{ "cells": [ { "cell_type": "markdown", "id": "58e0f16e", "metadata": {}, "source": [ "# Tutorial: Using phenom to Model Shot-to-Shot the European XFEL\n", "Our objective here is to generate pulses whose properties pertain analytical expressions of some other beam properties.\n", "\n", "In doing so, we may reduce the number of variables that needs to be parsed to our source model.\n", "\n", "## An Emipirical Model of SA1 Undulator at the European XFEL\n", "We make use analytical expressions of pulse properties at the SA1 undulator of the European XFEL, which obtains the following parameters as a function of photon energy and electron beam charge:\n", "\n", "1. Pulse energy in Joules\n", "2. Pulse duration in seconds\n", "3. Pulse width in m\n", "4. Pulse Divergence in rad.\n", "\n", "The analytical expressions are provided below:" ] }, { "cell_type": "code", "execution_count": 1, "id": "e9488632", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import scipy.constants\n", "\n", "h = scipy.constants.physical_constants['Planck constant in eV s'][0]\n", "\n", "def analytical_pulse_energy(q, photon_energy):\n", " \"\"\"\n", " Estimate of analytical_pulse_energy from electron bunch charge and radiation energy\n", "\n", " :param q: electron bunch charge [nC]\n", " :param photon_energy: radiation energy [eV]\n", "\n", " :return P: pulse energy [J]\n", " \"\"\"\n", "\n", " P = 19*q/photon_energy\n", " return P\n", "\n", "def analytical_pulse_duration(q):\n", " \"\"\"\n", " Estimate analytical_pulse_duration from electron bunch charge\n", "\n", " :param q: electron bunch charge [nC]\n", "\n", " :return t: Duration of pulse [s]\n", " \"\"\"\n", "\n", " t = (q*1e3)/9.8\n", " return t*1e-15\n", "\n", "\n", "def analytical_pulse_width(photon_energy):\n", " \"\"\"\n", " Estimate analytical_pulse_width (FWHM) from radiation energy (assumes symmetrical beam)\n", "\n", " :param photon_energy: radiation energy [eV]\n", "\n", " :return sig: Radiation pulse width [m]\n", " \"\"\"\n", "\n", " sig = np.log((7.4e03/(photon_energy/1e03)))*6\n", " return sig/1e6\n", "\n", "\n", "def analytical_pulse_divergence(photon_energy):\n", " \n", " \"\"\"\n", " Estimate of analytical_pulse_divergence (half-angle) from electron bunch charge and radiation energy\n", "\n", " :param q: electron bunch charge [nC]\n", " :param photon_energy: radiation energy [eV]\n", "\n", " :return dtheta: pulse divergence [rad]\n", " \"\"\"\n", " return ((14.1)/((photon_energy/1e03)**0.75)) / 1e06\n", " " ] }, { "cell_type": "code", "execution_count": 2, "id": "522f7420", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "<>:17: SyntaxWarning: invalid escape sequence '\\m'\n", "<>:22: SyntaxWarning: invalid escape sequence '\\m'\n", "<>:17: SyntaxWarning: invalid escape sequence '\\m'\n", "<>:22: SyntaxWarning: invalid escape sequence '\\m'\n", "/var/folders/r5/xp94p76n08l4hvjctdh74hl00000gn/T/ipykernel_23188/3668744920.py:17: SyntaxWarning: invalid escape sequence '\\m'\n", " ax2.set_ylabel(\"Pulse Width ($\\mu$m)\")\n", "/var/folders/r5/xp94p76n08l4hvjctdh74hl00000gn/T/ipykernel_23188/3668744920.py:22: SyntaxWarning: invalid escape sequence '\\m'\n", " ax3.set_ylabel(\"Pulse Divergence ($\\mu$rad)\")\n" ] }, { "data": { "text/plain": [ "Text(0, 0.5, 'Pulse Divergence ($\\\\mu$rad)')" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from matplotlib import pyplot as plt\n", "\n", "energies = np.arange(1,15,0.1)*1e3 ### photon energies\n", "q = 0.250 ### 250 pC bunch charge\n", "\n", "fig, [ax1,ax2,ax3] = plt.subplots(3,1, figsize = (4,6), sharex = True)\n", "\n", "duration = analytical_pulse_duration(q = 0.250)\n", "fig.suptitle(r\"Pulse Duration: {:.2f} fs\".format(duration * 1e15))\n", "\n", "pulse_energy = analytical_pulse_energy(q = q, photon_energy = energies)\n", "ax1.plot(energies, pulse_energy * 1e3)\n", "ax1.set_ylabel(r\"Pulse Energy (mJ)\")\n", "\n", "pulse_width = analytical_pulse_width(photon_energy = energies)\n", "ax2.plot(energies, pulse_width * 1e6)\n", "ax2.set_ylabel(r\"Pulse Width ($\\mu$m)\")\n", "\n", "pulse_div = analytical_pulse_divergence(photon_energy = energies)\n", "ax3.plot(energies, analytical_pulse_divergence(photon_energy = energies) * 1e6)\n", "ax3.set_xlabel(\"Energy (eV)\")\n", "ax3.set_ylabel(r\"Pulse Divergence ($\\mu$rad)\")" ] }, { "cell_type": "markdown", "id": "2d90b37c", "metadata": {}, "source": [ "### A Custom SASE Source" ] }, { "cell_type": "markdown", "id": "93faf7f8", "metadata": {}, "source": [ "We can use this model to generate pulses under a standard operating condition of the [SPB/SFX](http://scripts.iucr.org/cgi-bin/paper?S1600577519003308) instrument:" ] }, { "cell_type": "code", "execution_count": 3, "id": "fa49978e", "metadata": {}, "outputs": [], "source": [ "from phenom.source import SASE_Source\n", "\n", "## define the operating conditions\n", "photon_energy = 10e03\n", "beam_charge = 0.250 # nC\n", "\n", "## wrap sase\n", "def SA1_Source(photon_energy,\n", " beam_charge,\n", " nr = 512, \n", " nt = 512,\n", " bandwidth = 1e-12,\n", " x0 = 0.0,\n", " y0 = 0.0,\n", " t0 = 0.0,\n", " theta_x = 0.0,\n", " theta_y = 0.0):\n", " \n", " duration = analytical_pulse_duration(q = beam_charge)\n", " pulse_energy = analytical_pulse_energy(q = beam_charge, photon_energy = photon_energy)\n", " pulse_width = analytical_pulse_width(photon_energy = photon_energy)\n", " pulse_div = analytical_pulse_divergence(photon_energy = photon_energy)\n", " \n", " x = y = np.linspace(-pulse_width*4, pulse_width*4, nr)\n", " t = np.linspace(-duration*1.5, duration*1.5, nt)\n", " \n", " if type(pulse_width) == np.float64:\n", " pulse_width = float(pulse_width)\n", " \n", " ## define the pulse\n", " src = SASE_Source(x = x,\n", " y = y,\n", " t = t,\n", " photon_energy = photon_energy,\n", " pulse_energy = pulse_energy,\n", " pulse_duration = duration,\n", " bandwidth = bandwidth,\n", " sigma = pulse_width,\n", " div = pulse_div,\n", " x0 = x0,\n", " y0 = y0,\n", " t0 = t0,\n", " theta_x = theta_x,\n", " theta_y = theta_y\n", " )\n", " \n", " return src" ] }, { "cell_type": "markdown", "id": "3e6c60a8", "metadata": {}, "source": [ "It is then convenient to execute our wrapped function:" ] }, { "cell_type": "code", "execution_count": 4, "id": "898229bd", "metadata": {}, "outputs": [], "source": [ "save_loc = \"./sase_field.h5\"\n", "\n", "src = SA1_Source(photon_energy = 10e3, beam_charge = 0.250, nt = 252)\n", "src.generate_pulses(save_loc)" ] }, { "cell_type": "code", "execution_count": 6, "id": "dd527a16", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Time (fs)')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import h5py as h5\n", "\n", "with h5.File(save_loc, mode = 'r') as hf:\n", " \n", " x = sase_pulse = hf['pulse000']['mesh']['x'][()]\n", " y = sase_pulse = hf['pulse000']['mesh']['y'][()]\n", " t = sase_pulse = hf['pulse000']['mesh']['t'][()]\n", " \n", " sase_pulse = hf['pulse000']['data'][()]\n", " \n", "from matplotlib import pyplot as plt\n", " \n", "fig, [ax1, ax2] = plt.subplots(1,2, figsize = (9,3))\n", "\n", "### spatial intensity\n", "im = ax1.imshow((abs(sase_pulse)**2).sum(axis = 2),\n", " extent = [x.min() * 1e06,\n", " x.max() * 1e06,\n", " y.min() * 1e06,\n", " y.max() * 1e06],\n", " cmap = 'bone'\n", " )\n", "\n", "plt.colorbar(im, label = \"Intensity (W/mm$^2$)\")\n", "\n", "ax1.set_xlabel(r'x ($\\mu$m)')\n", "ax1.set_ylabel(r'y ($\\mu$m)')\n", "\n", "\n", "ax2.plot(t*1e15, (abs(sase_pulse)**2).sum(axis = (0,1)))\n", "ax2.set_xlabel(\"Time (fs)\")" ] }, { "cell_type": "markdown", "id": "685b634c", "metadata": {}, "source": [ "We can similarly pass a list of photon_energies:" ] }, { "cell_type": "code", "execution_count": null, "id": "40fe9a2a", "metadata": {}, "outputs": [], "source": [ "save_loc = \"./sase_field.h5\"\n", "\n", "energies = np.arange(10,15)*1e3\n", "\n", "src = SA1_Source(photon_energy = energies, beam_charge = 0.250, nt = 250)\n", "src.generate_pulses(save_loc)" ] }, { "cell_type": "code", "execution_count": null, "id": "8db9fa88", "metadata": {}, "outputs": [], "source": [ "fig, ax = plt.subplots(1,5, figsize = (10,2))\n", "ax = ax.flatten()\n", "\n", "with h5.File(save_loc, mode = 'r') as hf:\n", " \n", " for itr, key in enumerate(hf.keys()):\n", " \n", " ax[itr].set_xticks([])\n", " ax[itr].set_yticks([])\n", " \n", " sase_pulse = hf[key]['data'][()]\n", " ax[itr].imshow((abs(sase_pulse)**2).sum(axis = 2),\n", " cmap = 'bone'\n", " )\n", " photon_energy = hf[key]['params']['photon_energy'][()]\n", " ax[itr].set_title(\"Photon Energy:\\n{:.2e} eV\".format(photon_energy*1e3))" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (Spyder)", "language": "python3", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }