Summary

Code to calculate dispersion, density of state (DOS), local density of state (LDOS) of decorated square lattices solving tight binding models.

Installation

git clone https://github.com/kumarjnc/DECORATED_LATTICES.git

Example

Band dispersion of Decorated lattice

import numpy as np 
from numpy import tile
import matplotlib.pyplot as plt
from scipy import linalg as LA
import math,cmath
from scipy import linalg as LA
import math,cmath
pi = math.pi
cos = math.cos
sin = math.sin
exp=np.exp
sqrt = math.sqrt
log=np.log
from numpy.linalg import inv
from numpy import zeros
import main
import params
main.band(params.t1,params.t2,params.a,params.Nk,params.density,params.mass,params.dim,params.totomega,params.m,params.sigma,square=True)

Visualising dispersion, DOS and LDOS

Reshaping the output

dispersion_data=np.loadtxt("dispersion_lieb.dat")
kvecs = np.loadtxt("kvecs.dat")
X,Y=np.meshgrid(kvecs[:,0],kvecs[:,1])
Zup=dispersion_data[:,0].reshape(Nk,Nk)
Zdw=dispersion_data[:,1].reshape(Nk,Nk)
Zflat=dispersion_data[:,2].reshape(Nk,Nk)
Ztop=dispersion_data[:,3].reshape(Nk,Nk)

3d Plot interactive

%matplotlib notebook
from matplotlib import interactive
interactive(True)
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter

fig = plt.figure()
ax = fig.gca(projection='3d')
# Plot the surface.
ax.set_xlabel('$k_x$')
ax.set_ylabel('$k_y$')
ax.set_zlabel('$E$')


surf = ax.plot_surface(X, Y,Zup, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
surf = ax.plot_surface(X, Y,Zdw, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
surf = ax.plot_surface(X, Y,Zflat, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
surf = ax.plot_surface(X, Y,Ztop, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
plt.show()