def test_IndexSum_wrap(self):
d0, n0 = dnm_np_operator('x', L=self.L, index=0)
d1, n1 = dnm_np_operator('x', L=self.L, index=1)
# just to make sure this doesn't throw any exceptions
d0.L = None
d1.L = None
d = do.IndexSum(d0 * d1, wrap=True)
d.L = self.L
d.get_MSC()
d0.L = self.L
d1.L = self.L
d = do.IndexSum(d0 * d1, wrap=True)
d.L = self.L
n = n0.dot(n1)
for i in range(1, self.L - 1):
s = np_sigmai('x', index=i, L=self.L)
n += s.dot(np_sigmai('x', index=i + 1, L=self.L))
s = np_sigmai('x', index=self.L - 1, L=self.L)
n += s.dot(np_sigmai('x', index=0, L=self.L))
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def ising(L):
d = do.IndexSum(
do.Sigmaz(0) * do.Sigmaz(1)) + 0.2 * do.IndexSum(do.Sigmax())
d.L = L
n = np.zeros((2**L, 2**L), dtype=np.complex128)
n += sum(np_sigmaz(i, L).dot(np_sigmaz(i + 1, L)) for i in range(L - 1))
n += 0.2 * sum(np_sigmax(i, L) for i in range(L))
return d, n
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 test_IndexSum_edgelimits(self):
for i in range(self.L):
with self.subTest(ind=i):
d = do.IndexSum(do.Sigmay(L=self.L), min_i=i, max_i=i)
n = np_sigmay(i, self.L)
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def test_IndexSum(self):
for s in ['x', 'y', 'z']:
with self.subTest(s=s):
d, n = dnm_np_operator(s, index=0, L=self.L)
d = do.IndexSum(d)
for i in range(1, self.L):
n = n + np_sigmai(s, index=i, L=self.L)
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
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 test_IndexSum_limits(self):
for low, high in [(1, 1), (1, 3), (0, 3), (0, 0)]:
with self.subTest(low=low, high=high):
d = do.Sigmay(L=self.L)
d = do.IndexSum(d, min_i=low, max_i=high)
n = np_sigmay(low, self.L)
for i in range(low + 1, high + 1):
n += np_sigmay(i, self.L)
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
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 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_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_indexSumofProd(self):
for name, ol in self.op_lists.items():
with self.subTest(ops=name):
d = do.IndexSum(do.Product(s() for s in ol[1]))
n = ol[0][0](0, config.global_L)
for o in ol[0][1:]:
n = n.dot(o(0, config.global_L))
for i in range(1, config.global_L):
n_tmp = ol[0][0](i, config.global_L)
for o in ol[0][1:]:
n_tmp = n_tmp.dot(o(i, config.global_L))
n += n_tmp
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def test_indexSumofSumofProduct(self):
for name, ol in self.op_lists.items():
with self.subTest(ops=name):
d = do.IndexSum(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))
for i in range(1, config.global_L - 1):
for o in ol[0]:
s = o(i, config.global_L)
n += s.dot(o(i + 1, config.global_L))
r, msg = check_dnm_np(d, n)
self.assertTrue(r, msg=msg)
def test_IndexSum_exceptions(self):
for low, high in [(1, 0), (0, self.L + 1), (-1, 0)]:
with self.subTest(low=low, high=high):
d = do.Sigmay(L=self.L)
with self.assertRaises(ValueError):
do.IndexSum(d, min_i=low, max_i=high)