import torch
import ipeps.ipeps as ipeps
from groups.pg import make_c4v_symm
import config as cfg
[docs]class IPEPS_C4V(ipeps.IPEPS):
def __init__(self, site, peps_args=cfg.peps_args, global_args=cfg.global_args):
r"""
:param site: on-site tensor
:param peps_args: ipeps configuration
:param global_args: global configuration
:type site: torch.tensor
:type peps_args: PEPSARGS
:type global_args: GLOBALARGS
The index-position convetion for on-site tensor is defined as follows::
u s
|/
l--A--r <=> a[s,u,l,d,r]
|
d
where s denotes physical index, and u,l,d,r label four principal directions
up, left, down, right in anti-clockwise order starting from up.
"""
assert isinstance(site,torch.Tensor), "site is not a torch.Tensor"
super().__init__(dict({(0,0): site}),peps_args=peps_args,\
global_args=global_args)
[docs] def site(self,coord=None):
return self.sites[(0,0)]
[docs] def add_noise(self,noise,symmetrize=False):
r"""
:param noise: magnitude of the noise
:type noise: float
Take IPEPS and add random uniform noise with magnitude ``noise`` to on-site tensor
"""
rand_t = torch.rand( self.site().size(), dtype=self.dtype, device=self.device)
self.sites[(0,0)]= self.site() + noise * rand_t
if symmetrize:
self.sites[(0,0)]= make_c4v_symm(self.site())
def write_to_file(self,outputfile,symmetrize=True,**kwargs):
# symmetrize before writing out
tmp_t= make_c4v_symm(self.site()) if symmetrize else self.site()
tmp_state= IPEPS_C4V(tmp_t)
ipeps.write_ipeps(tmp_state, outputfile,**kwargs)
def extend_bond_dim(state, new_d):
return ipeps.extend_bond_dim(state, new_d)
def to_ipeps_c4v(state, normalize=False):
assert len(state.sites.items())==1, "state has more than a single on-site tensor"
A= next(iter(state.sites.values()))
A= make_c4v_symm(A)
# if normalize: A= A/torch.max(torch.abs(A))
if normalize: A= A/A.norm()
return IPEPS_C4V(A)
[docs]def read_ipeps_c4v(jsonfile, aux_seq=[0,1,2,3], peps_args=cfg.peps_args,\
global_args=cfg.global_args):
r"""
:param jsonfile: input file describing IPEPS_C4V in json format
:param aux_seq: array specifying order of auxiliary indices of on-site tensors stored
in `jsonfile`
:param peps_args: ipeps configuration
:param global_args: global configuration
:type jsonfile: str or Path object
:type aux_seq: list[int]
:type peps_args: PEPSARGS
:type global_args: GLOBALARGS
:return: wavefunction
:rtype: IPEPS_C4V
Parameter ``aux_seq`` defines the expected order of auxiliary indices
in input file relative to the convention fixed in tn-torch::
0
1A3 <=> [up, left, down, right]: aux_seq=[0,1,2,3]
2
for alternative order, eg.
1
0A2 <=> [left, up, right, down]: aux_seq=[1,0,3,2]
3
"""
state= ipeps.read_ipeps(jsonfile, aux_seq=aux_seq, peps_args=peps_args,\
global_args=global_args)
assert len(state.sites.items())==1, "state has more than a single on-site tensor"
return IPEPS_C4V(next(iter(state.sites.values())))