Mailman 3 June 2021 - Kwant-discuss

Realistic values of hopping parameters
by Yu Li 19 Oct '23

19 Oct '23

Dear all, Now I’m studying some transport property based on multilayered system, with nonmagnetic layer/ferromagnetic layer (NM/FM) stack. May I ask when creating a tight binding system, and setting hoppings by the following function: syst[(lat(1, 0), lat(1, 1))] = t, how to associate the hopping with a realistic system? Such as hoppings between FM and FM atoms, or between FM and NM atoms? I found in many literatures people just simply put t=1, but I assume the value should depend on the type of atoms. My another question is, is it possible to define more than one type of hopping between two sites? For the tight-binding approximation of p electrons, there are two types of hopping integrals: Vppσ, and Vppπ, so I’m wondering if it’s possible to simulate the effect of both hoppings? Thanks a lot for reading my questions! Cheers, Yu Li

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Gate-defined Nanowire Quantum Dot
by Jonathan Fields 15 Sep '22

15 Sep '22

Dear Reader, I am new to KWANT and trying to figure out if it is suitable for calculating transport properties of gate-defined quantum dots made out of nanowires, along the lines of the structure used in https://arxiv.org/abs/cond-mat/0609463. Now, I understand that the mailing list is not a place to ask people to do my work for me, and my question is also not for someone to do this. What I am looking for is some insights into if this is possible (and not all that difficult) with the package. At first sight (and going through the tutorials as well as the APS March Meeting material) this does not seem straightforward; what I struggle with is how to define this type of dot in KWANT. Now, one way would of course be to built the entire 3D geometry of the system, but this will be computationally expensive, and probably also rather tricky to do in terms of defining everything, from the hexagonal wire itself to all of the gates and oxide layers and such. Some abstraction would be preferred, perhaps even reducing the dimensionality and making a 2D system, such as often done in the tutorial. Is this a good idea? My problem is that if one does this, then I run into the problem of how to model the 'half wrap-around' type gates typically used in these devices. In the transport through barrier section of the APS March Meeting material there is a section on how to model realistic potentials, but this would not work all that well for these wrap around type gates. On the other hand, in a way they are perhaps not so different from the QPC in that section. One could model the three gates as something like https://i.imgur.com/WZC983c.png as they do essentially form channels in the wire. Apart from if this sacrifices too much of the nanowire nature in favor of a 2DEG system, I do suppose such a system should in principle be able to be treated as a quantum dot. I haven't been able to confirm this as I am not yet sure how one can apply a source-drain voltage in KWANT; I first thought that this would probably be related to the energy of the modes, but then again I have not been able to produce Coulomb diamonds in this way. The question is getting rather lenghty, and also a bit unclear at this point. Perhaps I should finish up by stating it in a concise form; would you think that it is possible to simulate the transport of such a gate defined nanowire quantum dot device with KWANT, and if so, is the approach I am suggesting above a viable one, or would you go about it very differently? Kind regards Jonathan <http://aka.ms/weboutlook>

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current-voltage diagram
by loojoo026＠gmail.com 08 Apr '22

08 Apr '22

dear all I have done my project using Kwant and I have drawn a conductance-energy diagram for the system. The question I have is how can I get the current-voltage diagram? thanks Leo

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How the spin is positioned in the Smatrix?
by Qingtian Zhang 06 Mar '22

06 Mar '22

Dear all, I am trying square lattice with spin-orbit coupling and Zeeman splititng just like the example of Tutorial 2.3.1. Now I want to get the spin-dependent conductance：Guu,Gud,Gdu,and Gdd, where "u" indicates up spin, d indicates down spin. We can have the scattering matrix through Smatrix=kwant.smatrix(sys, energy), but how the spin is positioned in the scattering matrix? I have checked some simple cases, it seems the Smatrix is organized like this: | r t | S= | t' r' | but how the spin is included? Thanks in advance. Qingtiian Zhang The code is: import kwant from matplotlib import pyplot from numpy import matrix import tinyarray sigma_0 = tinyarray.array([[1, 0], [0, 1]]) sigma_x = tinyarray.array([[0, 1], [1, 0]]) sigma_y = tinyarray.array([[0, -1j], [1j, 0]]) sigma_z = tinyarray.array([[1, 0], [0, -1]]) sys=kwant.Builder() lat=kwant.lattice.square() a=1 t=1.0 alpha=0.5 e_z=0.08 W=2 L=2 sys[(lat(x, y) for x in range(L) for y in range(W))] = \ 4 * t * sigma_0 + e_z * sigma_z # hoppings in x-direction sys[kwant.builder.HoppingKind((1, 0), lat, lat)] = \ -t * sigma_0 - 1j * alpha * sigma_y # hoppings in y-directions sys[kwant.builder.HoppingKind((0, 1), lat, lat)] = \ -t * sigma_0 + 1j * alpha * sigma_x #### Define the left lead. #### lead = kwant.Builder(kwant.TranslationalSymmetry((-a, 0))) lead[(lat(0, j) for j in xrange(W))] = 4 * t * sigma_0 + e_z * sigma_z # hoppings in x-direction lead[kwant.builder.HoppingKind((1, 0), lat, lat)] = \ -t * sigma_0 - 1j * alpha * sigma_y # hoppings in y-directions lead[kwant.builder.HoppingKind((0, 1), lat, lat)] = \ -t * sigma_0 + 1j * alpha * sigma_x #### Attach the leads and return the finalized system. #### sys.attach_lead(lead) sys.attach_lead(lead.reversed()) kwant.plot(sys) sys=sys.finalized() print "Hamiltonian=" print sys.hamiltonian_submatrix() Smatrix=kwant.smatrix(sys, energy=3.) print "The scattering matrix=" print matrix.round((Smatrix.data),2) print "T=",(Smatrix.transmission(1, 0))

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Spin polarized transport calculation
by L.M J 06 Mar '22

06 Mar '22

Dear Kwant users and developers I have two questions related to the spin calculation using kwant. 1. I'm wondering if we can do spin-polarized transport in kwant? For example, can we can get the separate Conductance Vs Energy diagram for spin up and spin down terms. I'm thinking one way of doing this is to set up the Rashba Hamiltonian as a whole. And then manually extract the spin up and spin down hamiltonian and do the transport calculation separately. But this will eliminate some extra terms that I don't know whether this is correct anymore. Any suggestions? 2. How can we set up the spin polarization for a particular site? For example, in some of the topological insulator, can we set up spin polarization on the edge as up and the other side of the edge as down, and then do the transport? Or this question is completely wrong? Thanks for advance. Sincerely, Liming

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Graphene Conductor-Superconductor Conductance above Gap
by Henry Axt 21 Feb '22

21 Feb '22

Hello, I set up a graphene lattice with periodic boundary conditions that is connected to a superconductor (simulated with an electron and hole lattice). When observing the transmission between the electron and hole lattice, I see a small amount conductance above the superconducting gap. I do not see this with something like a square lattice. What could explain this?

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How to caculate hall resistance
by ZHANG Bing 12 Sep '21

12 Sep '21

Dear Sir, I am a PhD student of Hong Kong University of Science and Technology. I want to use KWANT to caculate Hall resistance of a Hall bar structure.We can get the conductance between 6 electrodes, but how to get hall resistance? Can you give me some help? Thank you very much. Best Regards, Zhang Bing

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module 'kwant.linalg._mumps' has no attribute 'dmumps' ERROR
by BHAVYA BHARDWAJ 02 Sep '21

02 Sep '21

Repected Members, I am a B.Tech Student using Kwant for simulations.Python Version: 3.7.8 Kwant Version: 1.4.2Ubuntu 20The Error I faced is given below. AttributeError Traceback (most recent call last) <ipython-input-6-c80da766c4bb> in <module> 17 pyplot.ylabel("conductance [e^2/h]") 18 pyplot.show() ---> 19 solving(model.tokwant()) <ipython-input-6-c80da766c4bb> in solving(sys) 7 energy = ie * 0.01 8 # compute the scattering matrix at a given energy ----> 9 smatrix = kwant.greens_function(sys, energy,check_hermiticity=False) 10 # compute the transmission probability from lead 0 to 11 # lead 1 ~/Downloads/112358/lib/python3.7/site-packages/kwant/_common.py in inner(*args, **kwargs) 70 if sig.bind(*args, **kwargs).arguments.get(parameter_name): 71 warn() ---> 72 return f(*args, **kwargs) 73 74 return inner ~/Downloads/112358/lib/python3.7/site-packages/kwant/solvers/common.py in greens_function(self, sys, energy, args, out_leads, in_leads, check_hermiticity, params) 485 rhs = sp.bmat([[i for i in linsys.rhs if i.shape[1]]], 486 format=self.rhsformat) --> 487 flhs = self._factorized(linsys.lhs) 488 data = self._solve_linear_sys(flhs, rhs, kept_vars) 489 ~/Downloads/112358/lib/python3.7/site-packages/kwant/solvers/mumps.py in _factorized(self, a) 102 def _factorized(self, a): 103 inst = mumps.MUMPSContext() --> 104 inst.factor(a, ordering=self.ordering) 105 return inst 106 ~/Downloads/112358/lib/python3.7/site-packages/kwant/linalg/mumps.py in factor(self, a, ordering, ooc, pivot_tol, reuse_analysis, overwrite_a) 318 row, col, data) 319 else: --> 320 self.analyze(a, ordering=ordering, overwrite_a=overwrite_a) 321 322 self.mumps_instance.icntl[22] = 1 if ooc else 0 ~/Downloads/112358/lib/python3.7/site-packages/kwant/linalg/mumps.py in analyze(self, a, ordering, overwrite_a) 227 228 if dtype != self.dtype: --> 229 self.mumps_instance = getattr(_mumps, dtype+"mumps")(self.verbose) 230 self.dtype = dtype 231 AttributeError: module 'kwant.linalg._mumps' has no attribute 'dmumps' Kindly guide me so I can overcome this error. Thank You, Regards, Bhavya Bhardwaj

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3D structure
by tavakkolidjawad 19 Jul '21

19 Jul '21

Dear all In the following code I have defined a three-dimensional structure. The geometry of the lead and the scattering region are the same, but the lead is not ploted as I expected. I expected the lead to have a cubic structure. What is the problem with my code? Thanks Javad tavakoli ############################################################################ ############################################################################ import kwant lat = kwant.lattice.general([(0, 0.5, 0.5), (0.5, 0, 0.5), (0.5, 0.5, 0)], [(0, 0, 10), (0.25, 0.25, 10.25)], name=['a1', 'a2']) a1, a2 = lat.sublattices def make_system(a=10, b=10, c=30): syst = kwant.Builder() def cuboid_shape(pos): x, y, z = pos return 0 <= x < a and 0 <= y < b and 0 <= z < 10 syst[a1.shape(cuboid_shape, (0, 0, 0))] = 1 syst[a2.shape(cuboid_shape, (0, 0, 0))] = 1 syst[lat.neighbors()] = 1 def lead_shape(pos): x,y,z = pos return 0 <= x < a and 0 <= y < b and 10 <= z < 25 lead = kwant.Builder(kwant.TranslationalSymmetry((0,0,1))) lead[a1.shape(lead_shape, (0, 0, 10))] = 1 lead[a2.shape(lead_shape, (0, 0, 10))] = 1 lead[lat.neighbors()] = 1 syst.attach_lead(lead) syst.attach_lead(lead.reversed()) return syst , lead def main(): syst,lead= make_system() kwant.plot(syst) syst,lead = make_system(a=1.1, b=1.1, c=1.1) syst.attach_lead(lead) if __name__ == '__main__': main() ###########################################################################

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Inquiry about Kwant boundstate algorithm (unphysical spectra at some sets of parameters)
by Zhang, Chi 25 Jun '21

25 Jun '21

Dear Colleagues, Hi, we are 2 students at Imperial College looking to incorporate your boundstate algorithm (https://scipost.org/submissions/1711.08250v1<https://scipost.org/submissions/1711.08250v1/>) in the context of a lateral Josephson junction. The code we used was copied and pasted from here: ( https://gitlab.kwant-project.org/jbweston/kwant/-/blob/feature/boundstate/k…) As an exercise we are trying to reproduce fig. 9 in this paper. Implementing the same parameters, we managed to obtain similar graphs shown below for a value of t=0.7. [cid:d6350847-a84d-413c-966e-9f76a7e16b14] However, we notice that at some values of t, the boundstate algorithm starts yielding non-physical results. Examples include: 1. 1. At t=-1 (which is what we assumed t to be initially from the captions in fig. 7), the algorithm returned energies above the band gap in the JJ in topological regime for some values of phi, the phase difference, and returned true values for some values of phi but not for others in the trivial regime. 2. [cid:ab6b6f7d-c949-4867-a1de-fc904e9d617f] 1. In the B scan for t=-1 boundstates start disappearing from B=0.325 onwards, well before crossing the degeneracy point, and in the topological regime they do not line up with the band edge. 2. [cid:1390ff07-aa3a-4545-ae1b-11b041706548] 1. We also noticed that the algorithm results are dependent on the system setup. To be able to independently replicate fig. 9 my partner and I set up a 2-site (left lead - super - normal - right lead) and 3-site (left lead - super - normal - super - right lead) system respectively to implement the phase from crossing the S-N interface. A schematic of this is shown below. 2. [cid:ccd40751-9e75-4c9f-9dc1-66343648e586] 3. While most standard kwant functionalities seem to recognise the 2 systems are equivalent to each other, we obtained drastically different results from the boundstate algorithm. Examples include a t-scan at B=1 to uncover possible t values where physical ABS spectra could be returned. 4. [cid:d9ca0c7e-5d9f-4546-aadb-091d36aa3542] 5. 2 site 3 site 6. (We checked that the thing causing the drastically different behaviour is the number of sites in the system. We were able to replicate each other's results only by changing the number of sites in the scattering region.) 1. We plotted f(E) in the find_boundstate function for t=-1, B=0.3 (where the algorithm succeeds in detecting the bound state) and B=0.35 (where the algorithm fails to do so), respectively. We noticed that the 2 roots from B=0.3 which are validated to be the true bound states are omitted in B=0.35, not because the validation operator rejects them, but because min_eigenvalue() (or lowest value of sparse_diag()) at these 2 energies indeed returned a value much larger than tol=1e-8 (0.003). We incremented the B field to see when the boundstate to no-boundstate transition occurs and it's at B=0.325 that the min_eigenvalue suddenly shoots up to 1e-4 (for B=0.324 we have 1e-9). We do not understand how this comes to be. 2. [cid:b7e35a85-363c-47d1-b756-52827f73d3f5] 3. The above disappearance of boundstates past B=0.325 is encountered when we set sparse=False too. We would like to know if similar problems with the boundstate algorithm have been encountered before, and if so, what do these signatures tell us is wrong, or does this indeed suggest something is incomplete in the implementation? Finally, we would also like to ask about your specific system setup in Kwant to obtain figure 9, as well as the parameter t that was used, as this was not specified explicitly. Many thanks in advance for answering our query! Sincerely, Chi Zhang & Ryan Tiew Blackett Laboratory Imperial College London

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