def plot_local_dos(bar, energy, disorder, probability, seed):
smatrix = kwant.smatrix(bar, energy, args = [disorder, probability, seed])
print('seed : {}, transmission: {}'.format(seed, smatrix.transmission(1, 0)))
local_dos = kwant.ldos(bar, energy=energy, args=[disorder, probability, seed])
kwant.plot(bar, #site_color = -local_dos,
site_color=np.minimum(-np.log(local_dos), 10*np.ones_like(local_dos)),
hop_color='white', cmap='afmhot')
def ldos(cishu):
en = 0.4
salt = cishu + random.random() * 100
sys = make_system2(width, length, str(salt))
local_dos = kwant.ldos(sys, en)
ld = local_dos.reshape(-1, 2)
coord = np.array([sys.pos(i) for i in range(ld.shape[0])])
ans = np.concatenate((coord, ld), axis=1)
myDict = {'ans': ans}
completeName = os.path.join('E:/dwell/11/', str(cishu) + ".mat")
sio.savemat(completeName, myDict, oned_as='row')
def density_of_states(sys, energies, L, W, show=False, J="N/A", spin="N/A"):
"""Calculate the density of states"""
dos = []
for energy in energies:
dos.append(np.sum(kwant.ldos(sys, energy)))
dos = [x / (W * L) for x in dos]
if show is True:
plt.figure()
plt.title("Density of States (J=" + str(J) + ", Spin=" + spin + ")")
plt.plot(energies, dos)
plt.xlabel("Energies [t]")
plt.ylabel("Density of States [Energy^-1 m^-2]")
plt.grid(True)
plt.show()
return dos
def density_of_states(sys, energies, L, W, show=False):
"""Calculate the density of states in system"""
dos = []
for energy in energies:
dos.append(np.sum(kwant.ldos(sys, energy)))
dos = [x / (W * L) for x in dos]
if show is True:
plt.figure()
plt.title("Density of States")
plt.plot(energies, dos)
plt.xlabel("Energies [t]")
plt.ylabel("Density of States [t^-1 a^-2]")
plt.grid(True)
plt.show()
return dos
def TM(cishu):
en = 0.4
salt = cishu + random.random() * 100
syst = make_system(width, length, str(salt))
attach_lead(syst)
sys = syst.finalized()
wf = kwant.wave_function(sys, en)(0)
gf_mode = kwant.smatrix(sys, en).submatrix(1, 0)
# s=np.linalg.svd(gf_mode, full_matrices=False, compute_uv=False) #u, s, vh
ldos = kwant.ldos(sys, en)
if cishu == 0:
coord = np.array([sys.pos(i) for i in range(ldos.shape[0])])
sio.savemat('E:/dwell3/703/coord.mat', {'coord': coord}, oned_as='row')
myDict = {'gf_mode': gf_mode, 'wf': wf, 'ld': ldos} #'s':s,
completeName = os.path.join('E:/dwell3/703/', str(cishu) + ".mat")
sio.savemat(completeName, myDict, oned_as='row')
def tau_n(cishu):
en = 0.4
salt = cishu + random.random() * 1000
sys = make_system(length, width, str(salt))
gf_mode = kwant.smatrix(sys, en).submatrix(1, 0)
# s=np.linalg.svd(gf_mode, full_matrices=False, compute_uv=False) #u, s, vh
wf = kwant.wave_function(sys, en)(0)
# kwant.plotter.map(sys, (abs(wf[14])**2),num_lead_cells=5,fig_size=(15, 10),colorbar=False)
ldos = kwant.ldos(sys, en)
if cishu == 0:
coord = np.array([sys.pos(i) for i in range(ldos.shape[0])])
sio.savemat('E:/dwell3/167/coord.mat', {'coord': coord}, oned_as='row')
myDict = {'gf_mode': gf_mode, 'wf': wf, 'ld': ldos}
completeName = os.path.join('E:/dwell3/167/', str(cishu) + ".mat")
sio.savemat(completeName, myDict, oned_as='row')
def TM(cishu):
salt = cishu + random.random() * 100
syst = make_system(width, length, str(salt))
attach_lead(syst)
sys = syst.finalized()
#kwant.plot(sys, fig_size=(10, 3))
wf = kwant.wave_function(sys, 0.4)(0)
# kwant.plotter.map(sys, (abs(wf[14])**2),num_lead_cells=5,fig_size=(15, 10),colorbar=False)
#
# t=kwant.smatrix(sys,.35).transmission(1,0)
gf_mode = kwant.smatrix(sys, 0.4).submatrix(1, 0)
# s=np.linalg.svd(gf_mode, full_matrices=False, compute_uv=False) #u, s, vh
ldos = kwant.ldos(sys, 0.4)
if cishu == 0:
coord = np.array([sys.pos(i) for i in range(ldos.shape[0])])
sio.savemat('E:/dwell3/327/coord.mat', {'coord': coord}, oned_as='row')
myDict = {'gf_mode': gf_mode, 'wf': wf, 'ld': ldos} #'s':s,
completeName = os.path.join('E:/dwell3/327/', str(cishu) + ".mat")
sio.savemat(completeName, myDict, oned_as='row')
def local_dos(sys, energies, L, W, show=False):
"""Calculate the local density of states of the system. Returns
the total ldos of the system, spin up ldos, and spin down
ldos as numpy arrays."""
ldos = np.empty((0, (L + 1) * (W + 1)))
ldos_sys_p = np.empty((0, (L + 1) * (W + 1)))
ldos_sys_m = np.empty((0, (L + 1) * (W + 1)))
for energy in energies:
ldos_e = kwant.ldos(sys, energy)
# Extract the individual spin up and spin down ldos components.
ldos_sys_p_e = ldos_e.reshape(-1, 2)[:, 0]
ldos_sys_m_e = ldos_e.reshape(-1, 2)[:, 1]
# Calculate ldos per site, by summing spin up and
# spin down components.
ldos_e = np.sum(ldos_e.reshape(-1, 2), axis=1)
ldos = np.append(ldos, [ldos_e], axis=0)
ldos_sys_p = np.append(ldos_sys_p, [ldos_sys_p_e], axis=0)
ldos_sys_m = np.append(ldos_sys_m, [ldos_sys_m_e], axis=0)
if show is True:
kwant.plotter.map(sys, ldos_sys_p, num_lead_cells=3)
kwant.plotter.map(sys, ldos_sys_m, num_lead_cells=3)
kwant.plotter.map(sys, ldos, num_lead_cells=3)
return ldos, ldos_sys_p, ldos_sys_m
import kwant
from matplotlib import pyplot
def stadium(position):
x, y = position
x = max (abs(x)-7, 0)
return x**2 + y**2 < 10**2
sys = kwant.Builder()
sqlat = kwant.lattice.square()
sys[sqlat.shape(stadium, (0, 0))] = 4
sys[sqlat.neighbors()] = -1
lead_symmetry = kwant.TranslationalSymmetry([0, -1])
for start, end in [(-9, -3), (4, 10)]:
lead = kwant.Builder(lead_symmetry)
lead[(sqlat(x, 0) for x in range(start, end))] = 4
lead[sqlat.neighbors()] = -1
sys.attach_lead(lead)
sys = sys.finalized()
energies = [0.5 + 1e-4*i for i in range(300)]
conductances = [kwant.smatrix(sys, en).transmission(1, 0)
for en in energies]
local_dos = kwant.ldos(sys, energy=0.4)
pyplot.plot(energies, conductances)
pyplot.show()
kwant.plotter.map(sys, local_dos, num_lead_cells=10)
def DOS(cishu): # ONLY FOR UNITARY SYSTEM
return sum(kwant.ldos(sys, ens[cishu]))
#lead[lat.neighbors()]=-1/n2**2
#sys.attach_lead(lead)
sys = sys.finalized()
#en=1
energies = [1 + 1e-3 * t for t in range(100)]
shape = []
final_T = []
final_tau_sqrt = []
#save_path = 'E:/kwant/23/'
ld = []
kwant.plot(sys)
for cishu in np.arange(0, 2000):
salt = str(cishu + random.random())
# temp=[kwant.greens_function(sys,en).submatrix(1,0)[30,30] for en in energies]
# plt.plot(energies,abs(np.array(temp)**2))
aa = kwant.ldos(sys, 1)
temp = np.mean(kwant.ldos(sys, 1).reshape((length + 1 + 40, width - 1)), 1)
ld.append(temp)
# kwant.smatrix(sys,1).lead_info[0].velocities
# gf_mode=kwant.smatrix(sys,2.5).submatrix(1,0)
# try:
# u, s, v = np.linalg.svd(gf_mode, full_matrices=True)
# wf=kwant.wave_function(sys,en)(0)
# T=kwant.smatrix(sys,en).transmission(1,0)
# completeName = os.path.join(save_path, str(cishu)+".mat")
# myDict = {'u':u,'v':v,'s':s,'wf':wf,'T':T,'gf_mode':gf_mode}
# ## myDict['u'] = u
# sio.savemat(completeName,myDict,oned_as='row')
# except:
# continue
param_pot_2=param_pot(theta_min=-90/180*pi,theta_max=-45/180*pi,choice_pot=choice_pot_2)
H=make_system(param, param_pot_1,param_pot_2)
kwant.plot(H)
Hf=H.finalized()
## potential plot
if param.potential_activated==1:
vals=[potential(Hf.sites[n], phi,param_pot_1,param_pot_2) for n in range(Hf.graph.num_nodes)]
kwant.plotter.map(Hf, vals)
## density of state plot
local_dos = kwant.ldos(Hf, energy=.05,args=[phi,param_pot_1,param_pot_2])
kwant.plotter.map(Hf, local_dos, num_lead_cells=10)
#kwant.plotter.savefig('test.png')
# current density plot
wfs = kwant.wave_function(Hf, energy=0.05,args=[phi,param_pot_1,param_pot_2]) # to obtain the wave functions of the system
J0 = kwant.operator.Current(Hf)
wf_left = wfs(0)
current = sum(J0(p) for p in wf_left)
kwant.plotter.current(Hf, current, cmap='viridis')
#%% [markdown]
# ## Analysis of the transmission
#%%
