{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Configuration\n",
    "\n",
    "Here we illustrate how to create experimental configurations, using the ``atomsmltr.simulation.configurator`` subpackage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to configurations\n",
    "\n",
    "Configuration objects are at the heart of this package. They are the cement that allows to combine all the environment objects (lasers, magnetic fields, zones) and feed them into a simulation.\n",
    "\n",
    "Here is how to create a configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from atomsmltr.simulation import Configuration\n",
    "from atomsmltr.atoms import Ytterbium\n",
    "\n",
    "# init a configuration for ytterbium atoms\n",
    "config = Configuration(atom=Ytterbium())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "objects can be added to the configuration using the ``add_objects()`` method or the ``+=`` operator. The Configuration object will automatically sort them according to their type. \n",
    "\n",
    "**ATTENTION** objects are stored in internal dictionnaries, using their ``tag`` property as a key. Therefore, it is important to **define tags for the objects** and to make sure that objects do not have the same tags (otherwise, an error will be raised)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from atomsmltr.environment import Limits, MagneticOffset, MagneticGradient, GaussianLaserBeam\n",
    "\n",
    "# let's define two lasers\n",
    "laser1 = GaussianLaserBeam(tag=\"laser1\")\n",
    "laser2 = GaussianLaserBeam(tag=\"laser2\")\n",
    "\n",
    "# two magnetic fields\n",
    "mag_offset = MagneticOffset((0,1,0), tag=\"offset\")\n",
    "mag_gradient = MagneticGradient((0,0,0), 0.5, (0,1,0), (0,0,1), tag=\"gradient\")\n",
    "# one limit\n",
    "xlim = Limits(0, 10, axis=0, target=\"position\")\n",
    "\n",
    "# and add them\n",
    "config.add_objects([laser1, mag_offset])   # we can provide a list\n",
    "config.add_objects(xlim)  # a single object\n",
    "config += mag_gradient, laser2  # or use the operator :)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now we can print the information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# ------------ CONFIG INFO > START ------------ #\n",
      "────────────────────────\n",
      "| General informations |\n",
      "────────────────────────\n",
      ". atom :\n",
      "  └── name : Ytterbium\n",
      "\n",
      ". lasers :\n",
      "  ├── laser1\n",
      "  └── laser2\n",
      "\n",
      ". magnetic fields :\n",
      "  ├── offset\n",
      "  └── gradient\n",
      "\n",
      ". forces :\n",
      "  └── empty\n",
      "\n",
      ". zones :\n",
      "  └── vazewa\n",
      "\n",
      "\n",
      "────────────────────\n",
      "| atom | ytterbium |\n",
      "────────────────────\n",
      ". Parameters :\n",
      "  ├── mass (kg) : 2.89e-25\n",
      "  └── mass (au) : 173.94\n",
      "\n",
      ". Transition list :\n",
      "  ├── main\n",
      "  └── intercombination\n",
      "\n",
      ". 'main' transition :\n",
      "  ├── λ : 398.91 nm\n",
      "  ├── Γ : 2π × 2.89e+07 Hz\n",
      "  ├── Isat : 59.51 mw/cm²\n",
      "  └── lande factor g : 1.035\n",
      "\n",
      ". 'intercombination' transition :\n",
      "  ├── λ : 555.80 nm\n",
      "  ├── Γ : 2π × 1.82e+05 Hz\n",
      "  ├── Isat : 0.14 mw/cm²\n",
      "  └── lande factor g : 1.493\n",
      "\n",
      "\n",
      "────────────────────────\n",
      "| laser | tag='laser1' |\n",
      "────────────────────────\n",
      ". Parameters :\n",
      "  ├── type : Gaussian beam\n",
      "  ├── tag : laser1\n",
      "  ├── waist (m) : 0.001\n",
      "  ├── power (W) : 0.001\n",
      "  ├── waist position (m) : [0 0 0]\n",
      "  ├── direction type : vector\n",
      "  ├── direction : [0 0 1]\n",
      "  ├── unit vector : [0. 0. 1.]\n",
      "  ├── unit vector phi : π × 0.0\n",
      "  ├── unit vector theta : π × 0.0\n",
      "  └── Rayleigh length : 7.9 m\n",
      "\n",
      ". Polarization settings :\n",
      "  └── type : Vertical\n",
      "\n",
      ". Polarization vector :\n",
      "  ├── coords : (1.00, 0.00, 0.00)\n",
      "  ├── polar angle u : 0.50 pi\n",
      "  └── azimt angle v : 0.00 pi\n",
      "\n",
      ". Projections (amplitudes) :\n",
      "  ├── vertical : 1.00+0.00j\n",
      "  ├── horizontal : 0.00+0.00j\n",
      "  ├── circular left : 0.71+0.00j\n",
      "  └── circular right : 0.71+0.00j\n",
      "\n",
      ". Projections (squared norm) :\n",
      "  ├── vertical : 1.00\n",
      "  ├── horizontal : 0.00\n",
      "  ├── circular left : 0.50\n",
      "  └── circular right : 0.50\n",
      "\n",
      "\n",
      "────────────────────────\n",
      "| laser | tag='laser2' |\n",
      "────────────────────────\n",
      ". Parameters :\n",
      "  ├── type : Gaussian beam\n",
      "  ├── tag : laser2\n",
      "  ├── waist (m) : 0.001\n",
      "  ├── power (W) : 0.001\n",
      "  ├── waist position (m) : [0 0 0]\n",
      "  ├── direction type : vector\n",
      "  ├── direction : [0 0 1]\n",
      "  ├── unit vector : [0. 0. 1.]\n",
      "  ├── unit vector phi : π × 0.0\n",
      "  ├── unit vector theta : π × 0.0\n",
      "  └── Rayleigh length : 7.9 m\n",
      "\n",
      ". Polarization settings :\n",
      "  └── type : Vertical\n",
      "\n",
      ". Polarization vector :\n",
      "  ├── coords : (1.00, 0.00, 0.00)\n",
      "  ├── polar angle u : 0.50 pi\n",
      "  └── azimt angle v : 0.00 pi\n",
      "\n",
      ". Projections (amplitudes) :\n",
      "  ├── vertical : 1.00+0.00j\n",
      "  ├── horizontal : 0.00+0.00j\n",
      "  ├── circular left : 0.71+0.00j\n",
      "  └── circular right : 0.71+0.00j\n",
      "\n",
      ". Projections (squared norm) :\n",
      "  ├── vertical : 1.00\n",
      "  ├── horizontal : 0.00\n",
      "  ├── circular left : 0.50\n",
      "  └── circular right : 0.50\n",
      "\n",
      "\n",
      "─────────────────────────────────\n",
      "| magnetic field | tag='offset' |\n",
      "─────────────────────────────────\n",
      ". Parameters :\n",
      "  ├── type : constant field\n",
      "  ├── tag : offset\n",
      "  ├── field_value (T) : [0 1 0]\n",
      "  └── norm (T) : 1\n",
      "\n",
      "\n",
      "───────────────────────────────────\n",
      "| magnetic field | tag='gradient' |\n",
      "───────────────────────────────────\n",
      ". Parameters :\n",
      "  ├── type : perfect gradient\n",
      "  ├── tag : gradient\n",
      "  ├── slope (T/m) : 0.5\n",
      "  ├── gradient direction : [0. 1. 0.]\n",
      "  ├── field direction : [0. 0. 1.]\n",
      "  ├── origin (m) : [0 0 0]\n",
      "  └── offset (T) :   0\n",
      "\n",
      "\n",
      "───────────────────────\n",
      "| zone | tag='vazewa' |\n",
      "───────────────────────\n",
      ". Parameters :\n",
      "  ├── type : 1D limits\n",
      "  ├── tag : vazewa\n",
      "  ├── in_tag\n",
      "  ├── out_tag : vazewa\n",
      "  ├── target : position\n",
      "  ├── action : stop\n",
      "  ├── min : 0.0\n",
      "  ├── max : 10.0\n",
      "  ├── axis : 0\n",
      "  └── inverted : False\n",
      "\n",
      "\n",
      "────────────────────────\n",
      "| Atom-light couplings |\n",
      "────────────────────────\n",
      ". transition > 'main' :\n",
      "  └── empty\n",
      "\n",
      ". transition > 'intercombination' :\n",
      "  └── empty\n",
      "\n",
      "\n",
      "# ------------ CONFIG INFO > STOP  ------------ #\n"
     ]
    }
   ],
   "source": [
    "config.print_info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manage objects in a collection\n",
    "\n",
    "Currently, our convention is that **copies** of objects are stored in the configuration object. This way, if an object is modified after it has been added in the configuration, this modification won't affect the configuration.\n",
    "\n",
    "It might be that we change this behaviour at some point... this is to be discussed.\n",
    "\n",
    "The configuration object comes with a lot of useful methods to manage the objects. Here are some examples ; for more information, please have a look at the **API documentation**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from atomsmltr.simulation import Configuration\n",
    "from atomsmltr.atoms import Ytterbium\n",
    "from atomsmltr.environment import Limits, MagneticOffset, MagneticGradient, GaussianLaserBeam\n",
    "\n",
    "# - INIT\n",
    "# let's define some objects\n",
    "laser1 = GaussianLaserBeam(tag=\"laser1\")\n",
    "laser2 = GaussianLaserBeam(tag=\"laser2\")\n",
    "mag_offset = MagneticOffset((0,1,0), tag=\"offset\")\n",
    "\n",
    "# init a configuration for ytterbium atoms\n",
    "config = Configuration(atom=Ytterbium())\n",
    "\n",
    "# add objects\n",
    "config += laser1, laser2, mag_offset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['laser1', 'laser2']\n",
      "['laser2']\n"
     ]
    }
   ],
   "source": [
    "# - REMOVE AN OBJECT\n",
    "print(config.list_lasers())\n",
    "config.rm_laser(\"laser1\")\n",
    "print(config.list_lasers())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[]\n",
      "['offset']\n",
      "[]\n"
     ]
    }
   ],
   "source": [
    "# - REMOVE ALL OBJECTS\n",
    "# all lasers\n",
    "config.rm_all_lasers()\n",
    "print(config.list_lasers())\n",
    "print(config.list_magnetic_fields())\n",
    "\n",
    "# everything\n",
    "config.rm_all_objects()\n",
    "print(config.list_magnetic_fields())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.99e-07\n",
      "3.99e-07\n",
      "5.56e-07\n"
     ]
    }
   ],
   "source": [
    "# - UPDATE AN OBJECT\n",
    "# reset\n",
    "config.rm_all_objects()\n",
    "\n",
    "# add a laser > a copy is stored\n",
    "laser1.wavelength = 399e-9\n",
    "config += laser1\n",
    "\n",
    "# check wavelength of laser stored\n",
    "print(config.get_laser_copy(\"laser1\").wavelength)\n",
    "\n",
    "# update the laser > the stored version is not affected\n",
    "laser1.wavelength = 556e-9\n",
    "print(config.get_laser_copy(\"laser1\").wavelength)\n",
    "\n",
    "# to change the config, laser has to be updated\n",
    "config.update_objects(laser1)\n",
    "print(config.get_laser_copy(\"laser1\").wavelength)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up atom-light couplings\n",
    "\n",
    "### Defining a single-frequency coupling\n",
    "\n",
    "In order to give the user a full control on atom-light interactions, we decided to make the configuration object ignorant of any atom-light interaction coupling. Hence, it is not sufficient to add an atom and a laser with compatible wavelengths for the two to interact.\n",
    "\n",
    "Atom-light coupling are given by hand using the ``add_atomlight_coupling()`` method, associating a laser and a transition using their *tags*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "────────────────────────\n",
      "| Atom-light couplings |\n",
      "────────────────────────\n",
      ". transition > 'main' :\n",
      "  └── laser '399' : detuning=-3.63e+08 (-2.00Γ)\n",
      "\n",
      ". transition > 'intercombination' :\n",
      "  └── empty\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from atomsmltr.simulation import Configuration\n",
    "from atomsmltr.atoms import Ytterbium\n",
    "from atomsmltr.environment import PlaneWaveLaserBeam\n",
    "\n",
    "# init a configuration for ytterbium atoms\n",
    "config = Configuration(atom=Ytterbium())\n",
    "\n",
    "# get ytterbium main transition information\n",
    "main = config.atom.trans[\"main\"]\n",
    "\n",
    "# create a plane wave laser\n",
    "laser = PlaneWaveLaserBeam()\n",
    "laser.wavelength = main.wavelength\n",
    "laser.set_power_from_I(main.Isat)  # set power to have I=Isat\n",
    "laser.tag = \"399\"\n",
    "\n",
    "# add laser to config\n",
    "config += laser\n",
    "\n",
    "# create a coupling\n",
    "config.add_atomlight_coupling(\n",
    "    laser=\"399\",\n",
    "    transition=\"main\",\n",
    "    detuning=-2 * main.Gamma,\n",
    ")\n",
    "\n",
    "# show info\n",
    "config.print_atomlight_info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multi-frequency atom-light coupling\n",
    "\n",
    "In some cases, the spectrum of a laser might present multiple frequencies, such that the atom-light coupling should be defined with multiple detunings. A first option to simulate this situation in ``atomsmltr`` would be to define *one laser beam for each frequency component*, and then to set up the corresponding couplings with different detunings via the ``add_atomlight_coupling()`` method. However, with this method the effect of atom-light interaction will be calculated independently for each laser, and will for instance require to compute the laser intensity and polarization for each component, which is not so efficient.\n",
    "\n",
    "To circumvent that, it is possible to define the detuning as a list of detuning values ``[δ1, δ2, δ3]``, or a list of tuples defining a detuning value and a relative weight ``[(δ1, weight1), (δ2, weight2)]``. Our convention for the weights is the following:\n",
    "\n",
    "+ if no weight is given, we assume a weight of 1\n",
    "+ the atom-light interaction is then computed, for each detuning, with an intensity ``I0 * weight``\n",
    "\n",
    "Where ``I0`` is the total intensity of the laser beam. Note that then weights are given, we do not check the normalization of the intensity. It is up to the user to provide the good values for the laser beam intensity and the weights to account for a physical configuration. Specifically, if the sum of the weights exceeds one, the laser intensity seen by the atoms will be larger than the laser intensity specified when defining the ``LaserBeam`` environment object.\n",
    "\n",
    "For instance, if the configuration contains a laser beam with a total power of 100mW, a list of detuning ``[(δ1, 0.5), (δ2, 0.5)]`` would correspond to two frequency components with each 50mW of power, whereas a list\n",
    "``[δ1, δ2]`` would actually correspond to two laser beams of 100mW with detunings δ1 and δ2.\n",
    "\n",
    "We illustrate this bellow by comparing the force computed using a single laser beam with multiple atom-light coupling defined, and a corresponding collection of individual laser beams."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "────────────────────────\n",
      "| Atom-light couplings |\n",
      "────────────────────────\n",
      ". transition > 'main' :\n",
      "  └── laser '399' : -1.82e+08 (-1.00Γ) * w=0.5, -9.08e+08 (-5.00Γ) * w=0.3, -1.82e+09 (-10.00Γ) * w=0.2\n",
      "\n",
      ". transition > 'intercombination' :\n",
      "  └── empty\n",
      "\n",
      "\n",
      "────────────────────────\n",
      "| Atom-light couplings |\n",
      "────────────────────────\n",
      ". transition > 'main' :\n",
      "  ├── laser '399-1' : -1.82e+08 (-1.00Γ)\n",
      "  ├── laser '399-2' : -9.08e+08 (-5.00Γ)\n",
      "  └── laser '399-3' : -1.82e+09 (-10.00Γ)\n",
      "\n",
      ". transition > 'intercombination' :\n",
      "  └── empty\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from atomsmltr.simulation import Configuration\n",
    "from atomsmltr.atoms import Ytterbium\n",
    "from atomsmltr.environment import PlaneWaveLaserBeam, MagneticGradient, CircularRight\n",
    "\n",
    "# prepare two configs\n",
    "config_multibeams = Configuration(atom=Ytterbium())\n",
    "config_singlebeam = Configuration(atom=Ytterbium())\n",
    "\n",
    "# get ytterbium main transition information\n",
    "main = Ytterbium().trans[\"main\"]\n",
    "\n",
    "# create a plane wave laser\n",
    "laser = PlaneWaveLaserBeam()\n",
    "laser.wavelength = main.wavelength\n",
    "laser.set_power_from_I(main.Isat)  # set power to have I=Isat\n",
    "laser.tag = \"399\"\n",
    "laser.direction = (-1, 0, 0)  # propagates along -x\n",
    "laser.polarization = CircularRight()\n",
    "\n",
    "# add a gradient\n",
    "mag_gradient = MagneticGradient(\n",
    "    origin=(0, 0, 0),\n",
    "    slope=0.1,\n",
    "    gradient_direction=(1, 0, 0),\n",
    "    field_direction=(1, 0, 0),\n",
    ")\n",
    "\n",
    "# add the gradient for the two configs\n",
    "config_singlebeam += mag_gradient\n",
    "config_multibeams += mag_gradient\n",
    "\n",
    "# define couplings : three detunings, with decreasing relative weight\n",
    "detunings = [(-main.Gamma, 0.5), (-5 * main.Gamma, 0.3), (-10 * main.Gamma, 0.2)]\n",
    "\n",
    "# first config with one laser beam, using the multi-frequency atom-light coupling feature\n",
    "config_singlebeam += laser  # single laser\n",
    "config_singlebeam.add_atomlight_coupling(\n",
    "    laser=\"399\", transition=\"main\", detuning=detunings\n",
    ")\n",
    "\n",
    "# second config with three laser beams and single frequency coupling\n",
    "total_power = laser.power\n",
    "for i, (delta, weight) in enumerate(detunings):\n",
    "    # add a dedicated laser with a new tag and corrected intensity\n",
    "    laser.tag = f\"399-{i+1}\"\n",
    "    laser.power = total_power * weight\n",
    "    config_multibeams += laser\n",
    "    # setup coupling\n",
    "    config_multibeams.add_atomlight_coupling(\n",
    "        laser=laser, transition=\"main\", detuning=delta\n",
    "    )\n",
    "\n",
    "\n",
    "# show info\n",
    "config_singlebeam.print_atomlight_info()\n",
    "config_multibeams.print_atomlight_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -- Plotting the force, using simulator objects\n",
    "# imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from atomsmltr.simulation import RK4\n",
    "\n",
    "# define simulations\n",
    "sim_singlebeam = RK4(config_singlebeam)\n",
    "sim_multibeams = RK4(config_multibeams)\n",
    "\n",
    "# prepare grid\n",
    "\n",
    "grid = np.mgrid[-0.2:0.4:200j, 0:0:1j, 0:0:1j, -100:100:201j, 0:0:1j, 0:0:1j]\n",
    "grid = np.squeeze(grid)\n",
    "pos = grid.T\n",
    "X, _, _, VX, _, _ = grid\n",
    "\n",
    "# compute force\n",
    "force_singlebeam = sim_singlebeam.get_force(pos)\n",
    "FX_singlebeam, _, _ = force_singlebeam.T\n",
    "force_multibeams = sim_multibeams.get_force(pos)\n",
    "FX_multibeams, _, _ = force_multibeams.T\n",
    "\n",
    "# normalize to same value\n",
    "F_max = np.max(np.abs(FX_singlebeam))\n",
    "\n",
    "# prepare figure\n",
    "fix, ax = plt.subplots(1, 2, figsize=(9, 4), tight_layout=True)\n",
    "\n",
    "# plot single beam force\n",
    "c = ax[0].pcolormesh(X * 100, VX, FX_singlebeam / F_max)\n",
    "ax[0].set_title(\"Single beam | multi freq\")\n",
    "\n",
    "# plot multi beam\n",
    "ax[1].pcolormesh(X * 100, VX, FX_multibeams / F_max)\n",
    "ax[1].set_title(\"Multi beam | single freq\")\n",
    "\n",
    "# setup and show\n",
    "for cax in ax:\n",
    "    cax.set_xlabel(\"position (cm)\")\n",
    "    cax.set_ylabel(\"speed (m/s)\")\n",
    "    cax.grid()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "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": 2
}