Majumdar PRB 84 085309.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from qutip import *\n",
    "import pylab as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "N = 4                         # number of cavity fock states\n",
    "wc = 1.0 * 2 * np.pi     # cavity and atom frequency\n",
    "g = 20 * 2 * np.pi       # coupling strength\n",
    "kappa = 20*2*np.pi     # cavity dissipation rate\n",
    "\n",
    "\n",
    "gamma = 2*np.pi*1    # atom dissipation rate\n",
    "gamma_r = 2*np.pi*0.5\n",
    "gamma_d = 2*np.pi*0.5\n",
    "\n",
    "delta = 6*kappa\n",
    "wa = wc+delta\n",
    "omega = 2*np.pi * 6\n",
    "wl = wa                     # resonantly driven QD with Laser\n",
    "deltawc = wc-wl\n",
    "deltawa = wa-wl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Jaynes-Cummings Hamiltonian\n",
    "a  = tensor(qeye(N), destroy(2))\n",
    "sm = tensor(destroy(N), qeye(2))\n",
    "\n",
    "H = deltawc * a.dag() * a + deltawa * sm.dag() * sm + 1j * g * (a.dag() * sm - a * sm.dag()) + omega * (sm + sm.dag())\n",
    "\n",
    "# collapse operators\n",
    "\n",
    "n=0 #limit approximation\n",
    "c_ops =[np.sqrt(2*kappa)*a,np.sqrt(2*gamma)*sm,np.sqrt(2*gamma_r*n)*spre(sm.dag())*spost(a),np.sqrt(2*gamma_r*(n+1))*spre(sm)*spost(a.dag()),np.sqrt(2*gamma_d)*spre(sm.dag())*spost(sm)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "Quantum object: dims = [[4, 2], [4, 2]], shape = [8, 8], type = oper, isherm = True\\begin{equation*}\\left(\\begin{array}{*{11}c}0.0 & 0.0 & 37.699 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0\\\\0.0 & -753.982 & 125.664j & 37.699 & 0.0 & 0.0 & 0.0 & 0.0\\\\37.699 & -125.664j & 0.0 & 0.0 & 53.315 & 0.0 & 0.0 & 0.0\\\\0.0 & 37.699 & 0.0 & -753.982 & 177.715j & 53.315 & 0.0 & 0.0\\\\0.0 & 0.0 & 53.315 & -177.715j & 0.0 & 0.0 & 65.297 & 0.0\\\\0.0 & 0.0 & 0.0 & 53.315 & 0.0 & -753.982 & 217.656j & 65.297\\\\0.0 & 0.0 & 0.0 & 0.0 & 65.297 & -217.656j & 0.0 & 0.0\\\\0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 65.297 & 0.0 & -753.982\\\\\\end{array}\\right)\\end{equation*}"
      ],
      "text/plain": [
       "Quantum object: dims = [[4, 2], [4, 2]], shape = [8, 8], type = oper, isherm = True\n",
       "Qobj data =\n",
       "[[   0.00000000  +0.j            0.00000000  +0.j           37.69911184  +0.j\n",
       "     0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j\n",
       "     0.00000000  +0.j            0.00000000  +0.j        ]\n",
       " [   0.00000000  +0.j         -753.98223686  +0.j\n",
       "     0.00000000+125.66370614j   37.69911184  +0.j            0.00000000  +0.j\n",
       "     0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j        ]\n",
       " [  37.69911184  +0.j            0.00000000-125.66370614j\n",
       "     0.00000000  +0.j            0.00000000  +0.j           53.31459526  +0.j\n",
       "     0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j        ]\n",
       " [   0.00000000  +0.j           37.69911184  +0.j            0.00000000  +0.j\n",
       "  -753.98223686  +0.j            0.00000000+177.71531753j\n",
       "    53.31459526  +0.j            0.00000000  +0.j            0.00000000  +0.j        ]\n",
       " [   0.00000000  +0.j            0.00000000  +0.j           53.31459526  +0.j\n",
       "     0.00000000-177.71531753j    0.00000000  +0.j            0.00000000  +0.j\n",
       "    65.29677711  +0.j            0.00000000  +0.j        ]\n",
       " [   0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j\n",
       "    53.31459526  +0.j            0.00000000  +0.j         -753.98223686  +0.j\n",
       "     0.00000000+217.65592371j   65.29677711  +0.j        ]\n",
       " [   0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j\n",
       "     0.00000000  +0.j           65.29677711  +0.j\n",
       "     0.00000000-217.65592371j    0.00000000  +0.j            0.00000000  +0.j        ]\n",
       " [   0.00000000  +0.j            0.00000000  +0.j            0.00000000  +0.j\n",
       "     0.00000000  +0.j            0.00000000  +0.j           65.29677711  +0.j\n",
       "     0.00000000  +0.j         -753.98223686  +0.j        ]]"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# calculate the power spectrum using spectrum, which internally uses essolve \n",
    "# to solve for the dynamics (by default)\n",
    "#wlist2 = np.linspace(-5, 5, 200000) * 2 * np.pi\n",
    "wlist2 = np.linspace(-8, 8, 200000) * kappa # AMCD\n",
    "spec2 = spectrum(H, wlist2, c_ops, a.dag(), a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x12569d0f0>"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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ZZ59Njx49OOyww5g2bRoAGzdu5Bvf+Aa9evVi8ODB9OnTh8svvzxv/htSyujSpQvTp09n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\nc03KA4tzzrkm9f8B08UT+d3wAwEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x124b9f908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot((wlist2 ) / kappa, spec2, 'r', lw=2, label='eseries method')\n",
    "plt.legend()\n",
    "ax = plt.gca()\n",
    "ax.set_xlabel('Frequency')\n",
    "ax.set_ylabel('Power spectrum')\n",
    "ax.set_title('Vacuum Mollow Triplet')\n",
    "#ax.set_xlim(-wlist2[0]/(2*np.pi), wlist2[-1]/(2*np.pi))\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [qutip]",
   "language": "python",
   "name": "Python [qutip]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}