Victor, The `kwant.discretize` is devoted to discrete k.p Hamiltonians. In your case, I'd recommend to write the tight-binding version of that Hamiltonian instead.
I don't understand what you mean by "finding the hopping terms". You should set that, and not find it. Best, Antonio On Sat, 6 Feb 2021, 12:16 Victor Regis, <[email protected]> wrote: > Hi all, > > I need to use the following hamiltonian to test if the rest of my code is > correct, however I haven't been able to implement it in Kwant. Reading the > examples, all the discretize ones are for polynomial dependences on k but > mine isn't. > > H = sin(k_x)*sigma_x +sin(k_y)*sigma_y +B*(2+M-cos(k_x)-cos(k_y))*sigma_z > > When I implement it on a square grid I obtain the following output: > > # Discrete coordinates: x y > > # Onsite element: > _cache_0 = ( > array([[ 1.+0.j, 0.+0.j], > [ 0.+0.j, -1.+0.j]])) > _cache_1 = ( > array([[-1.+0.j, 0.+0.j], > [ 0.+0.j, 1.+0.j]])) > _cache_2 = ( > array([[-1.+0.j, 0.+0.j], > [ 0.+0.j, 1.+0.j]])) > _cache_3 = ( > array([[ 2.+0.j, 0.+0.j], > [ 0.+0.j, -2.+0.j]])) > _cache_4 = ( > array([[0.+0.j, 1.+0.j], > [1.+0.j, 0.+0.j]])) > _cache_5 = ( > array([[0.+0.j, 0.-1.j], > [0.+1.j, 0.+0.j]])) > def onsite(site, B, M, cos, k_x, k_y, sin): > _const_0 = (cos(k_x)) > _const_1 = (cos(k_y)) > _const_2 = (sin(k_x)) > _const_3 = (sin(k_y)) > return (B*M) * (_cache_0) + (B*_const_0) * (_cache_1) + (B*_const_1) * > (_cache_2) + (B) * (_cache_3) + (_const_2) * (_cache_4) + (_const_3) * > (_cache_5) > > My issues are: > > 1. The constants are just my sines and cosines of k_x/k_y, so what > happened here? > 2. I think because of that it can't find the hopping terms; > 3. It doesn't plot any lattice, however if I set hamiltonian = "k_x+k_y" i > does plot the square lattice. > > I know the hamiltonian can be linearized in k, but if possible I want to > implement it as it is. > > Thanks in advance. >
