# Add the root path of the pygra library
import os ; import sys ; sys.path.append(os.environ['PYGRAROOT'])
import numpy as np
from pygra import geometry
from pygra import hamiltonians
from pygra import ribbon
from pygra import multilayers
g = multilayers.get_geometry("AB",armchair=False) # bilayer AB geometry
g = ribbon.bulk2ribbon(g,n=20,clean=False) # get the geometry of a ribbon
#g = g.supercell(3)
#g.write() ; exit()
fun = multilayers.multilayer_hopping(ti=0.3) # function for the hopping
h = g.get_hamiltonian(has_spin=False,fun=fun) # create Hamiltonian
def ff(r): return r[2]*0.2 # interlayer bias
h.shift_fermi(ff) # add electric field
h.get_bands()
# Add the root path of the pygra library
import os
import sys
sys.path.append(os.environ['PYGRAROOT'])
import numpy as np
from pygra import geometry
from pygra import hamiltonians
from pygra import ribbon
from pygra import multilayers
g = multilayers.get_geometry("AB", armchair=False) # bilayer AB geometry
g = ribbon.bulk2ribbon(g, n=20, clean=False) # get the geometry of a ribbon
#g = g.supercell(3)
#g.write() ; exit()
fun = multilayers.multilayer_hopping(ti=0.3) # function for the hopping
h = g.get_hamiltonian(has_spin=False, fun=fun) # create Hamiltonian
def ff(r):
return r[2] * 0.2 # interlayer bias
h.shift_fermi(ff) # add electric field
h.get_bands()
import os
import sys
sys.path.append(os.environ["PYGRAROOT"])
from pygra import geometry
import numpy as np
from pygra import ribbon
from pygra import indexing
g = geometry.honeycomb_lattice() # get the 2D geometry of a honeycomb lattice
g = ribbon.bulk2ribbon(g,n=100) # generate a ribbon
h = g.get_hamiltonian(has_spin=False,is_sparse=True) # get the Hamiltonian
# Here you could use any 1d Hamiltonian you want
# Alternatively, you can generate 1D Hamiltonians from a 2D one using
# h = ribbon.hamiltonian_ribbon(h,n=10) # (more expensive though)
indb = indexing.bulk1d(h.geometry) # 1 for bulk sites, 0 for edges
def frand():
"""This function generates states located in the bulk"""
return (np.random.random(len(h.geometry.r))-0.5)*indb
h0 = h.copy() # make a copy of the Hamiltonian
def getdos(b=0.03):
"""Compute DOS for a certain magnetic field"""
h = h0.copy()
h.add_peierls(b) # add magnetic field
return h.get_dos(use_kpm=True, # use the KPM mode
scale=4.0, # scale of the problem
frand=frand, # random vector generator for KPM
delta=0.04, # smearing of the distribution
# Add the root path of the pygra library
import os ; import sys ; sys.path.append(os.environ['PYGRAROOT'])
import numpy as np
from pygra import geometry
from pygra import sculpt
from pygra import ribbon
g = geometry.kagome_lattice()
#g = geometry.honeycomb_lattice()
g.has_sublattice = True
g.sublattice = [-1,1,0]
g = ribbon.bulk2ribbon(g,n=20)
h = g.get_hamiltonian()
ms = [] # zeeman fields
m1 = np.array([1.,0.,0.])
m2 = np.array([-.5,np.sqrt(3.)/2.,0.])
m3 = np.array([-.5,-np.sqrt(3.)/2.,0.])
mm = 3.0
for (r,s) in zip(g.r,g.sublattice):
if r[1]<0.0:
if s==-1: ms.append(m1*mm)
if s==1: ms.append(m2*mm)
if s==0: ms.append(m3*mm)
else: ms.append([0.,0.,0.])
# swave
def fs(r):
if r[1]>0.0: return 0.3
else: return 0.0
h.add_magnetism(ms)
h.add_swave(fs)
h.shift_fermi(fs)