{ "cells": [ { "cell_type": "markdown", "id": "2d4263f9", "metadata": {}, "source": [ "# Euler waveguide bend" ] }, { "cell_type": "markdown", "id": "03eb4470", "metadata": {}, "source": [ "Efficiently routing light in a densely packed photonic chip has been a central topic in the photonic industry. This inevitably requires the use of waveguide bends of various angles and radii. Electromagnetic waves can travel in straight waveguides for a long distance with very little loss. However, when it enters a waveguide bend, significant reflection and leakage could occur. \n", "\n", "The most common waveguide bends are circular bends. A silicon waveguide bend typically has a loss in the order of 0.01 dB. This loss is sufficiently small for many applications. However, in cases where a large number of bends are used, the total loss due to the bends can be quite large. Therefore, new methods to reduce bending loss is needed. Recently, [T. Fujisawa et al.](https://opg.optica.org/oe/fulltext.cfm?uri=oe-25-8-9150&id=362937) demonstrated that a waveguide bend following the clothoid curve, also known as the Euler bend, yields a much lower loss compared to a circular bend due to its smooth curvature transition. In this example notebook, we model a 90 degree Euler waveguide bend and compare its loss to a conventional circular bend. The loss of the Euler waveguide bend is found to be several times smaller compared to the circular bend of the same effective radius at the telecom wavelength.\n", "\n", "" ] }, { "cell_type": "code", "execution_count": 1, "id": "b27b7f93", "metadata": { "execution": { "iopub.execute_input": "2023-02-02T22:02:43.719593Z", "iopub.status.busy": "2023-02-02T22:02:43.719281Z", "iopub.status.idle": "2023-02-02T22:02:44.645587Z", "shell.execute_reply": "2023-02-02T22:02:44.643948Z" } }, "outputs": [ { "data": { "text/html": [ "
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       "                    PyPI. Future releases will be uploaded to the 'tidy3d' repository. From now on,                \n",
       "                    please use 'pip install tidy3d' instead.                                                       \n",
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           INFO     Using client version: 1.9.0                                                     __init__.py:121\n",
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At the end point of the clothoid curve, the curve length is $L_{max}$ and the curvature is $1/R_{min}$. Unlike a circular curve, the curvature of a clothoid curve varies linearly from 0 to $1/R_{min}$. A 90 degree Euler waveguide bend is constructed by connecting two pieces of clothoid curves with a circular curve. One clothoid curve starts at $(0,0)$ and the other starts at $(R_{eff},R_{eff})$, where $R_{eff}$ is the effective waveguide bending radius. To ensure a smooth transition of curvature, we choose a $L_{max}$ such that the derivative is continuous at the connecting points.\n", "\n", "In this example notebook, we model waveguide bends with a 4 $\\mu m$ effective bending radius. First, we plot the shapes of the two types of bends to get a sense of how the Euler bend and the circular bend differ. More specifically, we try the case with $A=2.4$." ] }, { "cell_type": "code", "execution_count": 2, "id": "bf5fb3bd", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.346958Z", "iopub.status.busy": "2023-01-12T04:13:17.346546Z", "iopub.status.idle": "2023-01-12T04:13:17.350891Z", "shell.execute_reply": "2023-01-12T04:13:17.350232Z" } }, "outputs": [], "source": [ "R_eff = 4 # effective radius of the bend\n", "A = 2.4 # clothoid parameter\n" ] }, { "cell_type": "markdown", "id": "7a80be45", "metadata": {}, "source": [ "An important step in constructing the Euler bend is to determine $L_{max}$. Here we do it numerically by first setting $L_{max}=0$. $L_{max}$ is then slowly increased at some small step. At each increment, we check if the tangent curve is perpendicular to that of the circular curve. Once this condition is met, we obtain the correct value of $L_{max}$ as well as the coordinates of the clothoid." ] }, { "cell_type": "code", "execution_count": 3, "id": "adea8def", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.354333Z", "iopub.status.busy": "2023-01-12T04:13:17.354097Z", "iopub.status.idle": "2023-01-12T04:13:17.440718Z", "shell.execute_reply": "2023-01-12T04:13:17.439540Z" } }, "outputs": [], "source": [ "L_max = 0 # starting point of L_max\n", "precision = 0.05 # increasement of L_max at each iteration\n", "tolerance = 0.01 # difference tolerance of the derivatives\n", "\n", "# determine L_max\n", "while True:\n", " L_max = L_max + precision # update L_max\n", " Ls = np.linspace(0, L_max, 50) # L at (x1,y1)\n", " x1 = np.zeros(len(Ls)) # x coordinate of the clothoid curve\n", " y1 = np.zeros(len(Ls)) # y coordinate of the clothoid curve\n", "\n", " # compute x1 and y1 using the above integral equations\n", " for i, L in enumerate(Ls):\n", " y1[i], err = integrate.quad(lambda theta: A * np.sin(theta**2 / 2), 0, L / A)\n", " x1[i], err = integrate.quad(lambda theta: A * np.cos(theta**2 / 2), 0, L / A)\n", "\n", " # compute the derivative at L_max\n", " k = -(x1[-1] - x1[-2]) / (y1[-1] - y1[-2])\n", " xp = x1[-1]\n", " yp = y1[-1]\n", " # check if the derivative is continuous at L_max\n", " R = np.sqrt(\n", " ((R_eff + k * xp - yp) / (k + 1) - xp) ** 2\n", " + (-(R_eff + k * xp - yp) / (k + 1) + R_eff - yp) ** 2\n", " )\n", " if np.abs(R - A**2 / L_max) < tolerance:\n", " break\n", "\n", "# after L_max is determined, R_min is also determined\n", "R_min = A**2 / L_max\n" ] }, { "cell_type": "markdown", "id": "2105c43c", "metadata": {}, "source": [ "After determining the first piece of the clothoid curve, the second piece can be obtained simply by mirroring it with respect to $y=-x+R_{eff}$." ] }, { "cell_type": "code", "execution_count": 4, "id": "eed38c95", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.444402Z", "iopub.status.busy": "2023-01-12T04:13:17.444152Z", "iopub.status.idle": "2023-01-12T04:13:17.448264Z", "shell.execute_reply": "2023-01-12T04:13:17.447699Z" } }, "outputs": [], "source": [ "# getting the coordinates of the second clothoid curve by mirroring the first curve with respect to y=-x+R_eff\n", "x3 = np.flipud(R_eff - y1)\n", "y3 = np.flipud(R_eff - x1)\n" ] }, { "cell_type": "markdown", "id": "de05e33b", "metadata": {}, "source": [ "The last step is to determine the circular curve connecting the clothoid curves. This can be done simply by enforcing a circle $(x-a)^2+(y-b)^2=R_{min}^2$ to pass the endpoints of the clothoid curves. Here, we use the `fsolve` function from `scipy.optimize` to solve for $a$ and $b$." ] }, { "cell_type": "code", "execution_count": 5, "id": "108b88fb", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.451842Z", "iopub.status.busy": "2023-01-12T04:13:17.451563Z", "iopub.status.idle": "2023-01-12T04:13:17.458014Z", "shell.execute_reply": "2023-01-12T04:13:17.457506Z" } }, "outputs": [], "source": [ "# solve for the parameters of the circular curve\n", "def circle(var):\n", " a = var[0]\n", " b = var[1]\n", " Func = np.empty((2))\n", " Func[0] = (xp - a) ** 2 + (yp - b) ** 2 - R_min**2\n", " Func[1] = (R_eff - yp - a) ** 2 + (R_eff - xp - b) ** 2 - R_min**2\n", " return Func\n", "\n", "\n", "a, b = fsolve(circle, (0, R_eff))\n", "\n", "# calculate the coordinates of the circular curve\n", "x2 = np.linspace(xp + 0.01, R_eff - yp - 0.01, 50)\n", "y2 = -np.sqrt(R_min**2 - (x2 - a) ** 2) + b\n" ] }, { "cell_type": "markdown", "id": "a469aadb", "metadata": {}, "source": [ "Now we have obtained the coordinates of the whole Euler bend, we can plot it with a conventional circular bend to see the difference. Compared to the circular bend, we can see the Euler bend has a smaller curvature at $(0,0)$ and $(R_{eff},R_{eff})$. This allows a slower transition to and from the straight waveguides, which leads to smaller reflection and scattering loss." ] }, { "cell_type": "code", "execution_count": 6, "id": "418298bf", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.461365Z", "iopub.status.busy": "2023-01-12T04:13:17.461030Z", "iopub.status.idle": "2023-01-12T04:13:17.563296Z", "shell.execute_reply": "2023-01-12T04:13:17.563024Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# obtain the coordinates of the whole Euler bend by concatenating three pieces together\n", "x_euler = np.concatenate((x1, x2, x3))\n", "y_euler = np.concatenate((y1, y2, y3))\n", "\n", "# the conventional circular bend is simply given by a circle\n", "x_circle = np.linspace(0, R_eff, 100)\n", "y_circle = -np.sqrt(R_eff**2 - (x_circle) ** 2) + R_eff\n", "\n", "# plotting the shapes of the Euler bend and the circular bend\n", "plt.plot(x_euler, y_euler, label=\"Euler bend\")\n", "plt.plot(x_circle, y_circle, \"--\", label=\"Circular bend\")\n", "plt.axis(\"equal\")\n", "plt.ylim(-1, R_eff + 1)\n", "plt.legend()\n" ] }, { "cell_type": "markdown", "id": "c4fbcbe4", "metadata": {}, "source": [ "## Loss of a Circular Bend" ] }, { "cell_type": "markdown", "id": "7e4281c7", "metadata": {}, "source": [ "We first simulate a circular waveguide bend as a baseline reference. Then in the next section, we will simulate an Euler bend and compare their losses quantitatively. Both simulations share the same parameters and simulation setup. The only difference is the bend structure." ] }, { "cell_type": "code", "execution_count": 7, "id": "d46ffcb3", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.564908Z", "iopub.status.busy": "2023-01-12T04:13:17.564803Z", "iopub.status.idle": "2023-01-12T04:13:17.567138Z", "shell.execute_reply": "2023-01-12T04:13:17.566904Z" } }, "outputs": [], "source": [ "lda0 = 1.55 # central wavelength\n", "freq0 = td.C_0 / lda0 # central frequency\n", "ldas = np.linspace(1.5, 1.6, 100) # simulation wavelength range\n", "freqs = td.C_0 / ldas # simulation wavelength range\n", "fwidth = 0.5 * (np.max(freqs) - np.min(freqs)) # frequency width of the souce\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "aa37e2e4", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.568597Z", "iopub.status.busy": "2023-01-12T04:13:17.568488Z", "iopub.status.idle": "2023-01-12T04:13:17.570195Z", "shell.execute_reply": "2023-01-12T04:13:17.569949Z" } }, "outputs": [], "source": [ "t = 0.21 # thickness of the waveguide\n", "w = 0.4 # width of the waveguide\n", "inf_eff = 100 # effective infinity of the simulation\n", "buffer = 1 # buffer distance\n" ] }, { "cell_type": "markdown", "id": "a3414324", "metadata": {}, "source": [ "The silicon waveguide on the oxide substrate has an oxide top cladding. Therefore, we will define two materials for the simulations. Both are modeled as non-dispersive in this case." ] }, { "cell_type": "code", "execution_count": 9, "id": "96ca40ac", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.571555Z", "iopub.status.busy": "2023-01-12T04:13:17.571475Z", "iopub.status.idle": "2023-01-12T04:13:17.573474Z", "shell.execute_reply": "2023-01-12T04:13:17.573239Z" } }, "outputs": [], "source": [ "n_si = 3.476 # silicon refractive index\n", "si = td.Medium(permittivity=n_si**2)\n", "\n", "n_sio2 = 1.444 # silicon oxide refractive index\n", "sio2 = td.Medium(permittivity=n_sio2**2)\n" ] }, { "cell_type": "markdown", "id": "f84a97f6", "metadata": {}, "source": [ "In the previous section, we obtained the coordinates that describe the Euler bend and the circular bend. To construct the 3D waveguide bend structure, we define a helper function here. The idea is to take the coordinates of the curve and transform them into the vertices of the waveguide bend with a given width and thickness. Then a 3D structure is created as a [PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.PolySlab.html?highlight=polyslab)." ] }, { "cell_type": "code", "execution_count": 10, "id": "6fad676b", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.574897Z", "iopub.status.busy": "2023-01-12T04:13:17.574797Z", "iopub.status.idle": "2023-01-12T04:13:17.578901Z", "shell.execute_reply": "2023-01-12T04:13:17.578607Z" } }, "outputs": [], "source": [ "# function that takes the x and y coordinates of a curve and returns a waveguide bend structure with a given width and thickness\n", "def line_to_structure(x, y, w, t):\n", " # calculate the inverse of the derivative\n", " k = np.diff(y) / np.diff(x)\n", " k = np.insert(k, 0, 0)\n", "\n", " # compute the coordinates of the upper boundary of the waveguide bend\n", " y_top = w / (2 * np.sqrt(k**2 + 1)) + y\n", " x_top = -k * w / (2 * np.sqrt(k**2 + 1)) + x\n", "\n", " # adding the coordinates of the straight waveguides\n", " x_top = np.insert(x_top, 0, -inf_eff)\n", " y_top = np.insert(y_top, 0, w / 2)\n", " x_top = np.append(x_top, R_eff - w / 2)\n", " y_top = np.append(y_top, inf_eff)\n", "\n", " # compute the coordinates of the lower boundary of the waveguide bend\n", " y_bottom = -w / (2 * np.sqrt(k**2 + 1)) + y\n", " x_bottom = k * w / (2 * np.sqrt(k**2 + 1)) + x\n", "\n", " # adding the coordinates of the straight waveguides\n", " x_bottom = np.insert(x_bottom, 0, -inf_eff)\n", " y_bottom = np.insert(y_bottom, 0, -w / 2)\n", " x_bottom = np.append(x_bottom, R_eff + w / 2)\n", " y_bottom = np.append(y_bottom, inf_eff)\n", "\n", " # construct vertices\n", " x = np.concatenate((x_bottom, np.flipud(x_top)))\n", " y = np.concatenate((y_bottom, np.flipud(y_top)))\n", " vertices = np.transpose(np.vstack((x, y)))\n", "\n", " return td.Structure(\n", " geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t)), medium=si\n", " )\n" ] }, { "cell_type": "markdown", "id": "26c2e973", "metadata": {}, "source": [ "Use the `line_to_structure` function to create the circular bend structure." ] }, { "cell_type": "code", "execution_count": 11, "id": "3a370a01", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.580341Z", "iopub.status.busy": "2023-01-12T04:13:17.580235Z", "iopub.status.idle": "2023-01-12T04:13:17.582559Z", "shell.execute_reply": "2023-01-12T04:13:17.582303Z" } }, "outputs": [], "source": [ "circular_bend = line_to_structure(x_circle, y_circle, w, t)\n" ] }, { "cell_type": "markdown", "id": "97e3cd4b", "metadata": {}, "source": [ "Defined a [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeSource.html) for excitation, a [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FluxMonitor.html) for detecting transmission, and a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) to visualize the field propagation and leakage in the bend. The fundamental TE mode is excited in the input waveguide. All boundaries are set to [PML](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.PML.html) for efficient absorption of the outgoing radiation." ] }, { "cell_type": "code", "execution_count": 12, "id": "ab69656d", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.583998Z", "iopub.status.busy": "2023-01-12T04:13:17.583917Z", "iopub.status.idle": "2023-01-12T04:13:17.691115Z", "shell.execute_reply": "2023-01-12T04:13:17.690866Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# add a mode source that launches the fundamental te mode\n", "mode_source = td.ModeSource(\n", " center=(-buffer, 0, t / 2),\n", " size=(0, 4 * w, 6 * t),\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " direction=\"+\",\n", " mode_spec=td.ModeSpec(num_modes=1, target_neff=n_si),\n", " mode_index=0,\n", ")\n", "\n", "# add a flux monitor to measure transmission\n", "flux_monitor = td.FluxMonitor(\n", " center=(R_eff, R_eff + buffer, t / 2),\n", " size=(4 * w, 0, 6 * t),\n", " freqs=freqs,\n", " name=\"flux\",\n", ")\n", "\n", "# add a field monitor to visualize field propagation and leakage in the bend\n", "field_monitor = td.FieldMonitor(\n", " center=(R_eff / 2, R_eff / 2, t / 2),\n", " size=(td.inf, td.inf, 0),\n", " freqs=[freq0],\n", " colocate=True,\n", " name=\"field\",\n", ")\n", "\n", "run_time = 5e-13 # simulation run time\n", "\n", "# define simulation\n", "sim = td.Simulation(\n", " center=(R_eff / 2, R_eff / 2, t / 2),\n", " size=(R_eff + 2 * w + lda0, R_eff + 2 * w + lda0, 10 * t),\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n", " structures=[circular_bend],\n", " sources=[mode_source],\n", " monitors=[flux_monitor, field_monitor],\n", " run_time=run_time,\n", " boundary_spec=td.BoundarySpec.all_sides(\n", " boundary=td.PML()\n", " ), # pml is applied in all boundaries\n", " medium=sio2,\n", ") # background medium is set to sio2 because of the substrate and upper cladding\n", "\n", "# visualize the circular bend structure\n", "sim.plot(z=0)\n" ] }, { "cell_type": "markdown", "id": "8a311e42", "metadata": {}, "source": [ "Submit the simulation job to the server." ] }, { "cell_type": "code", "execution_count": 13, "id": "bcb827fd", "metadata": { "execution": { "iopub.execute_input": "2023-01-12T04:13:17.692662Z", "iopub.status.busy": "2023-01-12T04:13:17.692549Z", "iopub.status.idle": "2023-01-12T04:13:47.476686Z", "shell.execute_reply": "2023-01-12T04:13:47.476234Z" } }, "outputs": [ { "data": { "text/html": [ "
           INFO     Using Tidy3D credentials from stored file.                                           auth.py:70\n",
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[22:13:19] INFO     Authentication successful.                                                           auth.py:30\n",
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[22:13:20] INFO     Created task 'circular_bend' with task_id '88988a1f-5410-453a-b1f7-bcbd2ade59d7'. webapi.py:120\n",
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[22:13:22] INFO     Maximum FlexUnit cost: 0.025                                                      webapi.py:252\n",
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           INFO     status = queued                                                                   webapi.py:261\n",
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[22:13:29] INFO     starting up solver                                                                webapi.py:277\n",
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[22:13:39] INFO     running solver                                                                    webapi.py:283\n",
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       "                    \"data/simulation_data_circular.hdf5\"                                                           \n",
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    {
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       "
[22:13:47] INFO     loading SimulationData from data/simulation_data_circular.hdf5                    webapi.py:414\n",
       "
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      ],
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       "\u001b[2;36m[22:13:47]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/simulation_data_circular.hdf5                    \u001b]8;id=569068;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=622737;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#414\u001b\\\u001b[2m414\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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     "metadata": {},
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   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"circular_bend\")\n",
    "sim_data_circular = job.run(path=\"data/simulation_data_circular.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "246eba2a",
   "metadata": {},
   "source": [
    "After the simulation is complete, we first plot the bending loss as a function of wavelength. The circular bend exhibits a bending loss ~0.015 dB, which is already pretty low. In many applications, circular waveguide bends can meet the requirement. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0220b917",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:13:47.681168Z",
     "iopub.status.busy": "2023-01-12T04:13:47.681089Z",
     "iopub.status.idle": "2023-01-12T04:13:47.807776Z",
     "shell.execute_reply": "2023-01-12T04:13:47.807537Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Bending loss (dB)')"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T_circular = sim_data_circular[\n",
    "    \"flux\"\n",
    "].flux  # extract the transmission data from the flux monitor\n",
    "\n",
    "# plot the bending loss as a function of wavelength\n",
    "plt.plot(ldas, -10 * np.log10(T_circular))\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(0, 0.03)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Bending loss (dB)\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2856507a",
   "metadata": {},
   "source": [
    "To inspect where the loss occurs in the bend, we plot the field intensity in log scale. Since we will perform the same plot for the Euler bend later on, we define a helper function here.\n",
    "\n",
    "The energy leakage manifests as field intensity outside of the waveguide. Here we can see that a significant leakage occurs around the transition region where the straight waveguide meets the circular waveguide. This is due to the abrupt change of curvature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "63351ecf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:13:47.809423Z",
     "iopub.status.busy": "2023-01-12T04:13:47.809286Z",
     "iopub.status.idle": "2023-01-12T04:13:47.963846Z",
     "shell.execute_reply": "2023-01-12T04:13:47.963581Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_E_in_log(sim_data):\n",
    "    Ex = sim_data[\"field\"].Ex.abs\n",
    "    Ey = sim_data[\"field\"].Ey.abs\n",
    "    Ez = sim_data[\"field\"].Ez.abs\n",
    "    E = np.log10(Ex**2 + Ey**2 + Ez**2)\n",
    "    E.plot(x=\"x\", vmin=-1, vmax=5, cmap=plt.cm.nipy_spectral)\n",
    "\n",
    "\n",
    "# since some field values will be very close to 0, numpy will throw a warning when taking the log10\n",
    "# here we turn off numpy warning\n",
    "np.seterr(divide=\"ignore\")\n",
    "plot_E_in_log(sim_data_circular)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a3567d4",
   "metadata": {},
   "source": [
    "## Loss of an Euler Bend"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86b1f580",
   "metadata": {},
   "source": [
    "Next, we perform a similar simulation for the Euler waveguide bend and compare the results to the circular bend. The Euler waveguide bend structure is made by using the `line_to_structure` function we defined earlier. Since the simulation setup is the same as the previous one with the only difference being the structures, we can simply copy the previous simulation and update the structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "498b1288",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:13:47.965426Z",
     "iopub.status.busy": "2023-01-12T04:13:47.965316Z",
     "iopub.status.idle": "2023-01-12T04:13:48.071975Z",
     "shell.execute_reply": "2023-01-12T04:13:48.071718Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       ""
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the euler waveguide bend structure\n",
    "euler_bend = line_to_structure(x_euler, y_euler, w, t)\n",
    "\n",
    "# construct the simulation by copying the previous simulation and updating the structure\n",
    "sim = sim.copy(update={\"structures\": [euler_bend]})\n",
    "\n",
    "# visualize the euler bend structure\n",
    "sim.plot(z=0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "890172b2",
   "metadata": {},
   "source": [
    "Submit the simulation to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9533e5ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:13:48.073445Z",
     "iopub.status.busy": "2023-01-12T04:13:48.073340Z",
     "iopub.status.idle": "2023-01-12T04:14:20.865480Z",
     "shell.execute_reply": "2023-01-12T04:14:20.865118Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
[22:13:48] INFO     Created task 'circular_bend' with task_id '7684de33-1890-4117-97d0-0749f6e67a09'. webapi.py:120\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:13:48]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Created task \u001b[32m'circular_bend'\u001b[0m with task_id \u001b[32m'7684de33-1890-4117-97d0-0749f6e67a09'\u001b[0m. \u001b]8;id=553963;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=661548;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": [
       "\u001b[?25l"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a79e3b97050a4e318777918492cb3237",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n",
       "\u001b[?25h"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[22:13:50] INFO     Maximum FlexUnit cost: 0.025                                                      webapi.py:252\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:13:50]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Maximum FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                      \u001b]8;id=445218;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=980857;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#252\u001b\\\u001b[2m252\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
           INFO     status = queued                                                                   webapi.py:261\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = queued                                                                   \u001b]8;id=609806;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=431199;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#261\u001b\\\u001b[2m261\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": [
       "\u001b[?25l"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a2f4fbb5d5c9414fb451403b3adce7e1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[22:13:53] INFO     status = preprocess                                                               webapi.py:273\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:13:53]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = preprocess                                                               \u001b]8;id=815042;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=129728;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#273\u001b\\\u001b[2m273\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n",
       "\u001b[?25h\r",
       "\u001b[1A\u001b[2K"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[22:13:59] INFO     starting up solver                                                                webapi.py:277\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:13:59]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m starting up solver                                                                \u001b]8;id=718445;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=923228;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#277\u001b\\\u001b[2m277\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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     "metadata": {},
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[22:14:10] INFO     running solver                                                                    webapi.py:283\n",
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       "\u001b[2;36m[22:14:10]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m running solver                                                                    \u001b]8;id=438120;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=177832;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#283\u001b\\\u001b[2m283\u001b[0m\u001b]8;;\u001b\\\n"
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[22:14:16] INFO     early shutoff detected, exiting.                                                  webapi.py:294\n",
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       "\u001b[2;36m[22:14:16]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m early shutoff detected, exiting.                                                  \u001b]8;id=672795;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=50838;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#294\u001b\\\u001b[2m294\u001b[0m\u001b]8;;\u001b\\\n"
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           INFO     status = postprocess                                                              webapi.py:300\n",
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                                              \u001b]8;id=316060;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=259926;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
[22:14:18] INFO     status = success                                                                  webapi.py:306\n",
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      ],
      "text/plain": [
       "\u001b[2;36m[22:14:18]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = success                                                                  \u001b]8;id=912716;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=629668;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#306\u001b\\\u001b[2m306\u001b[0m\u001b]8;;\u001b\\\n"
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       "\n",
       "\u001b[?25h\r",
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    },
    {
     "data": {
      "text/html": [
       "
           INFO     Billed FlexUnit cost: 0.025                                                       webapi.py:310\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                       \u001b]8;id=548291;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=824935;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#310\u001b\\\u001b[2m310\u001b[0m\u001b]8;;\u001b\\\n"
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
           INFO     downloading file \"output/monitor_data.hdf5\" to \"data/simulation_data_euler.hdf5\"  webapi.py:592\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m downloading file \u001b[32m\"output/monitor_data.hdf5\"\u001b[0m to \u001b[32m\"data/simulation_data_euler.hdf5\"\u001b[0m  \u001b]8;id=715217;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=884303;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#592\u001b\\\u001b[2m592\u001b[0m\u001b]8;;\u001b\\\n"
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     "metadata": {},
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    },
    {
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       "
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       "\u001b[?25l"
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     "metadata": {},
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    {
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      "text/plain": [
       "Output()"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n",
       "\u001b[?25h"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[22:14:20] INFO     loading SimulationData from data/simulation_data_euler.hdf5                       webapi.py:414\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:14:20]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/simulation_data_euler.hdf5                       \u001b]8;id=617788;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=923982;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#414\u001b\\\u001b[2m414\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"circular_bend\")\n",
    "sim_data_euler = job.run(path=\"data/simulation_data_euler.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4a8247d",
   "metadata": {},
   "source": [
    "After the simulation is complete, we plot the bending loss of the Euler bend against that of the circular bend. Here we see that the Euler bend has a lower loss ~0.005 dB. In terms of absolute loss, both bends are very good. However, when a large number of waveguide bends are used in an integrated photonic circuit, the advantage of the Euler bend can be quite significant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "67b89904",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:14:21.131612Z",
     "iopub.status.busy": "2023-01-12T04:14:21.131533Z",
     "iopub.status.idle": "2023-01-12T04:14:21.217570Z",
     "shell.execute_reply": "2023-01-12T04:14:21.217334Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       ""
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T_euler = sim_data_euler[\"flux\"].flux\n",
    "plt.plot(ldas, -10 * np.log10(T_circular), label=\"Circular bend\")\n",
    "plt.plot(ldas, -10 * np.log10(T_euler), label=\"Euler bend\")\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(0, 0.03)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Bending loss (dB)\")\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e82a59f",
   "metadata": {},
   "source": [
    "Similarly, we plot the field intensity in log scale. From the plot, we can see that the leakage around the transition regions is indeed reduced. This is due to the fact that the curvature of the Euler curve varies smoothly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ba05d415",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-01-12T04:14:21.219236Z",
     "iopub.status.busy": "2023-01-12T04:14:21.219078Z",
     "iopub.status.idle": "2023-01-12T04:14:21.429585Z",
     "shell.execute_reply": "2023-01-12T04:14:21.429313Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_E_in_log(sim_data_euler)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1900f052",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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% done (field decay = 1.35e-06) ━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━  68% 0:00:02\n% done (field decay = 1.35e-06) ━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━  68% 0:00:02
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↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/14.3 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/14.3 kB • ? • -:--:--
\n",
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% done (field decay = 5.28e-06) ━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━  68% -:--:--\n% done (field decay = 5.28e-06) ━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━  68% -:--:--
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↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/18.4 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/18.4 kB • ? • -:--:--
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