{
 "metadata": {
  "name": "development-Qobj-extract-eliminate"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### QuTiP development notebook for testing extracting and eliminating states from a quantum object\n",
      "\n",
      "Copyright (C) 2011 and later, Paul D. Nation & Robert J. Johansson"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from qutip import *"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def visualize(result):\n",
      "    fig, ax = subplots(figsize=(12,6))\n",
      "    for idx, e in enumerate(result.expect):\n",
      "        ax.plot(result.times, e, label=\"%d\" % idx)\n",
      "    ax.legend()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Consider two coupled qubits:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "H0 = -2*pi*(tensor(sigmaz(), identity(2)) + tensor(identity(2), sigmaz()))\n",
      "Hint = 2*pi*0.1 * tensor(sigmax(), sigmax())\n",
      "\n",
      "H = H0 + Hint"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "H"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{equation}\\text{Quantum object: dims = [[2, 2], [2, 2]], shape = [4, 4], type = oper, isHerm = True}\\\\[1em]\\begin{pmatrix}-12.5663706144 & 0.0 & 0.0 & 0.628318530718\\\\0.0 & 0.0 & 0.628318530718 & 0.0\\\\0.0 & 0.628318530718 & 0.0 & 0.0\\\\0.628318530718 & 0.0 & 0.0 & 12.5663706144\\\\\\end{pmatrix}\\end{equation}"
       ],
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "Quantum object: dims = [[2, 2], [2, 2]], shape = [4, 4], type = oper, isherm = True\n",
        "Qobj data =\n",
        "[[-12.56637061   0.           0.           0.62831853]\n",
        " [  0.           0.           0.62831853   0.        ]\n",
        " [  0.           0.62831853   0.           0.        ]\n",
        " [  0.62831853   0.           0.          12.56637061]]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "energy_level_diagram([H], figsize=(6,6), show_ylabels=True);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAFdCAYAAAD49y2uAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n"
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If the highest energy state is not initially occupied, and if we neglect thermal excitations, it will never be occupied, and therefore not really necessary to include in a calculation of for example the dynamics of the three lowest states."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "psi_gg = tensor(basis(2, 0), basis(2, 0))\n",
      "psi_eg = tensor(basis(2, 1), basis(2, 0))\n",
      "psi_ge = tensor(basis(2, 0), basis(2, 1))\n",
      "psi_ee = tensor(basis(2, 1), basis(2, 1))\n",
      "\n",
      "c_op1 = tensor(destroy(2), identity(2))\n",
      "c_op2 = tensor(identity(2), destroy(2))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "psi0 = psi_eg"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tlist = linspace(0, 15, 100)\n",
      "result = mesolve(H, psi0, tlist,\n",
      "                 [sqrt(0.1) * c_op1, sqrt(0.25) * c_op2],\n",
      "                 [ket2dm(psi_gg), ket2dm(psi_ge), ket2dm(psi_eg), ket2dm(psi_ee)])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize(result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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g8mRo2RIaNQK7HVasgHnzoFMnhWEREfEOCsRgmh3r1DEDUt3Ilyu/JLBgIJ1D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\n"
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that the fourth state is not included in the dynamics at all. So..."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Assume we want to create a new Qobj instance using the three lowest states:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# We are only interested in these states\n",
      "keep_states = [0, 1, 2]\n",
      "\n",
      "# or equivalently, not interested in these states\n",
      "remove_states = [3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "H_sub = H.eliminate_states(remove_states)\n",
      "\n",
      "H_sub"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{equation}\\text{Quantum object: dims = [[3], [3]], shape = [3, 3], type = oper, isHerm = True}\\\\[1em]\\begin{pmatrix}-12.5663706144 & 0.0 & 0.0\\\\0.0 & 0.0 & 0.628318530718\\\\0.0 & 0.628318530718 & 0.0\\\\\\end{pmatrix}\\end{equation}"
       ],
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "Quantum object: dims = [[3], [3]], shape = [3, 3], type = oper, isherm = True\n",
        "Qobj data =\n",
        "[[-12.56637061   0.           0.        ]\n",
        " [  0.           0.           0.62831853]\n",
        " [  0.           0.62831853   0.        ]]"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "H_sub = H.extract_states(keep_states)\n",
      "\n",
      "H_sub"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{equation}\\text{Quantum object: dims = [[3], [3]], shape = [3, 3], type = oper, isHerm = True}\\\\[1em]\\begin{pmatrix}-12.5663706144 & 0.0 & 0.0\\\\0.0 & 0.0 & 0.628318530718\\\\0.0 & 0.628318530718 & 0.0\\\\\\end{pmatrix}\\end{equation}"
       ],
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "Quantum object: dims = [[3], [3]], shape = [3, 3], type = oper, isherm = True\n",
        "Qobj data =\n",
        "[[-12.56637061   0.           0.        ]\n",
        " [  0.           0.           0.62831853]\n",
        " [  0.           0.62831853   0.        ]]"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "energy_level_diagram([H_sub], figsize=(6,6), show_ylabels=True);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAFhCAYAAACLT+p4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngEDiDhBI3AECiTtAoP8A9LFQNb2VuUEAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "psi0_sub = psi0.extract_states(keep_states, normalize=True)\n",
      "\n",
      "psi0_sub"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{equation}\\text{Quantum object: dims = [[3], [1]], shape = [3, 1], type = ket}\\\\[1em]\\begin{pmatrix}0.0\\\\0.0\\\\1.0\\\\\\end{pmatrix}\\end{equation}"
       ],
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "Quantum object: dims = [[3], [1]], shape = [3, 1], type = ket\n",
        "Qobj data =\n",
        "[[ 0.]\n",
        " [ 0.]\n",
        " [ 1.]]"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c_op1_sub = c_op1.extract_states(keep_states)\n",
      "c_op2_sub = c_op2.extract_states(keep_states)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "psi_gg_sub = psi_gg.extract_states(keep_states)\n",
      "psi_eg_sub = psi_eg.extract_states(keep_states)\n",
      "psi_ge_sub = psi_ge.extract_states(keep_states)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tlist = linspace(0, 15, 100)\n",
      "result = mesolve(H_sub, psi0_sub, tlist,\n",
      "                 [sqrt(0.1) * c_op1_sub, sqrt(0.25) * c_op2_sub],\n",
      "                 [ket2dm(psi_gg_sub), ket2dm(psi_ge_sub), ket2dm(psi_eg_sub)])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "visualize(result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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N7nWrQBwVFcUzzzxDSkoKjz76KC+99NJV3z969Ci9evXi4MGDJCcn8/zzz9O3b99sF5Zp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      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Voila! Same results with fewer quantum states in the calculation, and therefore potentially more efficient."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Software versions"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from qutip.ipynbtools import version_table\n",
      "version_table()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table><tr><th>Software</th><th>Version</th></tr><tr><td>Cython</td><td>0.19-dev</td></tr><tr><td>SciPy</td><td>0.13.0.dev-38ad5d2</td></tr><tr><td>QuTiP</td><td>2.3.0.dev-9e45c8d</td></tr><tr><td>Python</td><td>2.7.3 (default, Sep 26 2012, 21:51:14) \n",
        "[GCC 4.7.2]</td></tr><tr><td>IPython</td><td>0.13</td></tr><tr><td>OS</td><td>posix [linux2]</td></tr><tr><td>Numpy</td><td>1.8.0.dev-bd7104c</td></tr><tr><td>matplotlib</td><td>1.3.x</td></tr><tr><td colspan='2'>Wed Mar 13 16:25:43 2013</td></tr></table>"
       ],
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "<IPython.core.display.HTML at 0x35d5dd0>"
       ]
      }
     ],
     "prompt_number": 20
    }
   ],
   "metadata": {}
  }
 ]
}