def rand_invar(cls, n, phys_dim=2, dtype=float, **mera_opts):
"""Generate a random translational and scale invariant MERA.
"""
d = phys_dim
iso = qu.rand_iso(d**2, d, dtype=dtype)
iso.shape = (d, d, d)
uni = qu.rand_iso(d**2, d**2, dtype=dtype)
uni.shape = (d, d, d, d)
return cls(n, uni, iso, phys_dim=d, **mera_opts)
def test_multisubsystem(self):
qu.seed_rand(42)
dims = [2, 2, 2]
IIX = qu.ikron(qu.rand_herm(2), dims, 2)
dcmp = qu.pauli_decomp(IIX, mode='c')
for p, x in dcmp.items():
if x == 0j:
assert (p[0] != 'I') or (p[1] != 'I')
else:
assert p[0] == p[1] == 'I'
K = qu.rand_iso(3 * 4, 4).reshape(3, 4, 4)
KIIXK = qu.kraus_op(IIX, K, dims=dims, where=[0, 2])
dcmp = qu.pauli_decomp(KIIXK, mode='c')
for p, x in dcmp.items():
if x == 0j:
assert p[1] != 'I'
else:
assert p[1] == 'I'
def gen_isos():
while True:
iso = qu.rand_iso(d**2, d, dtype=dtype)
iso.shape = (d, d, d)
yield iso
def gen_unis():
while True:
uni = qu.rand_iso(d**2, d**2, dtype=dtype)
uni.shape = (d, d, d, d)
yield uni