def test_global_L(self):
config.global_L = 10
test_ops = OrderedDict([
('sx', do.Sigmax),
('sy', do.Sigmay),
('sz', do.Sigmaz),
('ident', do.Identity),
('zero', do.Zero),
('sum', lambda: do.Sum([do.Sigmax()])),
('product', lambda: do.Product([do.Sigmax()])),
('indexsum', lambda: do.IndexSum(do.Sigmax())),
('indexproduct', lambda: do.IndexProduct(do.Sigmax())),
])
for op, d in test_ops.items():
with self.subTest(op=op):
self.assertEqual(d().L, 10)
v = build_state()
self.assertEqual(v.size, 2**10)
config.global_L = None
for op, d in test_ops.items():
with self.subTest(op=op):
self.assertIs(d().L, None)
with self.assertRaises(ValueError):
build_state()
def longrange(L):
d = do.Sum(
do.IndexSum(do.Sigmaz(0) * do.Sigmaz(i)) for i in range(1, L - 1))
d += 0.5 * do.IndexSum(do.Sigmax(0) * do.Sigmax(1))
d += 0.1 * do.Sum(
do.IndexSum(s()) for s in (do.Sigmax, do.Sigmay, do.Sigmaz))
d.L = L
n = np.zeros((2**L, 2**L), dtype=np.complex128)
for j in range(1, L - 1):
n += sum(
np_sigmaz(i, L).dot(np_sigmaz(i + j, L)) for i in range(L - j))
n += 0.5 * sum(
np_sigmax(i, L).dot(np_sigmax(i + 1, L)) for i in range(L - 1))
n += 0.1 * sum(np_sigmai(t, i, L) for i in range(L) for t in 'xyz')
return d, n
def XXYY(L):
d = do.IndexSum(do.Sum(s(0) * s(1) for s in [do.Sigmax, do.Sigmay]))
d.L = L
n = np.zeros((2**L, 2**L), dtype=np.complex128)
for s in 'xy':
n += sum(
np_sigmai(s, i, L).dot(np_sigmai(s, i + 1, L))
for i in range(L - 1))
return d, n
def test_generatorSum(self):
for name, ol in self.op_lists.items():
with self.subTest(ops=name):
d = do.Sum(s() for s in ol[1])
n = ol[0][0](0, config.global_L)
for o in ol[0][1:]:
n += o(0, config.global_L)
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def setUp(self):
self.L = 4
self.cuts = [0, 1, 2, 4]
self.states = OrderedDict([
('product0', build_state(L=self.L)),
('product1',
build_state(L=self.L, state=int(0.8675309 * (2**self.L)))),
('random', build_state(L=self.L, state='random'))
])
H = do.IndexSum(do.Sum(s(0) * s(1) for s in (do.Sigmax, do.Sigmaz)))
H.L = self.L
self.states['evolved'] = H.evolve(self.states['product1'], 1.0)
def test_SumofProduct(self):
for name, ol in self.op_lists.items():
with self.subTest(ops=name):
d = do.Sum(s(0) * s(1) for s in ol[1])
s = ol[0][0](0, config.global_L)
n = s.dot(ol[0][0](1, config.global_L))
for o in ol[0][1:]:
s = o(0, config.global_L)
n += s.dot(o(1, config.global_L))
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def test_indexSumofSum(self):
for name, ol in self.op_lists.items():
with self.subTest(ops=name):
d = do.IndexSum(do.Sum(s() for s in ol[1]))
n = ol[0][0](0, config.global_L)
for o in ol[0][1:]:
n += o(0, config.global_L)
for i in range(1, config.global_L):
for o in ol[0]:
n += o(i, config.global_L)
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def test_recursive(self):
s = [do.Sigmax(i) for i in range(3)]
s1 = s[0] * s[1] * s[2]
s2 = s[0] * (s[1] * s[2])
self.assertEqual(s1, s2)
self.assertEqual(len(s1.terms), 3)
self.assertEqual(len(s2.terms), 3)
s1 = s[0] * s[1] * s[2] * s[0]
s2 = (s[0] * s[1]) * (s[2] * s[0])
self.assertEqual(s1, s2)
self.assertEqual(len(s1.terms), 4)
self.assertEqual(len(s2.terms), 4)
with self.assertRaises(ValueError):
do.Sum(terms=[])
def test_sum_one(self):
d = do.Sum([do.Sigmax()])
self.assertEqual(do.Sigmax(), d)