File size: 2,857 Bytes
6288873 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | import jax.numpy as jnp
from varipeps import varipeps_config
from varipeps.ctmrg import calc_ctmrg_env, CTMRGNotConvergedError
from varipeps.peps import PEPS_Unit_Cell
from . import overlap_single_site
from . import overlap_four_sites
overlap_mapping = {
(1, 1): overlap_single_site.Overlap_Single_Site,
(2, 2): overlap_four_sites.Overlap_Four_Sites_Square,
}
def calculate_overlap(
unitcell_A, unitcell_B, chi, max_chi, *, test_automatic_overlap_conv=True
):
structure_A = tuple(tuple(i) for i in unitcell_A.data.structure)
structure_B = tuple(tuple(i) for i in unitcell_B.data.structure)
if structure_A != structure_B:
raise ValueError("Structure of both unit cells have to be the same.")
size = unitcell_A.get_size()
num_tensors = size[0] * size[1]
overlap_func = overlap_mapping[size].calc_overlap
unitcell_A = unitcell_A.convert_to_full_transfer()
unitcell_B = unitcell_B.convert_to_full_transfer()
norm_A = overlap_func(unitcell_A)
norm_B = overlap_func(unitcell_B)
overlap_tensors = [
type(t).from_tensor(
t.tensor / norm_A ** (1 / (2 * num_tensors)), t.d, t.D, chi, max_chi=max_chi
)
for t in unitcell_A.get_unique_tensors()
]
for i, e in enumerate(overlap_tensors):
e.tensor_conj = unitcell_B.get_unique_tensors()[i].tensor.conj() / norm_B ** (
1 / (2 * num_tensors)
)
overlap_unitcell = PEPS_Unit_Cell.from_tensor_list(overlap_tensors, structure_A)
if test_automatic_overlap_conv:
tmp_max_steps = varipeps_config.ctmrg_max_steps
tmp_fail = varipeps_config.ctmrg_fail_if_not_converged
varipeps_config.ctmrg_fail_if_not_converged = False
varipeps_config.ctmrg_max_steps = 10
overlap_unitcell, _ = calc_ctmrg_env(
[i.tensor for i in overlap_tensors], overlap_unitcell
)
overlap_AB = overlap_func(overlap_unitcell)
varipeps_config.ctmrg_max_steps = 1
for count in range(tmp_max_steps):
old_overlap_AB = overlap_AB
overlap_unitcell, _ = calc_ctmrg_env(
[i.tensor for i in overlap_tensors], overlap_unitcell
)
overlap_AB = overlap_func(overlap_unitcell)
if (
jnp.abs(overlap_AB - old_overlap_AB)
<= varipeps_config.ctmrg_convergence_eps
):
varipeps_config.ctmrg_fail_if_not_converged = tmp_fail
varipeps_config.ctmrg_max_steps = tmp_max_steps
break
if count == (tmp_max_steps - 1):
raise CTMRGNotConvergedError
else:
overlap_unitcell, _ = calc_ctmrg_env(
[i.tensor for i in overlap_tensors], overlap_unitcell
)
overlap_AB = overlap_func(overlap_unitcell)
return overlap_AB
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