def build_rotation(hi, basis):
localop = op.LocalOperator(hi, constant=1.0)
U_X = 1.0 / (ma.sqrt(2)) * np.asarray([[1.0, 1.0], [1.0, -1.0]])
U_Y = 1.0 / (ma.sqrt(2)) * np.asarray([[1.0, -1j], [1.0, 1j]])
N = hi.size
assert len(basis) == hi.size
for j in range(hi.size):
if basis[j] == "X":
localop *= op.LocalOperator(hi, U_X, [j])
if basis[j] == "Y":
localop *= op.LocalOperator(hi, U_Y, [j])
return localop
def load(path_to_samples, path_to_bases):
tsamples = np.loadtxt(path_to_samples)
fin_bases = open(path_to_bases, 'r')
lines = fin_bases.readlines()
N = (len(lines[0].strip('\n')))
# Create the hilbert space
# TODO remove Hypercube here and put customgraph
g = gr.Hypercube(length=N, n_dim=1)
hi = hs.Qubit(graph=g)
bases = []
for b in lines:
basis = ""
assert (len(b) == N + 1)
for j in range(N):
basis += b[j]
bases.append(basis)
index_list = sorted(range(len(bases)), key=lambda k: bases[k])
bases.sort()
training_samples = []
training_bases = []
for i in range(len(tsamples)):
training_samples.append(tsamples[index_list[i]].tolist())
U_X = (1. / (m.sqrt(2)) * np.asarray([[1., 1.], [1., -1.]])).tolist()
U_Y = (1. / (m.sqrt(2)) * np.asarray([[1., -1j], [1., 1j]])).tolist()
rotations = []
tmp = ''
b_index = -1
for b in bases:
if (b != tmp):
tmp = b
localop = op.LocalOperator(hi, 1.0)
for j in range(N):
if (tmp[j] == 'X'):
localop *= op.LocalOperator(hi, U_X, [j])
if (tmp[j] == 'Y'):
localop *= op.LocalOperator(hi, U_Y, [j])
rotations.append(localop)
b_index += 1
training_bases.append(b_index)
return hi, tuple(rotations), training_samples, training_bases