diff --git a/spyglass.ipynb b/spyglass.ipynb
index d272292..38828d5 100644
--- a/spyglass.ipynb
+++ b/spyglass.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": 56,
"id": "6026a74b",
"metadata": {},
"outputs": [],
@@ -16,7 +16,7 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": 57,
"id": "c7d740ee",
"metadata": {},
"outputs": [],
@@ -63,7 +63,7 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": 58,
"id": "a26f0ff4",
"metadata": {
"scrolled": false
@@ -72,7 +72,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "d19fee53d0f74ee5a891e7a1016bb669",
+ "model_id": "e617f99036964ea9ac79bf2b2e178d9c",
"version_major": 2,
"version_minor": 0
},
@@ -103,7 +103,7 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": 59,
"id": "85fd9885",
"metadata": {},
"outputs": [
@@ -141,14 +141,14 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": 60,
"id": "8f39b24f",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "dfcc24e9079f48f2b75810cacec1bb81",
+ "model_id": "27eac6b1a50a4387a7bc3a63a5177cc2",
"version_major": 2,
"version_minor": 0
},
@@ -186,14 +186,14 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": 61,
"id": "fbb733ef",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "411188d34c444ee78cc316237b79915a",
+ "model_id": "23c9def119674bf8a861a23902fed152",
"version_major": 2,
"version_minor": 0
},
@@ -225,14 +225,14 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": 62,
"id": "95deb34e",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "f172bd8c715148d495c13c1590d59a90",
+ "model_id": "bf1ce7e4ae3c487fa4f9fe60cf7085f4",
"version_major": 2,
"version_minor": 0
},
diff --git a/spyglass_v2.ipynb b/spyglass_v2.ipynb
index 235c8e0..65dbc19 100644
--- a/spyglass_v2.ipynb
+++ b/spyglass_v2.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 156,
+ "execution_count": 1,
"id": "6026a74b",
"metadata": {},
"outputs": [],
@@ -16,10 +16,20 @@
},
{
"cell_type": "code",
- "execution_count": 157,
+ "execution_count": 164,
"id": "c7d740ee",
- "metadata": {},
- "outputs": [],
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "203.43209152244057 17.29156926912888 -30.45841339555312\n"
+ ]
+ }
+ ],
"source": [
"opm = OpticalModel()\n",
"sm = opm['seq_model']\n",
@@ -37,53 +47,78 @@
"def calc_curvature(n, fl):\n",
" return (n-1)*fl\n",
"\n",
+ "n_bk7 = 1.5168\n",
"n_lasf9 = 1.85025\n",
+ "n_f2 = 1.62005\n",
+ "\n",
+ "v_bk7 = 64.17\n",
+ "v_lasf9 = 32.16\n",
+ "v_f2 = 36.43\n",
"# try for chaining a 3x telescope setup with a second 3x telescope setup\n",
- "f0 = 300\n",
- "f1 = 100\n",
+ "f0 = 150\n",
+ "f0_0 = (v_bk7-v_f2)*f0/v_bk7\n",
+ "f0_1 = -f0_0*v_bk7/v_f2/1.2\n",
+ "f0_actual = 1/(1/f0_0+1/f0_1)\n",
+ "f1 = 40\n",
+ "# 1/f = 1/f0 + 1/f1 = 1/f0 - v2/(f0*v1) = (v1-v2)/(v1*f0)\n",
+ "# f0 = (v1-v2)*f/v1\n",
+ "f1_0 = (v_bk7-v_f2)*f1/v_bk7\n",
+ "f1_1 = -f1_0*v_bk7/v_f2\n",
+ "print(f0_actual, f1_0, f1_1)\n",
"f2 = 150\n",
"f3 = 50\n",
"\n",
"f1_stacked = 2*f1\n",
"\n",
"r0 = calc_curvature(n_lasf9, f0)\n",
+ "r0_0 = calc_curvature(n_bk7, f0_0)\n",
+ "r0_1 = calc_curvature(n_f2, f0_1)\n",
"r1 = calc_curvature(n_lasf9, f1)\n",
+ "r1_0 = calc_curvature(n_bk7, f1_0)\n",
+ "r1_1 = calc_curvature(n_f2, f1_1)\n",
"r2 = calc_curvature(n_lasf9, f2)\n",
"r3 = calc_curvature(n_lasf9, f3)\n",
"\n",
- "sm.add_surface([r0, 2, 'N-LASF9', 'Schott', 42/2])\n",
- "sm.add_surface([1e9, f0+f1])\n",
+ "sm.add_surface([r0_0, 2, 'N-BK7', 'Schott', 42/2])\n",
+ "sm.add_surface([1e9, 2, 'N-F2', 'Schott', 42/2])\n",
+ "#sm.add_surface([-r0_1, 180+2*f1])\n",
+ "sm.add_surface([-r0_1, 180+2*36.])\n",
+ "\n",
+ "#sm.add_surface([r1_0, 6, 'N-BK7', 'Schott', 16])\n",
+ "#sm.add_surface([1e9, 2, 'N-F2', 'Schott', 16])\n",
+ "#sm.add_surface([-r1_1, 30])\n",
"sm.add_surface([1e9, 2, 'N-LASF9', 'Schott', 16])\n",
- "sm.add_surface([-r1, 0.])\n",
- "sm.add_surface([r2, 2, 'N-LASF9', 'Schott', 16])\n",
- "sm.add_surface([1e9, f2+f3])\n",
- "sm.add_surface([1e9, 2, 'N-LASF9', 'Schott', 16])\n",
- "sm.add_surface([-r3, f3])\n"
+ "sm.add_surface([-r1, f2+f3])\n",
+ "\n",
+ "#sm.add_surface([r2, 2, 'N-LASF9', 'Schott', 16])\n",
+ "#sm.add_surface([1e9, f2+f3])\n",
+ "#sm.add_surface([1e9, 2, 'N-LASF9', 'Schott', 16])\n",
+ "#sm.add_surface([-r3, f3])\n"
]
},
{
"cell_type": "code",
- "execution_count": 158,
+ "execution_count": 165,
"id": "a26f0ff4",
"metadata": {
- "scrolled": false
+ "scrolled": true
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "26bad7089f9349d18e7c2d2c09b077d9",
+ "model_id": "aab1fc89c06c440c985317b08f6a9fd7",
"version_major": 2,
"version_minor": 0
},
- "image/png": "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",
+ "image/png": "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",
"text/html": [
"\n",
" \n",
"
\n",
" Figure\n",
"
\n",
- "
\n",
+ "
\n",
"
\n",
"
\n",
" Figure\n",
"
\n",
- "
\n",
+ "
\n",
"
\n",
"
\n",
" Figure\n",
"
\n",
- "
\n",
+ "
\n",
"
\n",
"
\n",
" Figure\n",
"
\n",
- "
\n",
+ "
\n",
"
\n",
+ "
\n",
+ " Figure\n",
+ "
\n",
+ "
\n",
+ "