diff --git a/WaveguideToRingCoupling.ipynb b/WaveguideToRingCoupling.ipynb index f9974433..65648304 100644 --- a/WaveguideToRingCoupling.ipynb +++ b/WaveguideToRingCoupling.ipynb @@ -30,14 +30,7 @@ "cell_type": "code", "execution_count": 1, "id": "878ff685", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:41.153540Z", - "iopub.status.busy": "2023-08-19T01:57:41.153364Z", - "iopub.status.idle": "2023-08-19T01:57:42.759414Z", - "shell.execute_reply": "2023-08-19T01:57:42.758490Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", @@ -69,14 +62,7 @@ "cell_type": "code", "execution_count": 2, "id": "51e608fa", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.762692Z", - "iopub.status.busy": "2023-08-19T01:57:42.762328Z", - "iopub.status.idle": "2023-08-19T01:57:42.784004Z", - "shell.execute_reply": "2023-08-19T01:57:42.782345Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "lda0 = 1.55 # central wavelength\n", @@ -98,14 +84,7 @@ "cell_type": "code", "execution_count": 3, "id": "c889b560", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.789979Z", - "iopub.status.busy": "2023-08-19T01:57:42.789589Z", - "iopub.status.idle": "2023-08-19T01:57:42.818291Z", - "shell.execute_reply": "2023-08-19T01:57:42.817690Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# define silicon and silicon dioxide media from the material library\n", @@ -125,14 +104,7 @@ "cell_type": "code", "execution_count": 4, "id": "3b9ec897", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.820689Z", - "iopub.status.busy": "2023-08-19T01:57:42.820484Z", - "iopub.status.idle": "2023-08-19T01:57:42.842930Z", - "shell.execute_reply": "2023-08-19T01:57:42.842295Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "w = 0.5 # width of the waveguide\n", @@ -159,14 +131,7 @@ "cell_type": "code", "execution_count": 5, "id": "63cbe626", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.845559Z", - "iopub.status.busy": "2023-08-19T01:57:42.845378Z", - "iopub.status.idle": "2023-08-19T01:57:42.867210Z", - "shell.execute_reply": "2023-08-19T01:57:42.866579Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "def straight_waveguide(x0, y0, z0, x1, y1, wg_width, wg_thickness, medium, sidewall_angle=0):\n", @@ -212,14 +177,7 @@ "cell_type": "code", "execution_count": 6, "id": "844820b8", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.869756Z", - "iopub.status.busy": "2023-08-19T01:57:42.869603Z", - "iopub.status.idle": "2023-08-19T01:57:42.892940Z", - "shell.execute_reply": "2023-08-19T01:57:42.892229Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "def ring_resonator(\n", @@ -310,14 +268,7 @@ "cell_type": "code", "execution_count": 7, "id": "af37300c", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.896042Z", - "iopub.status.busy": "2023-08-19T01:57:42.895847Z", - "iopub.status.idle": "2023-08-19T01:57:42.925488Z", - "shell.execute_reply": "2023-08-19T01:57:42.924785Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# define straight waveguide\n", @@ -358,37 +309,8 @@ "cell_type": "code", "execution_count": 8, "id": "68e1f253", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:42.928530Z", - "iopub.status.busy": "2023-08-19T01:57:42.928346Z", - "iopub.status.idle": "2023-08-19T01:57:43.119830Z", - "shell.execute_reply": "2023-08-19T01:57:43.119201Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
[18:57:43] WARNING: Default value for the field monitor           monitor.py:261\n",
-       "           'colocate' setting has changed to 'True' in Tidy3D                   \n",
-       "           2.4.0. All field components will be colocated to the                 \n",
-       "           grid boundaries. Set to 'False' to get the raw fields                \n",
-       "           on the Yee grid instead.                                             \n",
-       "
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Set to \u001b[0m\u001b[32m'False'\u001b[0m\u001b[31m to get the raw fields \u001b[0m \u001b[2m \u001b[0m\n", - "\u001b[2;36m \u001b[0m\u001b[31mon the Yee grid instead. \u001b[0m \u001b[2m \u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ "n_si = 3.47\n", "# mode spec for the source\n", @@ -456,26 +378,11 @@ "cell_type": "code", "execution_count": 9, "id": "c0095a90", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:43.122459Z", - "iopub.status.busy": "2023-08-19T01:57:43.122288Z", - "iopub.status.idle": "2023-08-19T01:57:43.411245Z", - "shell.execute_reply": "2023-08-19T01:57:43.410673Z" - } - }, + "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/momchil/miniconda3/envs/tidy3d-docs/lib/python3.9/site-packages/shapely/set_operations.py:133: RuntimeWarning: invalid value encountered in intersection\n", - " return lib.intersection(a, b, **kwargs)\n" - ] - }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -518,25 +425,18 @@ "cell_type": "code", "execution_count": 10, "id": "b0eb7ca6", - "metadata": { - "execution": { - "iopub.execute_input": "2023-08-19T01:57:43.413417Z", - "iopub.status.busy": "2023-08-19T01:57:43.413246Z", - "iopub.status.idle": "2023-08-19T01:59:52.201635Z", - "shell.execute_reply": "2023-08-19T01:59:52.201088Z" - } - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
           Created task 'waveguide_to_ring' with task_id           webapi.py:188\n",
-       "           'fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1'.                       \n",
+       "
16:05:18 PST Created task 'waveguide_to_ring' with task_id                      \n",
+       "             'fdve-f6a84898-dd7d-4874-98c4-87b4d3705495' and task_type 'FDTD'.  \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'waveguide_to_ring'\u001b[0m with task_id           \u001b]8;id=694315;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=160214;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\u001b\\\u001b[2m188\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1'\u001b[0m.          \u001b[2m             \u001b[0m\n"
+       "\u001b[2;36m16:05:18 PST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'waveguide_to_ring'\u001b[0m with task_id                      \n",
+       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-f6a84898-dd7d-4874-98c4-87b4d3705495'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
       ]
      },
      "metadata": {},
@@ -545,15 +445,15 @@
     {
      "data": {
       "text/html": [
-       "
           View task using web UI at                               webapi.py:190\n",
-       "           'https://tidy3d.simulation.cloud/workbench?taskId=fdve-              \n",
-       "           36b213bb-ae23-4827-ab34-b31816ebae25v1'.                             \n",
+       "
             View task using web UI at                                          \n",
+       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7\n",
+       "             d-4874-98c4-87b4d3705495'.                                         \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                               \u001b]8;id=881061;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=941911;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\u001b\\\u001b[2m190\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m           \u001b[0m\u001b]8;id=2633;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=299729;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=2633;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=519976;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=2633;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32m-\u001b[0m\u001b]8;;\u001b\\ \u001b[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0m\u001b]8;id=2633;https://tidy3d.simulation.cloud/workbench?taskId=fdve-36b213bb-ae23-4827-ab34-b31816ebae25v1\u001b\\\u001b[32m36b213bb-ae23-4827-ab34-b31816ebae25v1'\u001b[0m\u001b]8;;\u001b\\.                \u001b[2m             \u001b[0m\n"
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=533705;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=142950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=533705;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=820861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=533705;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32m-f6a84898-dd7\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=533705;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[32md-4874-98c4-87b4d3705495'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
       ]
      },
      "metadata": {},
@@ -562,7 +462,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0d1fc80e8e10486e8f29ee66324e9ca5",
+       "model_id": "481dd5ca1f274a4f9a6275fcd3a36a13",
        "version_major": 2,
        "version_minor": 0
       },
@@ -599,11 +499,11 @@
     {
      "data": {
       "text/html": [
-       "
[18:57:44] status = queued                                         webapi.py:361\n",
+       "
16:05:20 PST status = queued                                                    \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:57:44]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                         \u001b]8;id=380156;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=908016;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\u001b\\\u001b[2m361\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:05:20 PST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
       ]
      },
      "metadata": {},
@@ -612,7 +512,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "308a3a0354f94c8285656e5839659adc",
+       "model_id": "",
        "version_major": 2,
        "version_minor": 0
       },
@@ -626,11 +526,11 @@
     {
      "data": {
       "text/html": [
-       "
[18:57:54] status = preprocess                                     webapi.py:355\n",
+       "
16:05:25 PST status = preprocess                                                \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:57:54]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                     \u001b]8;id=828718;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=795040;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\u001b\\\u001b[2m355\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:05:25 PST\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
       ]
      },
      "metadata": {},
@@ -649,15 +549,13 @@
     {
      "data": {
       "text/html": [
-       "
[18:57:58] Maximum FlexCredit cost: 0.210. Use                     webapi.py:341\n",
-       "           'web.real_cost(task_id)' to get the billed FlexCredit                \n",
-       "           cost after a simulation run.                                         \n",
+       "
16:05:27 PST Maximum FlexCredit cost: 0.469. Use 'web.real_cost(task_id)' to get\n",
+       "             the billed FlexCredit cost after a simulation run.                 \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:57:58]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.210\u001b[0m. Use                     \u001b]8;id=231439;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=986621;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\u001b\\\u001b[2m341\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m           \u001b[0m\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[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0mcost after a simulation run.                            \u001b[2m             \u001b[0m\n"
+       "\u001b[2;36m16:05:27 PST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.469\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\n",
+       "\u001b[2;36m             \u001b[0mthe billed FlexCredit cost after a simulation run.                 \n"
       ]
      },
      "metadata": {},
@@ -666,11 +564,11 @@
     {
      "data": {
       "text/html": [
-       "
           starting up solver                                      webapi.py:377\n",
+       "
             starting up solver                                                 \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                      \u001b]8;id=48928;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=295123;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\u001b\\\u001b[2m377\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
       ]
      },
      "metadata": {},
@@ -679,11 +577,11 @@
     {
      "data": {
       "text/html": [
-       "
           running solver                                          webapi.py:386\n",
+       "
16:05:28 PST running solver                                                     \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                          \u001b]8;id=231772;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=365338;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\u001b\\\u001b[2m386\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:05:28 PST\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
       ]
      },
      "metadata": {},
@@ -692,17 +590,17 @@
     {
      "data": {
       "text/html": [
-       "
           To cancel the simulation, use 'web.abort(task_id)' or   webapi.py:387\n",
-       "           'web.delete(task_id)' or abort/delete the task in the                \n",
-       "           web UI. Terminating the Python script will not stop the              \n",
-       "           job running on the cloud.                                            \n",
+       "
             To cancel the simulation, use 'web.abort(task_id)' or              \n",
+       "             'web.delete(task_id)' or abort/delete the task in the web UI.      \n",
+       "             Terminating the Python script will not stop the job running on the \n",
+       "             cloud.                                                             \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or   \u001b]8;id=343225;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=319807;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m           \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the   \u001b[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0mweb UI. Terminating the Python script will not stop the \u001b[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0mjob running on the cloud.                               \u001b[2m             \u001b[0m\n"
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
+       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
+       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
+       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
       ]
      },
      "metadata": {},
@@ -711,7 +609,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dc869fed1c944be49bd6046bb5736fe6",
+       "model_id": "b12c3ece59474f79b3ef6053a49f1a6a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -725,11 +623,11 @@
     {
      "data": {
       "text/html": [
-       "
[18:59:43] early shutoff detected, exiting.                        webapi.py:404\n",
+       "
16:07:11 PST early shutoff detected at 52%, exiting.                            \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:59:43]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                        \u001b]8;id=538392;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=842166;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\u001b\\\u001b[2m404\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:07:11 PST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m52\u001b[0m%, exiting.                            \n"
       ]
      },
      "metadata": {},
@@ -761,11 +659,11 @@
     {
      "data": {
       "text/html": [
-       "
           status = postprocess                                    webapi.py:419\n",
+       "
             status = postprocess                                               \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                    \u001b]8;id=382395;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=120908;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#419\u001b\\\u001b[2m419\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
       ]
      },
      "metadata": {},
@@ -774,7 +672,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1338ce57de6742a8a97cbe68fbaaa954",
+       "model_id": "",
        "version_major": 2,
        "version_minor": 0
       },
@@ -788,11 +686,11 @@
     {
      "data": {
       "text/html": [
-       "
[18:59:50] status = diverged                                       webapi.py:426\n",
+       "
16:07:19 PST status = diverged                                                  \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:59:50]\u001b[0m\u001b[2;36m \u001b[0mstatus = diverged                                       \u001b]8;id=376837;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=268832;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\u001b\\\u001b[2m426\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:07:19 PST\u001b[0m\u001b[2;36m \u001b[0mstatus = diverged                                                  \n"
       ]
      },
      "metadata": {},
@@ -808,10 +706,27 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "data": {
+      "text/html": [
+       "
             View simulation result at                                          \n",
+       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7\n",
+       "             d-4874-98c4-87b4d3705495'.                                         \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=141908;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=201488;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=141908;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=63288;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=141908;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34m-f6a84898-dd7\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=141908;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f6a84898-dd7d-4874-98c4-87b4d3705495\u001b\\\u001b[4;34md-4874-98c4-87b4d3705495'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4542e0d9aec04043b06398d6134f7a32",
+       "model_id": "3c10d4f593034e1e8a6e86cdb660a45c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -848,11 +763,11 @@
     {
      "data": {
       "text/html": [
-       "
[18:59:52] loading SimulationData from data/simulation_data.hdf5   webapi.py:590\n",
+       "
16:07:20 PST loading simulation from data/simulation_data.hdf5                  \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m[18:59:52]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/simulation_data.hdf5   \u001b]8;id=265612;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=479940;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\u001b\\\u001b[2m590\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m16:07:20 PST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/simulation_data.hdf5                  \n"
       ]
      },
      "metadata": {},
@@ -861,17 +776,13 @@
     {
      "data": {
       "text/html": [
-       "
           WARNING: Simulation final field decay value of 1.0 is   webapi.py:597\n",
-       "           greater than the simulation shutoff threshold of 1e-05.              \n",
-       "           Consider simulation again with large run_time duration               \n",
-       "           for more accurate results.                                           \n",
+       "
             WARNING: The simulation has diverged! For more information, check  \n",
+       "             'SimulationData.log' or use 'web.download_log(task_id)'.           \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Simulation final field decay value of \u001b[0m\u001b[1;36m1.0\u001b[0m\u001b[31m is  \u001b[0m \u001b]8;id=685963;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=261739;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#597\u001b\\\u001b[2m597\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m           \u001b[0m\u001b[31mgreater than the simulation shutoff threshold of \u001b[0m\u001b[1;36m1e-05\u001b[0m\u001b[31m.\u001b[0m \u001b[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0m\u001b[31mConsider simulation again with large run_time duration \u001b[0m \u001b[2m             \u001b[0m\n",
-       "\u001b[2;36m           \u001b[0m\u001b[31mfor more accurate results.                             \u001b[0m \u001b[2m             \u001b[0m\n"
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: The simulation has diverged! For more information, check  \u001b[0m\n",
+       "\u001b[2;36m             \u001b[0m\u001b[32m'SimulationData.log'\u001b[0m\u001b[31m or use \u001b[0m\u001b[32m'web.download_log\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m.           \u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -889,33 +800,97 @@
    "id": "888f5be1",
    "metadata": {},
    "source": [
-    "Now we see that the status of the job is shown to be **diverged**. As discussed in the introduction, it should not come as a surprise since the ring section in the PML layer is not perpendicular to the boundary and translational invariant as shown in the zoomed-in plot below."
+    "Now we see that the status of the job is shown to be **diverged**. As discussed in the introduction, it should not come as a surprise since the ring section in the PML layer is not perpendicular to the boundary and translational invariant as shown in the zoomed-in plot below. We see that we are also given a warning about the divergence and prompted to check the log for more information."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "bd12c0bf",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2023-08-19T01:59:54.663175Z",
-     "iopub.status.busy": "2023-08-19T01:59:54.663022Z",
-     "iopub.status.idle": "2023-08-19T01:59:54.867208Z",
-     "shell.execute_reply": "2023-08-19T01:59:54.866703Z"
-    }
-   },
+   "execution_count": 12,
+   "id": "9af23884-fff1-4900-bc79-78b7f46e9518",
+   "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/home/momchil/miniconda3/envs/tidy3d-docs/lib/python3.9/site-packages/shapely/set_operations.py:133: RuntimeWarning: invalid value encountered in intersection\n",
-      "  return lib.intersection(a, b, **kwargs)\n"
+      "[00:05:25] USER: Simulation domain Nx, Ny, Nz: [759, 280, 82]                   \n",
+      "           USER: Applied symmetries: (0, 0, 1)                                  \n",
+      "           USER: Number of computational grid points: 9.2279e+06.               \n",
+      "           USER: Using subpixel averaging: True                                 \n",
+      "           USER: Number of time steps: 6.2950e+04                               \n",
+      "           USER: Automatic shutoff factor: 1.00e-05                             \n",
+      "           USER: Time step (s): 3.1772e-17                                      \n",
+      "           USER:                                                                \n",
+      "                                                                                \n",
+      "           USER: Compute source modes time (s):     0.5671                      \n",
+      "[00:05:26] USER: Rest of setup time (s):            0.2845                      \n",
+      "[00:06:15] USER: Compute monitor modes time (s):    46.0400                     \n",
+      "[00:07:07] USER: Solver time (s):                   98.8520                     \n",
+      "           USER: Time-stepping speed (cells/s):     5.98e+09                    \n",
+      "           WARNING: The simulation has diverged!                                \n",
+      "           WARNING: Some structures were found to be spatially varying inside   \n",
+      "           the PML. Ensure that structures are translationally invariant in the \n",
+      "           PML regions in the direction normal to the PML interface.            \n",
+      "           Alternatively, switching the PML to Absorber boundary should fix the \n",
+      "           divergence.                                                          \n",
+      "           WARNING: A dispersive medium inside the PML regions was detected,    \n",
+      "           which may be causing the divergence. Consider making the medium      \n",
+      "           non-dispersive, or fitting a different dispersive model for that     \n",
+      "           medium. Alternatively, switching the PML to Absorber boundary should \n",
+      "           fix the divergence.                                                  \n",
+      "           USER: Post-processing time (s):          0.5129                      \n",
+      "\n",
+      " ====== SOLVER LOG ====== \n",
+      "\n",
+      "Processing grid and structures...\n",
+      "Building FDTD update coefficients...\n",
+      "Potential divergence: dispersive medium into PML.\n",
+      "Potential divergence: structures are not translationally invariant inside PML.\n",
+      "Solver setup time (s):             1.5782\n",
+      "\n",
+      "Running solver for 62950 time steps...\n",
+      "- Time step   2517 / time 8.00e-14s (  4 % done), field decay: 1.00e+00\n",
+      "- Time step   4010 / time 1.27e-13s (  6 % done), field decay: 1.00e+00\n",
+      "- Time step   5035 / time 1.60e-13s (  8 % done), field decay: 1.00e+00\n",
+      "- Time step   7553 / time 2.40e-13s ( 12 % done), field decay: 1.00e+00\n",
+      "- Time step  10071 / time 3.20e-13s ( 16 % done), field decay: 6.82e-02\n",
+      "- Time step  12589 / time 4.00e-13s ( 20 % done), field decay: 2.32e-04\n",
+      "- Time step  15107 / time 4.80e-13s ( 24 % done), field decay: 1.00e+00\n",
+      "- Time step  17625 / time 5.60e-13s ( 28 % done), field decay: 1.00e+00\n",
+      "- Time step  20143 / time 6.40e-13s ( 32 % done), field decay: 1.00e+00\n",
+      "- Time step  22661 / time 7.20e-13s ( 36 % done), field decay: 1.00e+00\n",
+      "- Time step  25179 / time 8.00e-13s ( 40 % done), field decay: 1.00e+00\n",
+      "- Time step  27697 / time 8.80e-13s ( 44 % done), field decay: 1.00e+00\n",
+      "- Time step  30215 / time 9.60e-13s ( 48 % done), field decay: 1.00e+00\n",
+      "- Time step  32733 / time 1.04e-12s ( 52 % done), field decay: 1.00e+00\n",
+      "Field diverged at time step  33860 ( 53 % done), exiting solver.\n",
+      "Time-stepping time (s):            97.0829\n",
+      "Data write time (s):               0.1915\n",
+      "\n"
      ]
-    },
+    }
+   ],
+   "source": [
+    "print(sim_data.log)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4bf3803e-059c-4c5a-93ba-7cd1142e6fa4",
+   "metadata": {},
+   "source": [
+    "The log indeed tells us that there are two potential causes of divergence that were found in this simulation. One is the presence of dispersive materials in the PML, while the other is the fact that the ring is not translationally invariant. While both of those things can cause divergence, our in-built silicon material model has been fit to perform well for straight waveguides going into the PML, at telecommunication wavelengths. Thus, the more likely cause of the divergence is the fact that the ring is not translationally invariant."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "bd12c0bf",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
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       ]
@@ -1480,7 +1455,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.7"
   },
   "title": "Modeling the Waveguide to Ring Coupling | Flexcompute",
   "widgets": {