Source code for magnumnp.field_terms.demagPBC

#
# This file is part of the magnum.np distribution
# (https://gitlab.com/magnum.np/magnum.np).
# Copyright (c) 2023 magnum.np team.
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from magnumnp.common import timedmethod, constants
from .field_terms import LinearFieldTerm
from math import pi
import torch

__all__ = ["DemagFieldPBC"]

[docs] class DemagFieldPBC(LinearFieldTerm): @timedmethod def h(self, state): m_fft = torch.fft.fftn(state.material["Ms"] * state.m, dim = [i for i in range(3) if state.mesh.n[i] > 1]).squeeze(-1) #TODO: use rfftn -> kz should be size N//2+1 dx, dy, dz = state.mesh.dx kx = (2. * pi * torch.arange(state.mesh.n[0]) / state.mesh.n[0]).reshape(-1,1,1) ky = (2. * pi * torch.arange(state.mesh.n[1]) / state.mesh.n[1]).reshape(1,-1,1) kz = (2. * pi * torch.arange(state.mesh.n[2]) / state.mesh.n[2]).reshape(1,1,-1) div_fft = (1.-torch.exp(-1j*kx)) * m_fft[:,:,:,0] / dx \ + (1.-torch.exp(-1j*ky)) * m_fft[:,:,:,1] / dy \ + (1.-torch.exp(-1j*kz)) * m_fft[:,:,:,2] / dz u_fft = -div_fft / (4./dx**2*torch.sin(kx/2.)**2 + \ 4./dy**2*torch.sin(ky/2.)**2 + \ 4./dz**2*torch.sin(kz/2.)**2) u_fft[0,0,0] = 0 h_fft = torch.empty_like(m_fft) h_fft[:,:,:,0] = (1.-torch.exp(1j*kx)) * u_fft / dx h_fft[:,:,:,1] = (1.-torch.exp(1j*ky)) * u_fft / dy h_fft[:,:,:,2] = (1.-torch.exp(1j*kz)) * u_fft / dz h = torch.fft.ifftn(h_fft, dim = [i for i in range(3) if state.mesh.n[i] > 1]) return h.real