead of Xs. This results in a more straight-forward mapping of theta
to the coefficients since no previously produced state will be mapped
to other states in a later stage. To clarify: with the current
implementation the state |1 1 0> will both be produced by exp(X2 X1)
operating on |0 0 0> and by exp(X2) operating on exp(X1)|0 0 0> (which
contains a |0 1 0> term). This could improve potential bad properties
with the current implementation. However, it might be difficult to
create commuting hermitian terms, which is required in
exponential_map_commuting_pauli_terms.
If this function is called multiple times, particularly if theta has the
same length in all calls, caching terms might significantly increase
performance.
@author: Joel
:param np.ndarray h: The hamiltonian matrix.
:param reference: integer representation of reference state
:param trotter_order: Trotter order in trotterization
:param trotter_steps: Trotter steps in trotterization
:return: function(theta) which returns the ansatz Program. -1j*theta[i] is
the coefficient in front of the term prod_k X_k^bit(i,k) where
bit(i, k) is the k'th bit of i in binary, in the exponent.
"""
dim = h.shape[0]
terms = []
for state in range(dim):
if state != reference:
term = QubitOperator(())
for qubit in range(int.bit_length(state)):
if (state ^ reference) & (1 << qubit):
# lower/raise qubit
term *= QubitOperator((qubit, "X"), 1 / 2) \
+ QubitOperator((qubit, "Y"), 1j * (int(
reference & (1 << qubit) != 0) - 1 / 2))
else:
# check that qubit has correct value (same as i and j)
term *= QubitOperator((), 1 / 2) \
+ QubitOperator((qubit, "Z"), 1 / 2 - int(
reference & (1 << qubit) != 0))
terms.append(
qubitop_to_pyquilpauli(term - hermitian_conjugated(term)))
exp_maps = trotterize(terms, trotter_order, trotter_steps)
def wrap(theta):
"""
Returns the ansatz Program.
:param np.ndarray theta: parameters
:return: the Program
:rtype: pyquil.Program
"""
prog = Program()
for qubit in range(int.bit_length(reference)):
if reference & (1 << qubit):
prog += X(qubit)
for idx, exp_map in enumerate(exp_maps):
for exp in exp_map:
prog += exp(theta[idx])
return prog
return wrap
def test_operators_initialization(coefficient: float):
# 1. Let's create some basic operator
operator = FermionOperator('2^ 1 3 7^', coefficient)
alternative_operator = coefficient * FermionOperator(((2, 1), (1, 0), (3, 0), (6, 1)))
sum_of_operators = operator + alternative_operator
identity = FermionOperator('')
zero = FermionOperator()
# print(f'Fermion operator: {operator}; the terms are {list(operator.terms.keys())[0]}')
print(f'Fermion operator: {operator}; the flattened terms are {operator.flattened_terms}')
print(f'Alternative fermion operator: {alternative_operator}')
print(f'Sum fermion operator: {sum_of_operators}; the terms are {sum_of_operators.terms}')
# print(operator == alternative_operator)
print(f'Identity operator: {identity}')
print(f'Zero operator: {zero}')
# 2. Checking operator combinations
lhs_operator = FermionOperator('17^')
rhs_operator = FermionOperator('19^')
print(describe_result(lhs_operator, rhs_operator, lambda lhs, rhs: lhs * rhs, '*'))
print(describe_result(lhs_operator, lhs_operator, lambda lhs, rhs: lhs * rhs, '*'))
print(describe_result(lhs_operator, rhs_operator, lambda lhs, rhs: lhs + rhs, '+'))
print(describe_result(lhs_operator, 5, lambda lhs, rhs: lhs ** rhs, '^'))
# print(describe_result(lhs_operator * rhs_operator, lhs_operator, lambda lhs, rhs: lhs / rhs, '/')) # Throws an exception
# 3. Use some auxiliary functions
print(f'Operator {lhs_operator ** 5} occupies {count_qubits(lhs_operator)} qubits')
print(f'Operator {rhs_operator ** 2} occupies {count_qubits(rhs_operator)} qubits')
print(f'Operator {operator} occupies {count_qubits(operator)} qubits')
print(f'Operator {operator} is {"not " if not operator.is_normal_ordered() else ""}normal ordered')
print(f'Operator {(lhs_operator + rhs_operator)} is {"not " if not (lhs_operator + rhs_operator).is_normal_ordered() else ""}normal ordered')
print(f'Operator {(lhs_operator * rhs_operator)} is {"not " if not (lhs_operator * rhs_operator).is_normal_ordered() else ""}normal ordered')
print(f'Operator {(rhs_operator * lhs_operator)} is {"not " if not (rhs_operator * lhs_operator).is_normal_ordered() else ""}normal ordered')
print(f'Commutator of {lhs_operator} and {rhs_operator} is {commutator(lhs_operator, rhs_operator)}')
# 4. See qubit operators
operator = QubitOperator('X1 Z3', coefficient) + QubitOperator('X20', coefficient - 1)
print(f'Operator {operator} occupies {count_qubits(operator)} qubits')
# 4. Perform transformations from fermion to qubit operators
fermion_operator = FermionOperator_('5^', 0.1 + 0.2j)
fermion_operator += hermitian_conjugated(fermion_operator)
jw_operator = jordan_wigner(fermion_operator)
bk_operator = bravyi_kitaev(fermion_operator)
print()
print('Source fermion operator:')
print(fermion_operator)
print()
print('Source fermion operator with conjugate:')
print(fermion_operator)
print()
print('Source fermion operator with conjugate passed through Jordan-Wigner transformation:')
print(jw_operator)
print()
print('Eigenspectrum of the obtained operator:')
print(eigenspectrum(jw_operator))
print()
print('Reversed:')
print(reverse_jordan_wigner(jw_operator))
print()
print('Source fermion operator with conjugate passed through Bravyi-Kitaev transformation:')
print(bk_operator)
print()
print('Eigenspectrum of the obtained operator:')
print(eigenspectrum(bk_operator))
print()
def doubles_factorization_svd(generator_tensor: np.ndarray, eig_cutoff=None):
"""
Given an antisymmetric antihermitian tensor perform a double factorized
low-rank decomposition.
Given:
A = sum_{pqrs}A^{pq}_{sr}p^ q^ r s
with A^{pq}_{sr} = -A^{qp}_{sr} = -A^{pq}_{rs} = -A^{sr}_{pq}
Rewrite A as a sum-of squares s.t
A = sum_{l}Y_{l}^2
where Y_{l} are normal operator one-body operators such that the spectral
theorem holds and we can use the double factorization to implement an
approximate evolution.
"""
if not np.allclose(generator_tensor.imag, 0):
raise TypeError("generator_tensor must be a real matrix")
if eig_cutoff is not None:
if eig_cutoff % 2 != 0:
raise ValueError("eig_cutoff must be an even number")
nso = generator_tensor.shape[0]
generator_tensor = generator_tensor.real
generator_mat = np.zeros((nso**2, nso**2))
for row_gem, col_gem in product(range(nso**2), repeat=2):
p, s = row_gem // nso, row_gem % nso
q, r = col_gem // nso, col_gem % nso
generator_mat[row_gem, col_gem] = generator_tensor[p, q, r, s]
test_generator_mat = np.reshape(
np.transpose(generator_tensor, [0, 3, 1, 2]),
(nso**2, nso**2)).astype(np.float)
assert np.allclose(test_generator_mat, generator_mat)
if not np.allclose(generator_mat, generator_mat.T):
raise ValueError("generator tensor does not correspond to four-fold"
" antisymmetry")
one_body_residual = -np.einsum('pqrq->pr', generator_tensor)
u, sigma, vh = np.linalg.svd(generator_mat)
ul = []
ul_ops = []
vl = []
vl_ops = []
if eig_cutoff is None:
max_sigma = len(sigma)
else:
max_sigma = eig_cutoff
for ll in range(max_sigma):
ul.append(np.sqrt(sigma[ll]) * u[:, ll].reshape((nso, nso)))
ul_ops.append(
get_fermion_op(np.sqrt(sigma[ll]) * u[:, ll].reshape((nso, nso))))
vl.append(np.sqrt(sigma[ll]) * vh[ll, :].reshape((nso, nso)))
vl_ops.append(
get_fermion_op(np.sqrt(sigma[ll]) * vh[ll, :].reshape((nso, nso))))
S = ul_ops[ll] + vl_ops[ll]
D = ul_ops[ll] - vl_ops[ll]
op1 = S + 1j * of.hermitian_conjugated(S)
op2 = S - 1j * of.hermitian_conjugated(S)
op3 = D + 1j * of.hermitian_conjugated(D)
op4 = D - 1j * of.hermitian_conjugated(D)
assert np.isclose(
of.normal_ordered(of.commutator(
op1, of.hermitian_conjugated(op1))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op2, of.hermitian_conjugated(op2))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op3, of.hermitian_conjugated(op3))).induced_norm(), 0)
assert np.isclose(
of.normal_ordered(of.commutator(
op4, of.hermitian_conjugated(op4))).induced_norm(), 0)
one_body_op = of.FermionOperator()
for p, q in product(range(nso), repeat=2):
tfop = ((p, 1), (q, 0))
one_body_op += of.FermionOperator(tfop,
coefficient=one_body_residual[p, q])
return ul, vl, one_body_residual, ul_ops, vl_ops, one_body_op
