def test_mappings():
n_density, rdm_gen, transform, molecule = h2_system()
density = SpinOrbitalDensity(n_density, molecule.n_qubits)
tpdm = density.construct_tpdm().real
opdm = density.construct_opdm().real
oqdm = density.construct_ohdm().real
tqdm = density.construct_thdm().real
phdm = density.construct_phdm().real
test_opdm = map_tpdm_to_opdm(tpdm, molecule.n_electrons)
assert np.allclose(test_opdm, opdm)
test_tqdm = map_tpdm_to_tqdm(tpdm, opdm)
assert np.allclose(test_tqdm, tqdm)
test_phdm = map_tpdm_to_phdm(tpdm, opdm)
assert np.allclose(test_phdm, phdm)
test_tpdm = map_tqdm_to_tpdm(tqdm, opdm)
assert np.allclose(test_tpdm, tpdm)
test_tpdm = map_phdm_to_tpdm(phdm, opdm)
assert np.allclose(test_tpdm, tpdm)
test_oqdm = map_tqdm_to_oqdm(tqdm,
molecule.n_qubits - molecule.n_electrons)
assert np.allclose(test_oqdm, oqdm)
test_opdm = map_oqdm_to_opdm(oqdm)
assert np.allclose(test_opdm, opdm)
test_oqdm = map_opdm_to_oqdm(opdm)
assert np.allclose(test_oqdm, oqdm)
eta = molecule.n_qubits - molecule.n_electrons
N = molecule.n_electrons
opdm_test = np.einsum('ijkj', phdm) / ((N + 1))
assert np.allclose(opdm, opdm_test)
def coleman_projection_dq(tpdm, N, error=1.0E-6, disp=False):
"""
Fixe up the tpdm trace and 1-particle piece and then iterate over the
Coleman decomp of exposed operators
:param tpdm:
:param N:
:param float error:
:param Bool disp: optional argument for displaying updates
:return:
"""
dim = tpdm.shape[0]
_, _, d2_2 = coleman_decomposition(tpdm)
# check if this thing I grabbed is actually an antisymmetric operator
eye_wedge_eye = wedge_product(np.eye(dim), np.eye(dim)).astype(complex)
eye_wedge_eye_mat = four_tensor2matrix(eye_wedge_eye)
# we know d2_0 by fixed trace from particle number
trace_value = N * (N - 1)
d2_0 = ((2 * trace_value) / (dim * (dim - 1))) * eye_wedge_eye
# we know d2_1 should be (N - 1) * opdm
# so grab the opdm first from the noisy tpdm and then purify
opdm = map_tpdm_to_opdm(tpdm, N)
# opdm_new = mazziotti_opdm_purification(opdm, N)
opdm_new = fixed_trace_positive_projection(opdm, N)
# first multiply by N - 1 get back to just contracted. Then another
# for adjusting
one_one_tensor = ((N - 1)**2) * opdm_new
one_one_eye = wedge_product(one_one_tensor, np.eye(dim))
one_one_eye_mat = four_tensor2matrix(one_one_eye)
d2_1 = (4 / (dim - 2)) * one_one_eye
d2_1 -= ((4 * trace_value) / (dim * (dim - 2))) * eye_wedge_eye
# we need to check a bunch of stuff about the reconstruct tpdm
# a) does it have all the right symmetry
# b) does it have the right trace and does it contract appropriately
# c) does the d2_0 + d2_1 look like a contracted tpdm_partial fix
tpdm_partial_fix = d2_0 + d2_1 + d2_2
d2_matrix = four_tensor2matrix(tpdm_partial_fix)
# grabbing the 2-Q-RDM
tqdm = map_tpdm_to_tqdm(tpdm_partial_fix, opdm_new)
q2_matrix = four_tensor2matrix(tqdm)
residual = 10
iter_max = 3000
iter = 0
while residual > error and iter < iter_max:
tpdm_current_iter = matrix2four_tensor(d2_matrix)
opdm = map_tpdm_to_opdm(tpdm_current_iter, N)
one_wedge_eye_mat = four_tensor2matrix(wedge_product(opdm, np.eye(dim)))
tqdm = map_tpdm_to_tqdm(tpdm_current_iter, opdm)
q2_matrix = four_tensor2matrix(tqdm)
# diagonalize both d2 and q2
w, v = np.linalg.eigh(d2_matrix)
wq, vq = np.linalg.eigh(q2_matrix)
# grab the exposing operators for both matrices
exposed_operator = []
for ii in range(w.shape[0]):
if w[ii] < float(-1.0E-13):
# get the exposing operator antisymmeterize
eo = v[:, [ii]].dot(np.conj(v[:, [ii]]).T)
eo_22_tensor = matrix2four_tensor(eo)
eo_22_tensor_antiy = antisymmeterizer(eo_22_tensor)
# add the operator to my list
exposed_operator.append(four_tensor2matrix(eo_22_tensor_antiy))
exposed_operator_q = []
for ii in range(wq.shape[0]):
if wq[ii] < float(-1.0E-13):
# get the exposing operator antisymmeterize
eo = vq[:, [ii]].dot(np.conj(vq[:, [ii]]).T)
eo_22_tensor = matrix2four_tensor(eo)
eo_22_tensor_antiy = antisymmeterizer(eo_22_tensor)
# add the operator to my list
exposed_operator_q.append(four_tensor2matrix(eo_22_tensor_antiy))
# Now we want to find the coleman decomp of each of the exposing operators
num_eo = len(exposed_operator)
zero_contraction_eo = []
for ii in range(num_eo):
eo = matrix2four_tensor(exposed_operator[ii])
eo_0, eo_1, eo_2 = coleman_decomposition(eo)
zero_contraction_eo.append(four_tensor2matrix(eo_2))
num_eo_q = len(exposed_operator_q)
zero_contraction_eo_q = []
for ii in range(num_eo_q):
eo = matrix2four_tensor(exposed_operator_q[ii])
eo_0, eo_1, eo_2 = coleman_decomposition(eo)
zero_contraction_eo_q.append(four_tensor2matrix(eo_2))
# set up system of equations to solve for alpha terms
Amatrix = np.zeros((num_eo + num_eo_q, num_eo + num_eo_q))
bvector = np.zeros((num_eo + num_eo_q, 1))
for i, j in product(range(num_eo), repeat=2):
# alpha coeffs
Amatrix[i, j] = np.trace(
exposed_operator[i].dot(zero_contraction_eo[j])).real
# beta vector component for i-term
if i == j:
bvector[i, 0] = np.trace(
d2_matrix.dot(exposed_operator[i])).real
for i, j in product(range(num_eo), range(num_eo_q)):
# beta coeffs
Amatrix[i, j + num_eo] = np.trace(
exposed_operator[i].dot(zero_contraction_eo_q[j])).real
# now fill in the rows of the Amatrix for the hole exposed operators
for i, j in product(range(num_eo_q), range(num_eo)):
# alpha coeffs with q-exposed operator
Amatrix[i + num_eo, j] = np.trace(
exposed_operator_q[i].dot(zero_contraction_eo[j]).real
)
for i, j in product(range(num_eo_q), repeat=2):
# beta coeffs with q-exposed operator
Amatrix[i + num_eo, j + num_eo] = np.trace(
exposed_operator_q[i].dot(zero_contraction_eo_q[j]).real
)
if i == j:
bvector[i + num_eo, 0] = np.trace(
d2_matrix.dot(exposed_operator_q[i])).real
bvector[i + num_eo, 0] += 2 * np.trace(
exposed_operator_q[i].dot(
eye_wedge_eye_mat)).real
bvector[i + num_eo, 0] -= 4 * np.trace(
exposed_operator_q[i].dot(
one_wedge_eye_mat)).real
# alpha_beta = np.linalg.solve(Amatrix, -bvector)
[alpha_beta, _, _, _] = np.linalg.lstsq(Amatrix, -bvector)
# update the 2-RDM matrix
d2_new = d2_matrix.copy()
for ii in range(num_eo):
d2_new += alpha_beta[ii] * zero_contraction_eo[ii]
for ii in range(num_eo_q):
d2_new += alpha_beta[ii + num_eo] * zero_contraction_eo_q[ii]
# check for conversion of the iterative method
w, v = np.linalg.eigh(d2_new)
residual = np.linalg.norm(w[w < 0])
if disp:
print("iter {:5.0f}\tdiff {:3.10e}\t".format(iter, np.linalg.norm(d2_new - d2_matrix)), end='')
print("trace new {:3.10f}\terror {:3.10e}".format(np.trace(d2_new).real, residual))
d2_matrix = d2_new
iter += 1
tpdm = matrix2four_tensor(d2_matrix)
return tpdm
def unitary_subspace_purification_fixed_initial_trace(tpdm,
N,
error=1.0E-6,
disp=False):
"""
Fixe up the tpdm trace and 1-particle piece and then iterate over the
Coleman decomp of exposed operators
:param tpdm:
:param N:
:param float error:
:param Bool disp: optional argument for displaying updates
:return:
"""
if __debug__:
check_antisymmetric_d2(tpdm)
dim = tpdm.shape[0]
_, _, d2_2 = coleman_decomposition(tpdm)
# check if this thing I grabbed is actually an antisymmetric operator
if __debug__:
check_antisymmetric_d2(d2_2)
assert np.isclose(np.einsum('ijij', d2_2), 0.0)
eye_wedge_eye = wedge_product(np.eye(dim), np.eye(dim)).astype(complex)
# we know d2_0 by fixed trace from particle number
trace_value = N * (N - 1)
d2_0 = ((2 * trace_value) / (dim * (dim - 1))) * eye_wedge_eye
# we know d2_1 should be (N - 1) * opdm
# so grab the opdm first from the noisy tpdm and then purify
opdm = map_tpdm_to_opdm(tpdm, N)
# opdm_new = mazziotti_opdm_purification(opdm, N)
opdm_new = fixed_trace_positive_projection(opdm, N)
# first multiply by N - 1 get back to just contracted. Then another
# for adjusting
one_one_tensor = ((N - 1)**2) * opdm_new
one_one_eye = wedge_product(one_one_tensor, np.eye(dim))
d2_1 = (4 / (dim - 2)) * one_one_eye
d2_1 -= ((4 * trace_value) / (dim * (dim - 2))) * eye_wedge_eye
if __debug__:
d2_1_trial = (4 / (dim - 2)) * wedge_product(
opdm_new - (trace_value / dim) * np.eye(dim), np.eye(dim))
assert np.allclose(d2_1_trial, d2_1)
# we need to check a bunch of stuff about the reconstruct tpdm
# a) does it have all the right symmetry
# b) does it have the right trace and does it contract appropriately
# c) does the d2_0 + d2_1 look like a contracted tpdm_partial fix
tpdm_partial_fix = d2_0 + d2_1 + d2_2
d2_matrix = four_tensor2matrix(tpdm_partial_fix)
if __debug__:
check_antisymmetric_d2(tpdm_partial_fix)
# check conversion back to the tpdm_partial_fix
np.testing.assert_allclose(matrix2four_tensor(d2_matrix),
tpdm_partial_fix)
residual = 10
iter_max = 3000
iter = 0
while residual > error and iter < iter_max:
w, v = np.linalg.eigh(d2_matrix)
exposed_operator = []
for ii in range(w.shape[0]):
if w[ii] < float(-1.0E-13):
if __debug__:
# checks to see if I'm sane?
assert v[:, [ii]].shape == (d2_matrix.shape[0], 1)
assert v[:, [ii]].dot(np.conj(
v[:, [ii]]).T).shape == d2_matrix.shape
# check_antisymmetric_index(v[:, [ii]])
# get the exposing operator antisymmeterize
eo = v[:, [ii]].dot(np.conj(v[:, [ii]]).T)
eo_22_tensor = matrix2four_tensor(eo)
eo_22_tensor_antiy = antisymmeterizer(eo_22_tensor)
if __debug__:
check_antisymmetric_d2(
eo_22_tensor_antiy) # redundant sanity check
# check if operator is hermetian
np.testing.assert_allclose(eo, np.conj(eo).T)
# add the operator to my list
exposed_operator.append(four_tensor2matrix(eo_22_tensor_antiy))
# Now we want to find the coleman decomp of each of the exposing operators
num_eo = len(exposed_operator)
zero_contraction_eo = []
for ii in range(num_eo):
eo = matrix2four_tensor(exposed_operator[ii])
eo_0, eo_1, eo_2 = coleman_decomposition(eo)
zero_contraction_eo.append(four_tensor2matrix(eo_2))
if __debug__:
# check result is sane
assert np.isclose(np.einsum('ijij', eo_0),
np.einsum('ijij', eo))
# check if it contracts to zero
assert np.allclose(np.einsum('ikjk', eo_2),
np.zeros_like(eo_2))
# check if the einsum is correct
assert np.allclose(np.einsum('ikjk', eo),
np.einsum('ikjk', eo_0 + eo_1))
# check if it reconstructs
assert np.allclose(eo_0 + eo_1 + eo_2, eo)
# check if it's hermetian
assert np.allclose(zero_contraction_eo[-1],
np.conj(zero_contraction_eo[-1]).T)
# check if eo_2 is antisymmetric
check_antisymmetric_d2(eo_2)
# set up system of equations to solve for alpha terms
Amatrix = np.zeros((num_eo, num_eo))
bvector = np.zeros((num_eo, 1))
for i, j in product(range(num_eo), repeat=2):
Amatrix[i, j] = np.trace(exposed_operator[i].dot(
zero_contraction_eo[j])).real
if i == j:
bvector[i,
0] = np.trace(d2_matrix.dot(exposed_operator[i])).real
# alpha = np.linalg.solve(Amatrix, -bvector)
[alpha, _, _, _] = np.linalg.lstsq(Amatrix, -bvector)
if __debug__:
assert np.allclose(np.dot(Amatrix, alpha), -bvector)
# update the 2-RDM matrix
d2_new = d2_matrix.copy()
for ii in range(num_eo):
d2_new += alpha[ii] * zero_contraction_eo[ii]
if __debug__:
# check if the new d2_new is orthogonal to zero_contraction
for ii in range(num_eo):
assert np.isclose(np.trace(d2_new.dot(exposed_operator[ii])),
0.0)
# check for conversion of the iterative method
w, v = np.linalg.eigh(d2_new)
residual = np.linalg.norm(w[w < 0])
if disp:
print("iter {:5.0f}\tdiff {:3.10e}\t".format(
iter, np.linalg.norm(d2_new - d2_matrix)),
end='')
print("trace new {:3.10f}\terror {:3.10e}".format(
np.trace(d2_new).real, residual))
d2_matrix = d2_new
iter += 1
tpdm = matrix2four_tensor(d2_matrix)
return tpdm