Mailman 3 March 2017 - Kwant-discuss

periodic boundary conditions on the lead
by Sergey Slizovskiy 21 Mar '17

21 Mar '17

Dear Colleagues, There has already been a discussion on this subject back in 2014, (https://www.mail-archive.com/kwant-discuss@kwant-project.org/msg00124.html) but I am not quite sure I understand the proper solution. I made a lead with rectangular unit cell and naive attempt to make periodic boundary conditions gives a error: "Further-than-nearest-neighbor cells are connected by hopping". The only solution I can think of, is to introduce an auxiliary 1-D lattice made of the atoms along the edge and introduce hopping from this 1D chain to the edge atoms of 2D lead. Hope it will work. Are there any better solutions? Thanks, Sergey

2 1

lead periodic boundary conditions
by Sergey Slizovskiy 20 Mar '17

20 Mar '17

Dear all, Can anyone send an example of setting periodic boundary conditions on a lead, please. E.g. on a simplest square lattice. Is defining a long unit cell the only solution? Thanks, Sergey

1 0

How to reduce memory requirement
by Li Mingkai 16 Mar '17

16 Mar '17

Dear all, I try to build a bulk transport system with periodic boundary condition by 40 * 40 * 40 sites. It requests over 2 GB memory during transmission calculation. I curious why it produces so large memory requirement. Since I'm going to expand the system up to 50 times, I want to know any way to reduce the memory requirement and increase calculation speed. I'm using kwant 1.1.2 and MUMPS with default PORD ordering. The system building code is syst = kwant.Builder(kwant.TranslationalSymmetry(lat.vec((0, cube.NY, 0)), lat.vec((0, 0, cube.NZ)))) for i in range(cube.NX): for j in range(cube.NY): for k in range(cube.NZ): syst[(lat(i, j, k))] = -cube.data[i, j, k] + 6 * t syst[lat.neighbors(1)] = -t lead = kwant.Builder(kwant.TranslationalSymmetry(lat.vec((-1, 0, 0)), lat.vec((0, cube.NY, 0)), lat.vec((0, 0, cube.NZ)))) lead[lat.shape(lead_shape, (0, 0, 0))] = 6 * t lead[lat.neighbors(1)] = -t syst=wraparound(syst) syst.attach_lead(wraparound(lead,keep=0)) syst.attach_lead(wraparound(lead,keep=0).reversed()) -- Mingkai Li

2 2

update Kwant to newer versions.
by Prof. CHAN Kwok Sum 16 Mar '17

16 Mar '17

Dear Kwant developers, I have a version of Kwant 1.02 installed for python 2.7 in a window computer. If I want to update it, do I need to uninstall it? Or Just download the new version and install the new version using the python 2.7. What happens if I want to change it to python 3.X, do I need to uninstall the python 2.7 and all the old Kwant? KS Chan Disclaimer: This email (including any attachments) is for the use of the intended recipient only and may contain confidential information and/or copyright material. If you are not the intended recipient, please notify the sender immediately and delete this email and all copies from your system. Any unauthorized use, disclosure, reproduction, copying, distribution, or other form of unauthorized dissemination of the contents is expressly prohibited.

2 1

updation to Kwant 1.3
by kamal ghosh 15 Mar '17

15 Mar '17

Dear Kwant Developers, We use Kwant 1.2.2 in the background of Python 3.4. We now understand that the Kwant package is updated to 1.3. The Kwant official website (https://kwant-project.org/install) recommends to download the packages from the website of Christoph Gohlke (http://www.lfd.uci.edu/~gohlke/pythonlibs/). But we are unable to find the updated Kwant package in the site mentioned above. Please help to solve the matter. Regards. Dr. K.K.Ghosh

2 1

Graphene band structure with more than 3 nearest-neighbors
by Juan Manuel Marmolejo-Tejada 14 Mar '17

14 Mar '17

Hi, I have been trying to get band structure for graphene with more than 3 nearest-neighbors using the following: graphene = kwant.lattice.general([[1, 0], [1/2, np.sqrt(3)/2]], # lattice vectors [[0, 0], [0, 1/np.sqrt(3)]]) # Coordinates of the sites a, b = graphene.sublattices zigzag_ribbon = kwant.Builder(kwant.TranslationalSymmetry([1, 0])) zigzag_ribbon[graphene.shape((lambda pos: abs(pos[1]) < 9), (0, 0))] = 0 zigzag_ribbon[graphene.neighbors(1)] = 1 zigzag_ribbon[graphene.neighbors(2)] = 0.2 zigzag_ribbon[graphene.neighbors(3)] = 0.18 zigzag_ribbon[graphene.neighbors(4)] = 0.1 kwant.plot(zigzag_ribbon); kwant.plotter.bands(zigzag_ribbon.finalized()); When I plot the system, I see the hoppings have been added successfully, but the band structure calculation returns the following error: ValueError: Further-than-nearest-neighbor cells are connected by hopping Can you please give me some advice on how to fix this error? Thanks for your help, Juan Marmolejo

2 4

problem with the wave_function calculation
by Luan Vieira de Castro 13 Mar '17

13 Mar '17

Dear Kwant team and community, I am trying to calculate the current density for a infinite system with kwant and, therefore, I have to use the the kwant.wave_function function. However, I always get a different result when I use this function, for example, with wf = kwant.wave_function(sys, energy=E), wf(0)[0][0] always gets a different value for every time I run my code. Am I misunderstanding the meaning of this function? Regards, Luan

2 1

Re: [Kwant] Transport across infinite plane with wraparound module
by Li Mingkai 10 Mar '17

10 Mar '17

Hi Kristjan, I'm working on 3D periodic boundary problem recently. Your code really helps me a lot. I tested your code. It seems working with nanowire leads instead of a periodic repeat in y direction. I changed the leads setting a little as following. A translational symmetry along y direction was added on lead. Then wraparound it with keep=0 lead = kwant.Builder(kwant.TranslationalSymmetry((-a, 0),lat.vec((0, W)))) lead[(lat(0,j) for j in range(W))] = 4*t lead[lat.neighbors(1)] = -t sys.attach_lead(wraparound(lead,keep=0)) sys.attach_lead(wraparound(lead,keep=0).reversed()) It seems working as a periodic boundary condiction. I judge it by settiing all potential to 0 in the scatting region. Then the tramsmittion with energy above 0 should be 1. Without above changes, the transmission at a little positive energy is 0 and the it will jump to 1 at a little higher energy. It implies the transversal energy quantization. I tested the ky under the above flat potential condition. The period of ky is 2Pi instead of 2Pi/L. I don't know why. Maybe some expert can explain it. Anyway, I'm just a newbie with kwant and trying to solve some bulk problem with it. I'm not sure about the above opinion. Let's discuss and figure out how it works in peroidic boundary condiction. -- Mingkai Li

2 3

Problems with memory allocation (?) in KWANT 1.3
by Camilla Espedal 10 Mar '17

10 Mar '17

Dear KWANT team, I am currently trying to write a program to try to calculate the spin Hall angle in a 4-terminal normal metal using Kwant 1.3 and the conservation law module. The scattering region is a square 40x40. I run in to a problem when trying to run it. The error message I get is: *** Error in `python3': malloc(): memory corruption: 0x00000000034f0de0 *** ======= Backtrace: ========= and then a bunch of stuff, and in the end [Finished in 29.6s with exit code -6] It seems to crash when I make the system too big or for too many energies. But, I don't understand why it doesn't work to solve the problem at one energy, store the result (which is just one number), and then for another. It seems the results from the other runs are somehow stored? I am not that experienced when it comes to programming, so I don't know if the problem is at my end or not. Thanks in advance, Camilla ------------------------------ Here is my code as well: import kwant import tinyarray as ta import numpy as np from scipy import sparse import matplotlib from matplotlib import pyplot s0 = ta.array([[1, 0], [0, 1]]) sx = ta.array([[0, 1], [1, 0]]) sy = ta.array([[0, -1j], [1j, 0]]) sz = ta.array([[1, 0], [0, -1]]) def calculate_sh_conductance(smatrix, leadIn, leadOut): con = -smatrix.transmission((leadOut, 0),(leadIn, 0)) + smatrix.transmission((leadOut, 1),(leadIn, 1)) return con def make_system(t=1.0, W=40, L=40, lead_W = 40): # Now we must specify the number of orbitals per site. lat = kwant.lattice.square(norbs=2) syst = kwant.Builder() """ We define the system below. The s-parameters are site parameters. The onsite has 1 site-parameter, while the hopping has two. The form of the functions must be like this, because Kwant requires it. """ syst[(lat(x, y) for x in range(L) for y in range(W))] = \ lambda s, alpha, phi: 0*4 * t * s0 # The last term here is the AF onsite coupling. syst[kwant.builder.HoppingKind((1, 0), lat, lat)] = \ lambda s1, s2, alpha, phi: -t * s0 - 1j * alpha * sy syst[kwant.builder.HoppingKind((0, 1), lat, lat)] = \ lambda s1, s2, alpha, phi: -t * s0 + 1j * alpha * sx ### Make the leads ### # Side leads lead = kwant.Builder(kwant.TranslationalSymmetry((-1, 0)), conservation_law=-sz, time_reversal=s0) lead[(lat(0, j) for j in range(W))] =0* 4 * t * s0 lead[lat.neighbors()] = -t * s0 # Note: no spin-orbit in the lead. # Top/bottom leads lead_tb = kwant.Builder(kwant.TranslationalSymmetry((0,-1)), conservation_law =-sz, time_reversal=s0) # We define the start and end fo the lead start = int(L/2 - lead_W/2) end = int(L/2 + lead_W/2) lead_tb[(lat(j,0) for j in range(start,end))] = 0*4 * t * s0 lead_tb[lat.neighbors()] = -t * s0 syst.attach_lead(lead) syst.attach_lead(lead.reversed()) syst.attach_lead(lead_tb) syst.attach_lead(lead_tb.reversed()) syst = syst.finalized() return syst def main(): syst = make_system(t=1.0, W=40, L=40, lead_W = 40) energies = np.linspace(-4,4, 200) socos = 0.5 fig = pyplot.figure(figsize=(13,8)) ax = fig.add_subplot(1, 1, 1) print("Starting spin calculation") conductance = [] # Calculate spin Hall conductance for energy in energies: smatrix= kwant.smatrix(syst, energy=energy, args=(socos, 0)) addi = calculate_sh_conductance(smatrix, 0, 3) conductance.append(addi) print(energy) ax.plot(energies, conductance, label="SOC %s" % socos) ax.legend(fontsize='x-large'); pyplot.show() if __name__ == '__main__': main()

3 4

(no subject)
by enrique colomes 09 Mar '17

09 Mar '17

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()

4 9