diff --git a/GL/scripts/Kaustik.ipynb b/GL/scripts/Kaustik.ipynb
new file mode 100644
index 0000000..4c6cc30
--- /dev/null
+++ b/GL/scripts/Kaustik.ipynb
@@ -0,0 +1,232 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "\"\"\"Calculation of the Kaustik of a Laserbeam.\"\"\"\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import importlib.util\n",
+    "from SecondaryValue import SecondaryValue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Input Parameters\n",
+    "R = 100  # cm\n",
+    "L = 46  # cm\n",
+    "f = 15  # cm\n",
+    "lam = 633e-8  # cm\n",
+    "lens_pos = 15 # cm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Optical Matrix Elements\n",
+    "A = SecondaryValue('1-x/f', defaults=dict(f=f))\n",
+    "B = SecondaryValue('s+x-x*s/f', defaults=dict(f=f))\n",
+    "C = SecondaryValue('-1/f', defaults=dict(f=f))\n",
+    "D = SecondaryValue('1-s/f', defaults=dict(f=f))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "w0 = SecondaryValue('((l/pi)^2*L*(R-L))^(1/4)', defaults=dict(l=lam, L=L, R=R, pi=np.pi))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# b parameter\n",
+    "b = SecondaryValue('l/(pi*w0^2)', defaults=dict(l=lam, pi=np.pi), dependencies=dict(w0=w0))\n",
+    "new_b = SecondaryValue('b*(A*D-C*B)/(A^2+B^2*b^2)', dependencies=dict(A=A, B=B, C=C, D=D, b=b))\n",
+    "b_before = SecondaryValue('b/(1+x^2*b^2)', dependencies=dict(b=b))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# omega\n",
+    "w = SecondaryValue('sqrt(l/(p*b))', defaults=dict(l=lam, p=np.pi), dependencies=dict(b=new_b))\n",
+    "w_before = SecondaryValue('sqrt(l/(p*b))', defaults=dict(l=lam, p=np.pi), dependencies=dict(b=b_before))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7ff41b7a7b10>]"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": [
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\n"
+      ],
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xs_before = np.linspace(0, lens_pos, 1000)\n",
+    "xs_after = np.linspace(0, 40, 1000)\n",
+    "plt.plot(xs, w_before(x=[xs_before]))\n",
+    "plt.plot(xs + lens_pos, w(s=lens_pos, x=[xs_after]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.010021086630321032"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "w0()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "autoscroll": false,
+    "collapsed": false,
+    "ein.hycell": false,
+    "ein.tags": "worksheet-0",
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "argv": [
+    "python",
+    "-m",
+    "ipykernel_launcher",
+    "-f",
+    "{connection_file}"
+   ],
+   "display_name": "Python 3",
+   "env": null,
+   "interrupt_mode": "signal",
+   "language": "python",
+   "metadata": null,
+   "name": "python3"
+  },
+  "name": "Untitled.ipynb"
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/interessant.org b/interessant.org
new file mode 100644
index 0000000..fe3feb7
--- /dev/null
+++ b/interessant.org
@@ -0,0 +1,23 @@
+* IAP
+** SZ Solarzelle
+** OCT Opt. Koh. Tom
+* IFMP
+** TEM Elektronenm.
+** PSL Phasenueber
+* IKTP
+** RE Reaktor
+** DD Dosimetrie
+** PET Positronen Em. Sp.
+** BE Beta Zerfall
+** MY Myonen
+** TR Transmission th. neutr
+* ZIK B Cube
+** MMC Molekularmotoren
+
+
+* Olga
+** GL
+** MMC
+** RS
+** SZ
+** SO