def rtransmat(self,m,use_qn=True): #should be discarded
rho_block_dict={}
for env_sec,indices in self.rsector_indices.items():
if indices: #
psi0_sector=self.restricted_psi0[indices]
psi0_sector=psi0_sector.reshape([-1,len(self.rhgen.basis_by_sector[env_sec])],order="C")
rho_block_dict[env_sec]=np.dot(psi0_sector.transpose(),psi0_sector.conjugate())
possible_eigenstates=[]
for sector,rho_block in rho_block_dict.items():
evals,evecs=np.linalg.eigh(rho_block)
current_sector_basis=self.rhgen.basis_by_sector[sector]
for eval,evec in zip(evals,evecs.transpose()):
possible_eigenstates.append((eval,evec,sector,current_sector_basis))
possible_eigenstates.sort(reverse=True,key=lambda x:x[0])
my_m=min(len(possible_eigenstates),m)
transformation_matrix=lil_matrix((self.rhgen.D,my_m),dtype='d') #
self.rnew_sector_array=np.zeros((my_m,),dtype='d')
possible_eigenstates=possible_eigenstates[:my_m]
possible_eigenstates.sort(reverse=False,key=lambda x:x[3])
for i,(eval,evec,sector,current_sector_basis) in enumerate(possible_eigenstates):
for j,v in zip(current_sector_basis,evec):
transformation_matrix[j,i]=v #
self.rnew_sector_array[i]=sector
self.rnew_basis_by_sector=index_map(self.rnew_sector_array)
transformation_matrix=transformation_matrix.tocsr()
return transformation_matrix
def __init__(self,terms,L,d=2,part='left',fermi=False,sfermi=False,sectors=np.array([0.5,-0.5])): self.l=1;self.d=d;self.D=self.d self.H=np.zeros([self.d,self.d]) self.terms=terms;self.pterms=[] self.L=L;self.part=part self.single_site_sectors=sectors self.basis_sector_array=copy(self.single_site_sectors) self.basis_by_sector=index_map(self.basis_sector_array) if fermi==True: self.I=Z elif sfermi==True: self.I=Zs else: self.I=identity(self.d) if self.part=='left': for term in self.terms: if len(term.ops)==1 and (term.ops[0].site is None or term.ops[0].site==1): self.H+=term.ops[0].mat*term.param elif len(term.ops)>1 and (term.ops[0].site is None or term.ops[0].site==1): pterm=deepcopy(term) pterm.ops[0].site=1 pterm.current_index=0 pterm.current_op=deepcopy(pterm.ops[0]) for i in range(len(pterm.dists)): #if sites are given,this step can be skipped pterm.ops[i+1].site=pterm.dists[i]+pterm.ops[i].site self.pterms.append(pterm) else: for term in self.terms: if len(term.ops)==1 and (term.ops[-1].site is None or term.ops[-1].site==self.L): self.H+=term.ops[-1].mat*term.param elif len(term.ops)>1 and (term.ops[-1].site is None or term.ops[-1].site==self.L): pterm=deepcopy(term) pterm.ops[-1].site=self.L pterm.current_index=len(term.ops)-1 pterm.current_op=deepcopy(pterm.ops[-1]) for i in range(len(pterm.dists)): pterm.ops[-i-2].site=pterm.ops[-i-1].site-pterm.dists[-i-1] self.pterms.append(pterm)
def enlarge(self): self.l+=1 if self.part=='left': self.H=kron(self.H,identity(self.d)) pts=[] for pterm in self.pterms: if pterm.ops[pterm.current_index+1].site==self.l: pterm.current_index+=1 pterm.current_op.mat=kron(pterm.current_op.mat,pterm.ops[pterm.current_index].mat) #other attribute? else: pterm.current_op.mat=kron(pterm.current_op.mat,self.I) if pterm.current_index<len(pterm.ops)-1: pts.append(pterm) else: self.H+=pterm.current_op.mat*pterm.param self.pterms=deepcopy(pts) for term in self.terms: if len(term.ops)==1 and (term.ops[0].site is None or term.ops[0].site==self.l): self.H+=kron(identity(self.D),term.ops[0].mat)*term.param elif len(term.ops)>1 and (term.ops[0].site is None or term.ops[0].site==self.l): pterm=deepcopy(term) pterm.current_index=0 pterm.current_op=deepcopy(pterm.ops[0]) pterm.current_op.mat=kron(identity(self.D),pterm.current_op.mat) pterm.ops[0].site=self.l for i in range(len(pterm.dists)): pterm.ops[i+1].site=pterm.dists[i]+pterm.ops[i].site self.pterms.append(pterm) self.basis_sector_array=np.add.outer(self.basis_sector_array,self.single_site_sectors).flatten() else: self.H=kron(identity(self.d),self.H) pts=[] for pterm in self.pterms: if pterm.ops[pterm.current_index-1].site==self.L-self.l+1: pterm.current_index-=1 pterm.current_op.mat=kron(pterm.ops[pterm.current_index].mat,pterm.current_op.mat) else: pterm.current_op.mat=kron(self.I,pterm.current_op.mat) if pterm.current_index>0: pts.append(pterm) else: self.H+=pterm.current_op.mat*pterm.param self.pterms=deepcopy(pts) for term in self.terms: if len(term.ops)==1 and (term.ops[-1].site is None or term.ops[-1].site==self.L-self.l+1): self.H+=kron(term.ops[-1].mat,identity(self.D))*term.param elif len(term.ops)>1 and (term.ops[-1].site is None or term.ops[-1].site==self.L-self.l+1): pterm=deepcopy(term) pterm.current_index=len(pterm.ops)-1 pterm.current_op=deepcopy(pterm.ops[-1]) pterm.current_op.mat=kron(pterm.current_op.mat,identity(self.D)) pterm.ops[-1].site=self.L-self.l+1 for i in range(len(pterm.dists)): pterm.ops[-i-2].site=pterm.ops[-i-1].site-pterm.dists[-i-1] self.pterms.append(pterm) self.basis_sector_array=np.add.outer(self.single_site_sectors,self.basis_sector_array).flatten() self.basis_by_sector=index_map(self.basis_sector_array) self.D*=self.d
