Hello,
Thanks both of you for the quick answers. I have Phyton3. It was an old line
from another code.
a) Clearly I didn't explain myself correctly about the edges and leads. But
everything is solved now, following Adel's instructions.
b) When I asked about computing it directly from Kwant it was because I read in
another thread that it was going to be in Kwant1.3, but I was not sure if it
was already avalaible. I will "fight" then with the code and will try to use
your guidelines Joseph. Definetively doing it with neighbors will be much
faster than itering the whole system. Will this new version be ready soon? :-)
I will let you know my progress and will attach the code if successful.
Thanks again,
Enrique
El 08/02/2017 a las 5:19, Abbout Adel escribió:
Dear Enrique,
What I see in your program is that you put a potential ''edge_potential=10'' to
help you to color the sites at the edge where you want to put disorder. In your
case, the width is uniform. So you can achieve your goal just by putting a
constraint on the coordinates of your sites: Ex: W-1>site.pos[1]>1.
The most interesting case, is when the shape of your system is arbitrary. To
choose the edge , you do:
for site in sys.expand(graphene.shape(rec, (0, 1))):
if sys.degree(site)<9 : sys[site]=edge_potential
Please, notice that I used <9 and not <=9 as you did in your program (this is
why everything is green in your plot).
To get rid of the sites at the edge, in front of the leads, just do, after
attaching the leads :
for site in sys.leads[0].interface+sys.leads[1].interface:
sys[site]=0
This way, your program will work for arbitrary shape, and you can think how to
put disorder after this.
I hope that this helps.
Adel
On Wed, Feb 8, 2017 at 5:31 AM, enrique colomes
<[email protected]<mailto:[email protected]>> wrote:
Hello,
My name is Enrique and first of all, thanks for the developping of such a
useful tool.
My question is related to that one of the edge potentials. I am trying to
reproduce the Haldane model with disorder in a rectangular scattering region.
My goal is to introduce edge disorder as well as compute the local current
density.
I have two problems:
a) Regarding the edge disorder, I cannot remove the disorder in the edges with
the leads (I saw your recent previous discussion)
b) Is it possible already to compute directly from Kwant the local current
density? If yes, how?
Thanks again,
Enrique
from __future__ import division # so that 1/2 == 0.5, and not 0
from scipy.sparse import spdiags
from math import pi, sqrt, tanh, e
import numpy as np
import kwant
import random
import math
# For computing eigenvalues
import scipy.sparse.linalg as sla
# For plotting
from matplotlib import pyplot
# Define the graphene lattice
graphene = kwant.lattice.honeycomb()
a, b = graphene.sublattices
edge_potential=10
def make_system(L=10, W=10, pot=0.001):
t=1
tt= 0.04 * t
phi=1*pi/2
edge=1 # 1 if there is edge disorder
bulk=0 # 1 if there is bulk disorder
nnn_hoppinga=tt*e**(1j*phi)
nnn_hoppingb=tt*e**(1j*phi)
#### Define the scattering region. ####
def rec(pos):
x, y = pos
return 0 < x < L and 0 < y < W
sys = kwant.Builder()
# w: width and pot: potential maximum of the p-n junction
def potential(site):
(x, y) = site.pos
d = y * 2 + x * 3
return 0
sys[graphene.shape(rec, (1, 1))] = potential
# specify the hoppings of the graphene lattice
nn_hoppings = (((0, 0), a, b), ((0, 1), a, b), ((-1, 1), a, b))
nnn_hoppings_a = (((-1, 0), a, a), ((0, 1), a, a), ((1, -1), a, a))
nnn_hoppings_b = (((1, 0), b, b), ((0, -1), b, b), ((-1, 1), b, b))
sys[[kwant.builder.HoppingKind(*hopping) for hopping in nn_hoppings]] = -t
sys[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_a]] =
-nnn_hoppinga
sys[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_b]] =
-nnn_hoppingb
# Modify the scattering region
if edge==1:
# change the values of the potential at the edge
for site in sys.expand(graphene.shape(rec, (0, 1))):
if sys.degree(site)<=9 and abs(site.pos[0])!=L-4:
#abs(site.pos[0])!=19 execludes the interfaces with the leads
sys[site]=edge_potential
elif bulk==1:
# change the values of the potential at the edge
for site in sys.expand(graphene.shape(rec, (0, 1))):
if sys.degree(site)==9 and abs(site.pos[0])!=19: #abs(site.pos[0])!=19
execludes the interfaces with the leads
sys[site]=edge_potential
#### Define the leads. ####
# left lead
sym0 = kwant.TranslationalSymmetry(graphene.vec((-1, 0)))
sym0.add_site_family(graphene.sublattices[0], other_vectors=[(-1, 2)])
sym0.add_site_family(graphene.sublattices[1], other_vectors=[(-1, 2)])
def lead0_shape(pos):
x, y = pos
return (0 < y < W)
lead0 = kwant.Builder(sym0)
lead0[graphene.shape(lead0_shape, (0, 0))] = -pot
lead0[[kwant.builder.HoppingKind(*hopping) for hopping in nn_hoppings]] = -t
lead0[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_a]]
= -nnn_hoppinga
lead0[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_b]]
= -nnn_hoppingb
# right lead
sym1 = kwant.TranslationalSymmetry(graphene.vec((1, 0)))
sym1.add_site_family(graphene.sublattices[0], other_vectors=[(-1, 2)])
sym1.add_site_family(graphene.sublattices[1], other_vectors=[(-1, 2)])
def lead1_shape(pos):
x, y = pos
return (0 < y < W)
lead1 = kwant.Builder(sym1)
lead1[graphene.shape(lead1_shape, (0, 0))] = pot
lead1[[kwant.builder.HoppingKind(*hopping) for hopping in nn_hoppings]] = -t
lead1[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_a]]
= -nnn_hoppinga
lead1[[kwant.builder.HoppingKind(*hopping) for hopping in nnn_hoppings_b]]
= -nnn_hoppingb
sys.attach_lead(lead1)
sys.attach_lead(lead0)
return sys
# Call the main function if the script gets executed (as opposed to imported).
if __name__ == '__main__':
main()t.show()
def main():
sys = make_system()
# Check that the system looks as intended.
def family_color(site):
#print(sys[site])
if sys[site]==edge_potential:
return 'green'
else: return 'black'
def site_size(site):
if sys[site]==edge_potential:
return 0.35
else:return 0.2
kwant.plot(sys,site_color=family_color,site_size=site_size)
# Finalize the system.
sys = sys.finalized()
# Compute number of neighbors
i=sys.sites.index(graphene(5,6))
all_the_neighbors=sys.graph.out_neighbors(i)
# Call the main function if the script gets executed (as opposed to imported).
# See
<http://docs.python.org/library/__main__.html><http://docs.python.org/library/__main__.html>.
if __name__ == '__main__':
main()
--
Abbout Adel
