Dear Professors, I want to put a transverse electric field on this example. So Imodify the onsite energy as follows, def onsite(site, p): x, y = site.pos E = 0.15 # the magnitude of electrical field in y direction return tau_z * (p.mu - 2 * p.t) + sigma_z * p.B + tau_x * p.Delta + E* y* s_0 s_0 = numpy.identity(2). However, the program crashed to UserCodeError: Error occurred in user-supplied value function "onsite". The same error also occur when I put a perpendicular magnetic field and modify the hopping energy as def hopping(sitei, sitej, phi, salt): xi, yi = sitei.pos xj, yj = sitej.pos return t0 * exp(-0.5j * phi * (xi - xj) * (yi + yj)) where t0 is the hopping matrix before put magnetic field. Would you like help me in this issue? Happy Kwant! QC HNIE __________The full code _____________________ from matplotlib import pyplot import kwant from kwant.digest import gauss import numpy import tinyarray import scipy.sparse.linalg # Python >= 3.3 provides SimpleNamespace in the # standard library so we can simply import it: # >>> from types import SimpleNamespace # (Kwant does not yet support Python 3.) class SimpleNamespace(object): """A simple container for parameters.""" def __init__(self, **kwargs): self.__dict__.update(kwargs) s_0 = numpy.identity(2) s_z = numpy.array([[1, 0], [0, -1]]) s_x = numpy.array([[0, 1], [1, 0]]) s_y = numpy.array([[0, -1j], [1j, 0]]) tau_z = tinyarray.array(numpy.kron(s_z, s_0)) tau_x = tinyarray.array(numpy.kron(s_x, s_0)) sigma_z = tinyarray.array(numpy.kron(s_0, s_z)) tau_zsigma_x = tinyarray.array(numpy.kron(s_z, s_x)) def onsite(site, p): x, y = site.pos Electric = 0.15 # the magnitude of electrical field in y direction return tau_z * (p.mu - 2 * p.t) + sigma_z * p.B + tau_x * p.Delta + Eeletric * y* s_0 def hopping(site0, site1, p): return tau_z * p.t + 1j * tau_zsigma_x * p.alpha def make_system(l=70): sys = kwant.Builder() lat = kwant.lattice.chain() sys[(lat(x) for x in range(l))] = onsite sys[lat.neighbors()] = hopping return sys.finalized() sys = make_system() # Calculate and plot lowest eigenenergies in B-field. B_values = numpy.linspace(0, 0.6, 80) energies = [] params = SimpleNamespace( t=1, mu=-0.1, alpha=0.05, Delta=0.2) for params.B in B_values: H = sys.hamiltonian_submatrix( args=[params], sparse=True) H = H.tocsc() eigs = scipy.sparse.linalg.eigsh(H, k=20, sigma=0) energies.append(numpy.sort(eigs[0])) pyplot.plot(B_values, energies) pyplot.show()