Topological Hall effect in four terminal devices
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zgnr_adatoms_4t.py
from math import sqrt import random import itertools as it import tinyarray as ta import numpy as np import matplotlib.pyplot as plt import kwant class Honeycomb(kwant.lattice.Polyatomic): """Honeycomb lattice with methods for dealing with hexagons""" def __init__(self, name=''): prim_vecs = [[0.5, sqrt(3)/2], [1, 0]] # bravais lattice vectors # offset the lattice so that it is symmetric around x and y axes basis_vecs = [[-0.5, -1/sqrt(12)], [-0.5, 1/sqrt(12)]] super(Honeycomb, self).__init__(prim_vecs, basis_vecs, name) self.a, self.b = self.sublattices def hexagon(self, tag): """ Get sites belonging to hexagon with the given tag. Returns sites in counter-clockwise order starting from the lower-left site. """ tag = ta.array(tag) # a-sites b-sites deltas = [(0, 0), (0, 0), (1, 0), (0, 1), (0, 1), (-1, 1)] lats = it.cycle(self.sublattices) return (lat(*(tag + delta)) for lat, delta in zip(lats, deltas)) def hexagon_neighbors(self, tag, n=1): """ Get n'th nearest neighbor hoppings within the hexagon with the given tag. """ hex_sites = list(self.hexagon(tag)) return ((hex_sites[(i+n)%6], hex_sites[i%6]) for i in range(6)) def random_placement(builder, lattice, density): """ Randomly selects hexagon tags where adatoms can be placed. This avoids the edge case where adatoms would otherwise be placed on incomplete hexagons at the system boundaries. """ assert 0 <= density <= 1 system_sites = builder.sites() def hexagon_in_system(tag): return all(site in system_sites for site in lattice.hexagon(tag)) # get set of tags for sites in system (i.e. tags from only one sublattice) system_tags = (s.tag for s in system_sites if s.family == lattice.a) # only allow tags which have complete hexagons in the system valid_tags = list(filter(hexagon_in_system, system_tags)) N = int(density * len(valid_tags)) total_hexagons=len(valid_tags) valuef=random.sample(valid_tags, N) return valuef def cross(W, L): def shape(pos): return ((-W <= pos[0] <= W and -L <= pos[1] <= L) or # vertical (-W <= pos[1] <= W and -L <= pos[0] <= L)) # horizontal return shape ## Pauli matrices ## sigma_0 = ta.array([[1, 0], [0, 1]]) # identity sigma_x = ta.array([[0, 1], [1, 0]]) sigma_y = ta.array([[0, -1j], [1j, 0]]) sigma_z = ta.array([[1, 0], [0, -1]]) ## Hamiltonian value functions ## def onsite_potential(site, params): return params['ep'] * sigma_0 def potential_shift(site, params): return params['mu'] * sigma_0 def kinetic(site_i, site_j, params): return -params['gamma'] * sigma_0 def rashba(site_i, site_j, params): d_ij = site_j.pos - site_i.pos rashba = 1j * params['V_R'] * (sigma_x * d_ij[1] - sigma_y * d_ij[0]) return rashba + kinetic(site_i, site_j, params) def spin_orbit(site_i, site_j, params): so = (1j/3.) * params['V_I'] * sigma_z return so lat = Honeycomb() pv1, pv2 = lat.prim_vecs ysym = kwant.TranslationalSymmetry(pv2 - 2*pv1) # lattice symmetry in -y direction xsym = kwant.TranslationalSymmetry(-pv2) # lattice symmetry in -x direction # adatom lattice, for visualization only adatom_lat = kwant.lattice.Monatomic(lat.prim_vecs, name='adatom') def site_size(s): return 0.25 if s.family in lat.sublattices else 0.35 def site_color(s): return '#000000' if s.family in lat.sublattices else '#808080' def create_lead_h(W, symmetry, axis=(0, 0)): lead = kwant.Builder(symmetry) lead[lat.wire(axis, W)] = 0. * sigma_0 lead[lat.neighbors(1)] = kinetic return lead def create_lead_v(L,W, symmetry): axis=(0, 0) lead = kwant.Builder(symmetry) lead[lat.wire(axis, W)] = 0. * sigma_0 lead[lat.neighbors(1)] = kinetic return lead def create_hall_cross(W, L, adatom_density=0.2, show_adatoms=False): ## scattering region ## sys = kwant.Builder() sys[lat.shape(cross(W, L), (0, 0))] = onsite_potential sys[lat.neighbors(1)] = kinetic adatoms = random_placement(sys, lat, adatom_density) sys[(lat.hexagon(a) for a in adatoms)] = potential_shift sys[(lat.hexagon_neighbors(a, 1) for a in adatoms)] = rashba sys[(lat.hexagon_neighbors(a, 2) for a in adatoms)] = spin_orbit if show_adatoms: # no hoppings are added so these won't affect the dynamics; purely cosmetic sys[(adatom_lat(*a) for a in adatoms)] = 0 ## leads ## leads = [create_lead_h(W, xsym)] leads += [create_lead_v(L,W, ysym)] leads += [lead.reversed() for lead in leads] # right and bottom leads for lead in leads: sys.attach_lead(lead) return sys def plot_bands(sys, params): fsys = sys.finalized() fig, (ax1, ax2) = plt.subplots(1, 2) ax1.set_title('left lead band structure') ax2.set_title('top lead band structure') for ax in (ax1, ax2): ax.set_xlabel('$k$', size=20) ax.set_ylabel('$E$', size=20) kwant.plotter.bands(fsys.leads[0], ax=ax1, args=(params,)) kwant.plotter.bands(fsys.leads[1], ax=ax2, args=(params,)) fig.tight_layout() plt.show() def plot_ldos(sys, Es, params): fsys = sys.finalized() ldos = kwant.ldos(fsys, energy=Es, args=(params,)) ldos = ldos[::2] + ldos[1::2] # sum spins kwant.plotter.map(fsys, ldos, vmax=0.1) def plot_conductance(sys, energies,lead_i,lead_j, params): fsys = sys.finalized() data = [] for energy in energies: smatrix = kwant.smatrix(fsys, energy, args=(params,)) data.append(smatrix.transmission(lead_i,lead_j)) plt.figure() plt.plot(energies, data) plt.xlabel("energy (t)") plt.ylabel("conductance (e^2/h)") plt.show() if __name__ == '__main__': # params = dict(gamma=1., ep=0, mu=0., V_I=0.017, V_R=0) # Tl adatoms params = dict(gamma=1., ep=0, mu=0, V_I=0.0032, V_R=0) # In adatoms W=16 L=32 adatom_density=0.3 sys = create_hall_cross(W, L, adatom_density, show_adatoms=True) kwant.plot(sys, site_color=site_color, site_size=site_size) plot_bands(sys, params) sys = create_hall_cross(W, L, adatom_density, show_adatoms=False) plot_ldos(sys, 1e-5, params) Es = np.linspace(-0.2, 0.2, 100) plot_conductance(sys, Es, 1, 0, params) # T01 plot_conductance(sys, Es, 2, 0, params) # T02