{
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   "source": [
    "# Absorbed Power Density Map of a Lossy Cylinder\n",
    "\n",
    "The `dft_flux` routines (`add_flux`) described in the previous examples compute the *total* power in a given region (`FluxRegion`). It is also possible to compute the *local* (i.e., position-dependent) absorbed power density in a dispersive (lossy) material. This quantity is useful for obtaining a spatial map of the photon absorption. The absorbed power density is defined as $$\\mathrm{Re}\\, \\left[ {\\mathbf{E}^* \\cdot \\frac{d\\mathbf{P}}{dt}} \\right]$$ where $\\mathbf{P}$ is the total polarization field. In the Fourier (frequency) domain with time-harmonic fields, this expression is $$\\mathrm{Re}\\, \\left[ {\\mathbf{E}^* \\cdot (-i \\omega \\mathbf{P})} \\right] = \\omega\\, \\mathrm{Im}\\, \\left[ {\\mathbf{E}^* \\cdot \\mathbf{P}} \\right]$$ where $\\mathbf{E}^* \\cdot \\mathbf{P}$ denotes the dot product of the complex conjugate of $\\mathbf{E}$ with $\\mathbf{P}$. However, since $\\mathbf{D}=\\mathbf{E}+\\mathbf{P}$, this is equivalent to $$ \\omega\\, \\mathrm{Im}\\, \\left[ {\\mathbf{E}^* \\cdot (\\mathbf{D}-\\mathbf{E})} \\right] = \\omega\\, \\mathrm{Im}\\, \\left[ {\\mathbf{E}^* \\cdot \\mathbf{D}} \\right]$$ since $\\mathbf{E}^* \\cdot \\mathbf{E} = |\\mathbf{E}|^2$ is purely real. Calculating this quantity involves two steps: (1) compute the Fourier-transformed $\\mathbf{E}$ and $\\mathbf{D}$ fields in a region via the `dft_fields` feature and (2) in post processing, compute $\\omega\\, \\mathrm{Im}\\, \\left[ {\\mathbf{E}^* \\cdot \\mathbf{D}} \\right]$.\n",
    "\n",
    "This tutorial example involves computing the absorbed power density for a two-dimensional cylinder (radius: 1 μm) of silicon dioxide (SiO<sub>2</sub>, from the [materials library](https://meep.readthedocs.io/en/latest/Materials/#materials-library)) at a wavelength of 1 μm given an incident $E_z$-polarized planewave. (The [attenuation length](https://en.wikipedia.org/wiki/Refractive_index#Complex_refractive_index) of SiO<sub>2</sub> at this wavelength is $\\lambda/\\mathrm{Im}\\, \\sqrt{\\varepsilon}$ = ~3000 μm.) We will also verify that the total power absorbed by the cylinder obtained by integrating the absorbed power density over the entire cylinder is equivalent to the same quantity computed using the alternative method involving a closed, four-sided `dft_flux` box (Poynting's theorem)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------\n",
      "Initializing structure...\n",
      "Halving computational cell along direction y\n",
      "time for choose_chunkdivision = 0.00278592 s\n",
      "Working in 2D dimensions.\n",
      "Computational cell is 8 x 8 x 0 with resolution 100\n",
      "     cylinder, center = (0,0,0)\n",
      "          radius 1, height 1e+20, axis (0, 0, 1)\n",
      "          dielectric constant epsilon diagonal = (1,1,1)\n",
      "time for set_epsilon = 0.94641 s\n",
      "lorentzian susceptibility: frequency=9.67865, gamma=0.0806554\n",
      "-----------\n"
     ]
    },
    {
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       "version_minor": 0
      },
      "text/plain": [
       "FloatProgress(value=0.0, description='0% done ', max=200.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "run 0 finished at t = 200.0 (40000 timesteps)\n",
      "flux:, 0.13120421825956843 (dft_fields), 0.13249534167200247 (dft_flux), 0.0097446702362583 (error)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import meep as mp\n",
    "from meep.materials import SiO2\n",
    "\n",
    "resolution = 100  # pixels/um\n",
    "\n",
    "dpml = 1.0\n",
    "pml_layers = [mp.PML(thickness=dpml)]\n",
    "\n",
    "r = 1.0     # radius of cylinder\n",
    "dair = 2.0  # air padding thickness\n",
    "\n",
    "s = 2*(dpml+dair+r)\n",
    "cell_size = mp.Vector3(s,s)\n",
    "\n",
    "wvl = 1.0\n",
    "fcen = 1/wvl\n",
    "\n",
    "# is_integrated=True necessary for any planewave source extending into PML\n",
    "sources = [mp.Source(mp.GaussianSource(fcen,fwidth=0.1*fcen,is_integrated=True),\n",
    "                     center=mp.Vector3(-0.5*s+dpml),\n",
    "                     size=mp.Vector3(0,s),\n",
    "                     component=mp.Ez)]\n",
    "\n",
    "symmetries = [mp.Mirror(mp.Y)]\n",
    "\n",
    "geometry = [mp.Cylinder(material=SiO2,\n",
    "                        center=mp.Vector3(),\n",
    "                        radius=r,\n",
    "                        height=mp.inf)]\n",
    "\n",
    "sim = mp.Simulation(resolution=resolution,\n",
    "                    cell_size=cell_size,\n",
    "                    boundary_layers=pml_layers,\n",
    "                    sources=sources,\n",
    "                    k_point=mp.Vector3(),\n",
    "                    symmetries=symmetries,\n",
    "                    geometry=geometry)\n",
    "\n",
    "dft_fields = sim.add_dft_fields([mp.Dz,mp.Ez],\n",
    "                                fcen,0,1,\n",
    "                                center=mp.Vector3(),\n",
    "                                size=mp.Vector3(2*r,2*r),\n",
    "                                yee_grid=True)\n",
    "\n",
    "# closed box surrounding cylinder for computing total incoming flux\n",
    "flux_box = sim.add_flux(fcen, 0, 1,\n",
    "                        mp.FluxRegion(center=mp.Vector3(x=-r),size=mp.Vector3(0,2*r),weight=+1),\n",
    "                        mp.FluxRegion(center=mp.Vector3(x=+r),size=mp.Vector3(0,2*r),weight=-1),\n",
    "                        mp.FluxRegion(center=mp.Vector3(y=+r),size=mp.Vector3(2*r,0),weight=-1),\n",
    "                        mp.FluxRegion(center=mp.Vector3(y=-r),size=mp.Vector3(2*r,0),weight=+1))\n",
    "\n",
    "sim.run(until_after_sources=100)\n",
    "\n",
    "Dz = sim.get_dft_array(dft_fields,mp.Dz,0)\n",
    "Ez = sim.get_dft_array(dft_fields,mp.Ez,0)\n",
    "absorbed_power_density = 2*np.pi*fcen * np.imag(np.conj(Ez)*Dz)\n",
    "\n",
    "dxy = 1/resolution**2\n",
    "absorbed_power = np.sum(absorbed_power_density)*dxy\n",
    "absorbed_flux = mp.get_fluxes(flux_box)[0]\n",
    "err = abs(absorbed_power-absorbed_flux)/absorbed_flux\n",
    "print(\"flux:, {} (dft_fields), {} (dft_flux), {} (error)\".format(absorbed_power,absorbed_flux,err))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is one important item to note: in order to eliminate discretization artifacts when computing the $\\mathbf{E}^* \\cdot \\mathbf{D}$ dot-product, the `add_dft_fields` definition includes `yee_grid=True` which ensures that the $E_z$ and $D_z$ fields are computed on the Yee grid rather than interpolated to the centered grid. As a corollary, we cannot use [`get_array_metadata`](https://meep.readthedocs.io/en/latest/Python_User_Interface/#array-metadata) to obtain the coordinates of the `dft_fields` region or its interpolation weights because this involves the centered grid.\n",
    "\n",
    "The two values for the total absorbed power which are displayed at the end of the run are nearly equivalent. The relative error between the two methods is ~1.0%.\n",
    "\n",
    "A schematic of the simulation layout generated using [`plot2D`](https://meep.readthedocs.io/en/latest/Python_User_Interface/#data-visualization) shows the line source (red), PMLs (green hatch region), `dft_flux` box (solid blue contour line), and `dft_fields` surface (blue hatch region)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f450c399110>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "sim.plot2D()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The spatial map of the absorbed power density shows that most of the absorption occurs in a small region near the back surface of the cylinder (i.e., on the opposite side of the incident planewave)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f44ecab7f90>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "x = np.linspace(-r,r,Dz.shape[0])\n",
    "y = np.linspace(-r,r,Dz.shape[1])\n",
    "plt.pcolormesh(x,\n",
    "               y,\n",
    "               np.transpose(absorbed_power_density),\n",
    "               cmap='inferno_r',\n",
    "               shading='gouraud',\n",
    "               vmin=0,\n",
    "               vmax=np.amax(absorbed_power_density))\n",
    "plt.xlabel(\"x (μm)\")\n",
    "plt.xticks(np.linspace(-r,r,5))\n",
    "plt.ylabel(\"y (μm)\")\n",
    "plt.yticks(np.linspace(-r,r,5))\n",
    "plt.gca().set_aspect('equal')\n",
    "plt.title(\"absorbed power density\" + \"\\n\" +\"SiO2 Labs(λ={} μm) = {:.2f} μm\".format(wvl,wvl/np.imag(np.sqrt(SiO2.epsilon(fcen)[0][0]))))\n",
    "plt.colorbar()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}