def heis_pbc():
L = 10
chi = 8
dtype = 'float32'
psi0 = qtn.MPS_rand_state(L, chi, cyclic=True, seed=42).astype(dtype)
H = qtn.MPO_ham_heis(L, cyclic=True).astype(dtype)
def norm_fn(psi):
factor = (psi & psi).contract(all, optimize='random-greedy')
return psi / factor**0.5
def loss_fn(psi, H):
k, H, b = qtn.align_TN_1D(psi, H, psi)
energy = (k & H & b).contract(all, optimize='random-greedy')
return energy
en_ex = qu.groundenergy(qu.ham_heis(L, cyclic=True, sparse=True))
return psi0, H, norm_fn, loss_fn, en_ex
def ham_mbl_pbc_complex():
L = 10
chi = 8
dtype = 'complex64'
psi0 = qtn.MPS_rand_state(L, chi, cyclic=True, seed=42).astype(dtype)
ham_opts = {'cyclic': True, 'dh': 0.7, 'dh_dim': 3, 'seed': 42}
H = qtn.MPO_ham_mbl(L, **ham_opts).astype(dtype)
def norm_fn(psi):
factor = (psi.H & psi).contract(all, optimize='random-greedy')
return psi * factor**-0.5
def loss_fn(psi, H):
k, H, b = qtn.align_TN_1D(psi, H, psi.H)
energy = (k & H & b).contract(all, optimize='random-greedy')
return real(energy)
en_ex = qu.groundenergy(qu.ham_mbl(L, sparse=True, **ham_opts))
return psi0, H, norm_fn, loss_fn, en_ex
def test_groundenergy(self, mat_herm_dense, backend):
_, a = mat_herm_dense
ge = qu.groundenergy(a, backend=backend)
assert_allclose(ge, -3)