{ "cells": [ { "cell_type": "markdown", "id": "da3f0190", "metadata": {}, "source": [ "# Waveguide Y junction" ] }, { "cell_type": "markdown", "id": "eab8c7bd", "metadata": {}, "source": [ "Power splitters such as Y-junctions are widely used in photonic integrated circuits across different applications. When designing a power splitter, we aim to achieve a flat broadband response, low insertion loss, and compact footprint. At the same time, the design needs to comply with the fabrication resolution and tolerance.\n", "\n", "In this example, we demonstrate the modeling of a Y-junction for integrated photonics. The designed device shows an average insertion loss below 0.2 dB in the wavelength range of 1500 nm to 1600 nm. At the same time, it has a small footprint. The junction area is smaller than 2 $\\mu m$ by 2 $\\mu m$, much smaller than the typical power splitters based on multimode interference devices. The design is adapted from [Yi Zhang, Shuyu Yang, Andy Eu-Jin Lim, Guo-Qiang Lo, Christophe Galland, Tom Baehr-Jones, and Michael Hochberg, \"A compact and low loss Y-junction for submicron silicon waveguide,\" Opt. Express 21, 1310-1316 (2013)](https://opg.optica.org/oe/fulltext.cfm?uri=oe-21-1-1310).\n", "\n", "\"Schematic\n", "\n", "For more integrated photonic examples such as the [8-Channel mode and polarization de-multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/8ChannelDemultiplexer/), the [broadband bi-level taper polarization rotator-splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/), and the [broadband directional coupler](https://www.flexcompute.com/tidy3d/examples/notebooks/BroadbandDirectionalCoupler/), please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/).\n", "\n", "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. " ] }, { "cell_type": "code", "execution_count": 1, "id": "ad43045e", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:02.306336Z", "iopub.status.busy": "2023-03-27T23:47:02.306184Z", "iopub.status.idle": "2023-03-27T23:47:03.664582Z", "shell.execute_reply": "2023-03-27T23:47:03.664014Z" } }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import gdstk\n", "\n", "import tidy3d as td\n", "import tidy3d.web as web\n", "from tidy3d.plugins.mode import ModeSolver\n" ] }, { "cell_type": "markdown", "id": "128b718e", "metadata": {}, "source": [ "## Simulation Setup " ] }, { "cell_type": "markdown", "id": "c26dafaa", "metadata": {}, "source": [ "Define simulation wavelength range to be 1.5 $\\mu m$ to 1.6 $\\mu m$." ] }, { "cell_type": "code", "execution_count": 2, "id": "3a2dd129", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:03.667202Z", "iopub.status.busy": "2023-03-27T23:47:03.666920Z", "iopub.status.idle": "2023-03-27T23:47:03.686371Z", "shell.execute_reply": "2023-03-27T23:47:03.685840Z" } }, "outputs": [], "source": [ "lda0 = 1.55 # central wavelength\n", "freq0 = td.C_0 / lda0 # central frequency\n", "ldas = np.linspace(1.5, 1.6, 101) # wavelength range\n", "freqs = td.C_0 / ldas # frequency range\n" ] }, { "cell_type": "markdown", "id": "946d0a45", "metadata": {}, "source": [ "In this model, the Y-junction is made of silicon. The top and bottom claddings are made of silicon oxide. We will model them as non-dispersive materials here." ] }, { "cell_type": "code", "execution_count": 3, "id": "b90f342c", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:03.688684Z", "iopub.status.busy": "2023-03-27T23:47:03.688526Z", "iopub.status.idle": "2023-03-27T23:47:03.707421Z", "shell.execute_reply": "2023-03-27T23:47:03.706885Z" } }, "outputs": [], "source": [ "n_si = 3.48 # silicon refractive index\n", "si = td.Medium(permittivity=n_si**2)\n", "\n", "n_sio2 = 1.44 # silicon oxide refractive index\n", "sio2 = td.Medium(permittivity=n_sio2**2)\n" ] }, { "cell_type": "markdown", "id": "473f2133", "metadata": {}, "source": [ "The junction is discretized into 13 segments. Each segment is a tapper with the given widths. The optimum design is obtained by optimizing the 13 width parameters using the Particle Swarm Optimization algorithm. For the sake of simplicity, in this notebook, we skip the optimization procedure and only present the optimized result." ] }, { "cell_type": "code", "execution_count": 4, "id": "c67cbbf5", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:03.709835Z", "iopub.status.busy": "2023-03-27T23:47:03.709661Z", "iopub.status.idle": "2023-03-27T23:47:03.729588Z", "shell.execute_reply": "2023-03-27T23:47:03.729044Z" } }, "outputs": [], "source": [ "t = 0.22 # thickness of the silicon layer\n", "\n", "# width of the 13 segments\n", "w1 = 0.5\n", "w2 = 0.5\n", "w3 = 0.6\n", "w4 = 0.7\n", "w5 = 0.9\n", "w6 = 1.26\n", "w7 = 1.4\n", "w8 = 1.4\n", "w9 = 1.4\n", "w10 = 1.4\n", "w11 = 1.31\n", "w12 = 1.2\n", "w13 = 1.2\n", "\n", "l_in = 1 # input waveguide length\n", "l_junction = 2 # length of the junction\n", "l_bend = 6 # horizontal length of the waveguide bend\n", "h_bend = 2 # vertical offset of the waveguide bend\n", "l_out = 1 # output waveguide length\n", "inf_eff = 100 # effective infinity\n" ] }, { "cell_type": "markdown", "id": "98ae6d2c", "metadata": {}, "source": [ "First, define the junction structure by using a [PolySlab](../_autosummary/tidy3d.PolySlab.html). The vertices are given by the widths of the segments defined above. If a smooth curve is desirable, one can interpolate the vertices to a finer grid using spline for example. \n", "\n", "Before proceeding further to construct other structures, we can use the `plot` method to inspect the geometry. " ] }, { "cell_type": "code", "execution_count": 5, "id": "f1bd7cba", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:03.731924Z", "iopub.status.busy": "2023-03-27T23:47:03.731752Z", "iopub.status.idle": "2023-03-27T23:47:04.120469Z", "shell.execute_reply": "2023-03-27T23:47:04.119990Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x = np.linspace(l_in, l_in + l_junction, 13) # x coordinates of the top edge vertices\n", "y = np.array(\n", " [w1, w2, w3, w4, w5, w6, w7, w8, w9, w10, w11, w12, w13]\n", ") # y coordinates of the top edge vertices\n", "\n", "# using concatenate to include bottom edge vertices\n", "x = np.concatenate((x, np.flipud(x)))\n", "y = np.concatenate((y / 2, -np.flipud(y / 2)))\n", "\n", "# stacking x and y coordinates to form vertices pairs\n", "vertices = np.transpose(np.vstack((x, y)))\n", "\n", "junction = td.Structure(\n", " geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t)), medium=si\n", ")\n", "junction.plot(z=t / 2)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "f33fc2d8", "metadata": {}, "source": [ "For the output waveguide bends, we use S bend sine waveguides, which are described by the function\n", "
$y = \\frac{xh_{band}}{l_{bend}}-\\frac{h_{bend}}{2\\pi}sin(\\frac{2\\pi x}{l_{bend}})$.
\n", "\n", "Different types of bend can also be used here for similar performance. To define the bends, the most convenient way is to use `gdstk`. First compute the $x$ and $y$ coordinates of the bend, then define a `FlexPath` and add it to a gds cell. The paths in the cell can be converted to Tidy3D [PolySlabs](../_autosummary/tidy3d.PolySlab.html) using the `from_gds` method." ] }, { "cell_type": "code", "execution_count": 6, "id": "2f517ebb", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.122624Z", "iopub.status.busy": "2023-03-27T23:47:04.122434Z", "iopub.status.idle": "2023-03-27T23:47:04.400328Z", "shell.execute_reply": "2023-03-27T23:47:04.399604Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x_start = l_in + l_junction # x coordinate of the starting point of the waveguide bends\n", "\n", "x = np.linspace(\n", " x_start, x_start + l_bend, 100\n", ") # x coordinates of the top edge vertices\n", "\n", "y = (\n", " (x - x_start) * h_bend / l_bend\n", " - h_bend * np.sin(2 * np.pi * (x - x_start) / l_bend) / (np.pi * 2)\n", " + w13 / 2 - w1/2\n", ") # y coordinates of the top edge vertices\n", "\n", "# adding the last point to include the straight waveguide at the output\n", "x = np.append(x, inf_eff)\n", "y = np.append(y, y[-1])\n", "\n", "# add path to the cell\n", "cell = gdstk.Cell(\"bends\")\n", "cell.add(gdstk.FlexPath(x + 1j * y, w1, layer=1, datatype=0)) # top waveguide bend\n", "cell.add(gdstk.FlexPath(x - 1j * y, w1, layer=1, datatype=0)) # bottom waveguide bend\n", "\n", "# define top waveguide bend structure\n", "wg_bend_1 = td.Structure(\n", " geometry=td.PolySlab.from_gds(\n", " cell,\n", " gds_layer=1,\n", " axis=2,\n", " slab_bounds=(0, t),\n", " )[0], \n", " medium=si\n", ")\n", "\n", "# define bottom waveguide bend structure\n", "wg_bend_2 = td.Structure(\n", " geometry=td.PolySlab.from_gds(\n", " cell,\n", " gds_layer=1,\n", " axis=2,\n", " slab_bounds=(0, t),\n", " )[1], \n", " medium=si\n", ")\n", "\n", "# plot the top waveguide bend to visualize\n", "ax = wg_bend_1.plot(z=t / 2)\n", "ax.set_xlim(2, 10)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "fecdf772", "metadata": {}, "source": [ "Lastly, define the straight input waveguide using [Box](../_autosummary/tidy3d.Box.html)." ] }, { "cell_type": "code", "execution_count": 7, "id": "37f3f2e2", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.403908Z", "iopub.status.busy": "2023-03-27T23:47:04.403632Z", "iopub.status.idle": "2023-03-27T23:47:04.426202Z", "shell.execute_reply": "2023-03-27T23:47:04.425595Z" } }, "outputs": [], "source": [ "# straight input waveguide\n", "wg_in = td.Structure(\n", " geometry=td.Box.from_bounds(rmin=(-inf_eff, -w1 / 2, 0), rmax=(l_in, w1 / 2, t)),\n", " medium=si,\n", ")\n", "\n", "# the entire model is the collection of all structures defined so far\n", "y_junction = [wg_in, junction, wg_bend_1, wg_bend_2]\n" ] }, { "cell_type": "markdown", "id": "051768d5", "metadata": {}, "source": [ "Define the simulation domain. Here we ensure sufficient buffer spacing in each direction. In general, we want to make sure that the structure is at least half a wavelength away from the domain boundaries unless it goes into the PML." ] }, { "cell_type": "code", "execution_count": 8, "id": "f0cef4aa", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.428769Z", "iopub.status.busy": "2023-03-27T23:47:04.428500Z", "iopub.status.idle": "2023-03-27T23:47:04.451219Z", "shell.execute_reply": "2023-03-27T23:47:04.450498Z" } }, "outputs": [], "source": [ "Lx = l_in + l_junction + l_out + l_bend # simulation domain size in x direction\n", "Ly = w13 + 2 * h_bend + 1.5 * lda0 # simulation domain size in y direction\n", "Lz = 10 * t # simulation domain size in z direction\n", "sim_size = (Lx, Ly, Lz)\n" ] }, { "cell_type": "markdown", "id": "4eaa0e1e", "metadata": {}, "source": [ "We will use a [ModeSource](../_autosummary/tidy3d.ModeSource.html) to excite the input waveguide using the fundamental TE mode. \n", "\n", "A [ModeMonitor](../_autosummary/tidy3d.ModeMonitor.html) is placed at the top output waveguide to measure the transmission. A [FieldMonitor](../_autosummary/tidy3d.FieldMonitor.html) is added to the xy plane to visualize the power flow." ] }, { "cell_type": "code", "execution_count": 9, "id": "dbf57f31", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.454505Z", "iopub.status.busy": "2023-03-27T23:47:04.454128Z", "iopub.status.idle": "2023-03-27T23:47:04.481248Z", "shell.execute_reply": "2023-03-27T23:47:04.480571Z" } }, "outputs": [], "source": [ "# add a mode source as excitation\n", "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n", "mode_source = td.ModeSource(\n", " center=(l_in / 2, 0, t / 2),\n", " size=(0, 4 * w1, 6 * t),\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10),\n", " direction=\"+\",\n", " mode_spec=mode_spec,\n", " mode_index=0,\n", ")\n", "\n", "# add a mode monitor to measure transmission at the output waveguide\n", "mode_monitor = td.ModeMonitor(\n", " center=(l_in + l_junction + l_bend + l_out / 2, w13 / 2 - w1 / 2 + h_bend, t / 2),\n", " size=(0, 4 * w1, 6 * t),\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " name=\"mode\",\n", ")\n", "\n", "# add a field monitor to visualize field distribution at z=t/2\n", "field_monitor = td.FieldMonitor(\n", " center=(0, 0, t / 2), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n", ")\n" ] }, { "cell_type": "markdown", "id": "725eee9e", "metadata": {}, "source": [ "Set up the simulation with the previously defined structures, source, and monitors. All boundaries are set to PML to mimic infinite open space. Since the top and bottom claddings are silicon oxide, we will set the medium of the background to silicon oxide. \n", "\n", "In principle, we can impose symmetry to reduce the computational load. Since this model is relatively small and quick to solve, we will simply model the whole device without using symmetry." ] }, { "cell_type": "code", "execution_count": 10, "id": "9a4ec279", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.483609Z", "iopub.status.busy": "2023-03-27T23:47:04.483432Z", "iopub.status.idle": "2023-03-27T23:47:04.867253Z", "shell.execute_reply": "2023-03-27T23:47:04.866650Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# construct simulation\n", "sim = td.Simulation(\n", " center=(Lx / 2, 0, 0),\n", " size=sim_size,\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=30, wavelength=lda0),\n", " structures=y_junction,\n", " sources=[mode_source],\n", " monitors=[mode_monitor, field_monitor],\n", " run_time=5e-13,\n", " boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n", " medium=sio2,\n", ")\n", "\n", "sim.plot(z=0)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "f7f50958", "metadata": {}, "source": [ "Before submitting the simulation to the server, it is a good practice to visualize the mode profile at the [ModeSource](../_autosummary/tidy3d.ModeSource.html) to ensure we are launching the fundamental TE mode. To do so, we will use the [ModeSolver](../_autosummary/tidy3d.plugins.mode.ModeSolver.html) plugin, which solves for the mode profile on your local computer." ] }, { "cell_type": "code", "execution_count": 11, "id": "da2af982", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:04.869381Z", "iopub.status.busy": "2023-03-27T23:47:04.869214Z", "iopub.status.idle": "2023-03-27T23:47:05.904447Z", "shell.execute_reply": "2023-03-27T23:47:05.903861Z" } }, "outputs": [], "source": [ "mode_solver = ModeSolver(\n", " simulation=sim,\n", " plane=td.Box(center=mode_source.center, size=mode_source.size),\n", " mode_spec=mode_spec,\n", " freqs=[freq0],\n", ")\n", "mode_data = mode_solver.solve()\n" ] }, { "cell_type": "markdown", "id": "1c0322c9", "metadata": {}, "source": [ "Visualize the mode profile. We confirm that we are exciting the waveguide with the fundamental TE mode." ] }, { "cell_type": "code", "execution_count": 12, "id": "a2e49017", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:05.906972Z", "iopub.status.busy": "2023-03-27T23:47:05.906767Z", "iopub.status.idle": "2023-03-27T23:47:06.522409Z", "shell.execute_reply": "2023-03-27T23:47:06.521796Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(10, 3))\n", "abs(mode_data.Ex.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax1, cmap=\"magma\")\n", "abs(mode_data.Ey.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax2, cmap=\"magma\")\n", "abs(mode_data.Ez.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax3, cmap=\"magma\")\n", "\n", "ax1.set_title(\"|Ex(x, y)|\")\n", "ax1.set_aspect(\"equal\")\n", "ax2.set_title(\"|Ey(x, y)|\")\n", "ax2.set_aspect(\"equal\")\n", "ax3.set_title(\"|Ez(x, y)|\")\n", "ax3.set_aspect(\"equal\")\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "7e904938", "metadata": {}, "source": [ "Now that we verified all the settings, we are ready to submit the simulation job to the server. Before running the simulation, we can get a cost estimation using `estimate_cost`. This prevents us from accidentally running large jobs that we set up by mistake. The estimated cost is the maximum cost corresponding to running all the time steps." ] }, { "cell_type": "code", "execution_count": 13, "id": "15e791dd", "metadata": { "execution": { "iopub.execute_input": "2023-03-27T23:47:06.525276Z", "iopub.status.busy": "2023-03-27T23:47:06.525074Z", "iopub.status.idle": "2023-03-27T23:48:54.178263Z", "shell.execute_reply": "2023-03-27T23:48:54.177662Z" } }, "outputs": [ { "data": { "text/html": [ "
[16:37:33] Created task 'y_junction' with task_id 'fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1'.      webapi.py:186\n",
       "
\n" ], "text/plain": [ "\u001b[2;36m[16:37:33]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'y_junction'\u001b[0m with task_id \u001b[32m'fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1'\u001b[0m. \u001b]8;id=959128;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=156592;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#186\u001b\\\u001b[2m186\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
           View task using web UI at                                                                  webapi.py:188\n",
       "           'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f715              \n",
       "           1v1'.                                                                                                   \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at \u001b]8;id=257517;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=163005;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#188\u001b\\\u001b[2m188\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[2;36m \u001b[0m\u001b]8;id=27493;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=858598;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27493;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=274481;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27493;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32m-a45843c9-86bc-45c9-9a97-24fd427f715\u001b[0m\u001b]8;;\u001b\\ \u001b[2m \u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b]8;id=27493;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a45843c9-86bc-45c9-9a97-24fd427f7151v1\u001b\\\u001b[32m1v1'\u001b[0m\u001b]8;;\u001b\\. \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "48dab8375b574639b3bc47b9d2267b43", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
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       "
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       "\n"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The estimated maximum cost is 0.171 Flex Credits.\n"
     ]
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"y_junction\", verbose=True)\n",
    "estimated_cost = web.estimate_cost(job.task_id)\n",
    "\n",
    "print(f'The estimated maximum cost is {estimated_cost:.3f} Flex Credits.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cedcee1e",
   "metadata": {},
   "source": [
    "The cost is reasonaly so we can run the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "73df031e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "
[16:37:36] status = queued                                                                            webapi.py:321\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[16:37:36]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=91486;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=367621;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#321\u001b\\\u001b[2m321\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[16:37:38] status = preprocess                                                                        webapi.py:315\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[16:37:38]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=366221;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=41391;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#315\u001b\\\u001b[2m315\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    },
    {
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      "text/html": [
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      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[16:37:46] Maximum FlexCredit cost: 0.171. Use 'web.real_cost(task_id)' to get the billed FlexCredit  webapi.py:338\n",
       "           cost after a simulation run.                                                                            \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m[16:37:46]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.171\u001b[0m. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit  \u001b]8;id=48800;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=472084;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#338\u001b\\\u001b[2m338\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mcost after a simulation run.                                                               \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
           starting up solver                                                                         webapi.py:342\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=266358;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=433960;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#342\u001b\\\u001b[2m342\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "
           running solver                                                                             webapi.py:352\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=782948;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=823262;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#352\u001b\\\u001b[2m352\u001b[0m\u001b]8;;\u001b\\\n"
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     },
     "metadata": {},
     "output_type": "display_data"
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[16:38:22] early shutoff detected, exiting.                                                           webapi.py:366\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[16:38:22]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=257803;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=714548;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#366\u001b\\\u001b[2m366\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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     "output_type": "display_data"
    },
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
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           status = postprocess                                                                       webapi.py:383\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=182747;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=539992;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#383\u001b\\\u001b[2m383\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
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[16:38:38] status = success                                                                           webapi.py:390\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[16:38:38]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=184546;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=745126;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#390\u001b\\\u001b[2m390\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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    },
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     },
     "metadata": {},
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       "Output()"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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      ],
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     "metadata": {},
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    },
    {
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       "
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      ],
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     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
[16:38:41] loading SimulationData from data/simulation_data.hdf5                                      webapi.py:568\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[16:38:41]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/simulation_data.hdf5                                      \u001b]8;id=929334;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=985273;file://C:\\Users\\xinzhong\\anaconda3\\envs\\tidy3d_env\\lib\\site-packages\\tidy3d\\web\\webapi.py#568\u001b\\\u001b[2m568\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec4554c",
   "metadata": {},
   "source": [
    "## Result Visualization "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17041534",
   "metadata": {},
   "source": [
    "After the simulation is complete, we first inspect the insertion loss. Within this wavelength range, we see that the insertion loss is generally below 0.2 dB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "04666ade",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:48:55.903495Z",
     "iopub.status.busy": "2023-03-27T23:48:55.903357Z",
     "iopub.status.idle": "2023-03-27T23:48:56.100573Z",
     "shell.execute_reply": "2023-03-27T23:48:56.100062Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# extract the transmission data from the mode monitor\n",
    "amp = sim_data[\"mode\"].amps.sel(mode_index=0, direction=\"+\")\n",
    "T = np.abs(amp)**2 \n",
    "\n",
    "plt.plot(ldas, -10 * np.log10(2 * T))\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(0, 0.5)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Insertion loss (dB)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d9e0403",
   "metadata": {},
   "source": [
    "We can also visualize the field distribution. Here we can see the interference in the junction while no visible higher order modes are excited at the output waveguides."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e44e8128",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:48:56.102690Z",
     "iopub.status.busy": "2023-03-27T23:48:56.102524Z",
     "iopub.status.idle": "2023-03-27T23:48:57.648019Z",
     "shell.execute_reply": "2023-03-27T23:48:57.647600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data.plot_field(\n",
    "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", f=freq0, vmin=0, vmax=2000\n",
    ")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "016a3a86",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "description": "This notebook demonstrates how to simulate a waveguide Y junction in Tidy3D FDTD.",
  "feature_image": "./img/y_junction_schematic.png",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "Y junction, T branch, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  },
  "title": "How to model a waveguide Y junction in Tidy3D FDTD",
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