{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Optimization of a dissipative state-to-state transfer in a Lambda system" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "attributes": { "classes": [], "id": "", "n": "1" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "qutip 4.3.1\n", "numpy 1.15.4\n", "scipy 1.1.0\n", "matplotlib 3.0.2\n", "matplotlib.pylab 1.15.4\n", "krotov 0.0.1\n", "CPython 3.6.7\n", "IPython 7.2.0\n" ] } ], "source": [ "# NBVAL_IGNORE_OUTPUT\n", "%load_ext watermark\n", "import qutip\n", "import numpy as np\n", "import scipy\n", "import matplotlib\n", "import matplotlib.pylab as plt\n", "import krotov\n", "import qutip\n", "from qutip import Qobj\n", "import pickle\n", "%watermark -v --iversions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$\\newcommand{tr}[0]{\\operatorname{tr}}\n", "\\newcommand{diag}[0]{\\operatorname{diag}}\n", "\\newcommand{abs}[0]{\\operatorname{abs}}\n", "\\newcommand{pop}[0]{\\operatorname{pop}}\n", "\\newcommand{aux}[0]{\\text{aux}}\n", "\\newcommand{opt}[0]{\\text{opt}}\n", "\\newcommand{tgt}[0]{\\text{tgt}}\n", "\\newcommand{init}[0]{\\text{init}}\n", "\\newcommand{lab}[0]{\\text{lab}}\n", "\\newcommand{rwa}[0]{\\text{rwa}}\n", "\\newcommand{bra}[1]{\\langle#1\\vert}\n", "\\newcommand{ket}[1]{\\vert#1\\rangle}\n", "\\newcommand{Bra}[1]{\\left\\langle#1\\right\\vert}\n", "\\newcommand{Ket}[1]{\\left\\vert#1\\right\\rangle}\n", "\\newcommand{Braket}[2]{\\left\\langle #1\\vphantom{#2} \\mid\n", "#2\\vphantom{#1}\\right\\rangle}\n", "\\newcommand{Ketbra}[2]{\\left\\vert#1\\vphantom{#2}\n", "\\right\\rangle \\hspace{-0.2em} \\left\\langle #2\\vphantom{#1} \\right\\vert}\n", "\\newcommand{op}[1]{\\hat{#1}}\n", "\\newcommand{Op}[1]{\\hat{#1}}\n", "\\newcommand{dd}[0]{\\,\\text{d}}\n", "\\newcommand{Liouville}[0]{\\mathcal{L}}\n", "\\newcommand{DynMap}[0]{\\mathcal{E}}\n", "\\newcommand{identity}[0]{\\mathbf{1}}\n", "\\newcommand{Norm}[1]{\\lVert#1\\rVert}\n", "\\newcommand{Abs}[1]{\\left\\vert#1\\right\\vert}\n", "\\newcommand{avg}[1]{\\langle#1\\rangle}\n", "\\newcommand{Avg}[1]{\\left\\langle#1\\right\\rangle}\n", "\\newcommand{AbsSq}[1]{\\left\\vert#1\\right\\vert^2}\n", "\\newcommand{Re}[0]{\\operatorname{Re}}\n", "\\newcommand{Im}[0]{\\operatorname{Im}}\n", "\\newcommand{toP}[0]{\\omega_{12}}\n", "\\newcommand{toS}[0]{\\omega_{23}}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The aim of this example is to test the\n", "behaviour of Krotov's algorithm when\n", "dealing with non-Hermitian Hamiltonians.\n", "This notebook is heavily based on the\n", "example \"Optimization of a state-to-state\n", "transfer in a lambda system with RWA\",\n", "and therefore it is recommended that the\n", "reader become familiar with the system\n", "before hand. The main change in the\n", "results will be represented by the loss of\n", "norm during the propagation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Define the Hamiltonian" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We start with the usual 3-level lambda system such that\n", "$E_1 < E_2$ and $E_3 <\n", "E_2$. The states $\\Ket{1}$ and $\\Ket{2}$ are coupled\n", "coupled through a pump\n", "laser with frequency $\\omega_{P}=\\omega_{P}(t)$ and\n", "similarly for the states\n", "$\\Ket{2}$ and $\\Ket{3}$ through a Stokes laser with\n", "frequency\n", "$\\omega_{S}=\\omega_{S}(t)$.\n", "\n", "The level $\\Ket{2}$ is assumed to\n", "experience a\n", "spontaneous decay into a reservoir that is out of the Hilbert\n", "space. This can be\n", "reproduced with a simple model that adds a dissipative\n", "coefficient $\\gamma > 0$,\n", "such that the original eigenvalue for the second level\n", "is modified into $E_2\n", "\\rightarrow E_2 - i \\gamma$.\n", "\n", "We perform the same\n", "rotating wave approximation as\n", "described in the aforementioned example and\n", "obtain the time independent\n", "Hamiltonian\n", "\n", "\\begin{equation}\n", " \\op{H}_{0} =\n", " \\Delta_{P}\\Ketbra{1}{1} -i\n", "\\gamma \\Ketbra{2}{2} +\\Delta_{S} \\Ketbra{3}{3}\n", "\\end{equation}\n", "\n", "with the\n", "detunings $\\Delta_{P}=E_{1} + \\omega_{P} - E_{2}$ and\n", "$\\Delta_{S} = E_{3} +\n", "\\omega_{S} -E_{2}$.\n", "\n", "The control Hamiltonian is again given by\n", "\n", "\\begin{equation}\n", "\\op{H}_{1}(t)\n", " = \\op{H}_{1,P}(t) + \\op{H}_{1,S}(t)\n", " = \\Omega_{P}(t)\n", "\\Ketbra{1}{2} +\n", " \\Omega_{S}(t)\\Ketbra{2}{3} + \\text{H.c.}\\,,\n", "\\end{equation}\n", "where $\\Omega_{P} = \\Omega_{P}(t) = \\frac{\\mu_{21} \\varepsilon_{P}(t)}{2}\n", "e^{-i\\Phi_{S}(t) t}$\n", "and $\\Omega_{S} = \\Omega_{S}(t) = \\frac{\\mu_{23}\n", "\\varepsilon_{S}(t)}{2} e^{-i\\Phi_{P}(t) t}$\n", "with the phases $\\Phi_{P}(t) = \\toP\n", "- \\omega_{P}(t)$ and\n", "$\\Phi_{S}(t) = \\toS - \\omega_{S}(t)$ and $\\mu_{ij}$ the\n", "$ij^{\\text{th}}$ dipole-transition moment.\n", "\n", "For optimizing the complex pulses we\n", "once again\n", "separate them into their real and imaginary parts, i.e.,\n", "$\\Omega_{P}(t) = \\Omega_{P}^\\text{Re}(t) + i\\Omega_{P}^\\text{Im}(t)$\n", "and\n", "$\\Omega_{S}(t) = \\Omega_{S}^\\text{Re}(t) + i\\Omega_{S}^\\text{Im}(t)$,\n", "so we can\n", "optimize four real pulses." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "attributes": { "classes": [], "id": "", "n": "2" } }, "outputs": [], "source": [ "def ham_and_states():\n", " \"\"\"Lambda-system Hamiltonian\"\"\"\n", " E1 = 0.0\n", " E2 = 10.0\n", " E3 = 5.0\n", " ω_P = 9.5\n", " ω_S = 4.5\n", " gamma = 0.5\n", " Ω_init = 5.0\n", " H0 = Qobj(\n", " [\n", " [E1 + ω_P - E2, 0.0, 0.0],\n", " [0.0, -gamma * 1.0j, 0.0],\n", " [0.0, 0.0, E3 + ω_S - E2],\n", " ]\n", " )\n", "\n", " H1P_re = Qobj([[0.0, -1.0, 0.0], [-1.0, 0.0, 0.0], [0.0, 0.0, 0.0]])\n", " H1P_im = Qobj([[0.0, -1.0j, 0.0], [1.0j, 0.0, 0.0], [0.0, 0.0, 0.0]])\n", " ΩP_re = lambda t, args: Ω_init\n", " ΩP_im = lambda t, args: Ω_init\n", "\n", " H1S_re = Qobj([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0], [0.0, 1.0, 0.0]])\n", " H1S_im = Qobj([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0j], [0.0, -1.0j, 0.0]])\n", " ΩS_re = lambda t, args: Ω_init\n", " ΩS_im = lambda t, args: Ω_init\n", "\n", " \"\"\"Initial and target states\"\"\"\n", " psi0 = qutip.Qobj(np.array([1.0, 0.0, 0.0]))\n", " psi1 = qutip.Qobj(np.array([0.0, 0.0, 1.0]))\n", "\n", " return (\n", " [\n", " H0,\n", " [H1P_re, ΩP_re],\n", " [H1P_im, ΩP_im],\n", " [H1S_re, ΩS_re],\n", " [H1S_im, ΩS_im],\n", " ],\n", " psi0,\n", " psi1,\n", " )\n", "\n", "\n", "H, psi0, psi1 = ham_and_states()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We check whether our Hamiltonians are Hermitian:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "attributes": { "classes": [], "id": "", "n": "3" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "H0 is Hermitian: False\n", "H1 is Hermitian: True\n" ] } ], "source": [ "print(\"H0 is Hermitian: \" + str(H[0].isherm))\n", "print(\"H1 is Hermitian: \"+ str(\n", " H[1][0].isherm\n", " and H[2][0].isherm\n", " and H[3][0].isherm\n", " and H[4][0].isherm))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We introduce projectors for each of the three energy levels\n", "$\\op{P}_{i} =\n", "\\Ketbra{i}{i}$" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "attributes": { "classes": [], "id": "", "n": "4" } }, "outputs": [], "source": [ "proj1 = Qobj([[1.,0.,0.],[0.,0.,0.],[0.,0.,0.]])\n", "proj2 = Qobj([[0.,0.,0.],[0.,1.,0.],[0.,0.,0.]])\n", "proj3 = Qobj([[0.,0.,0.],[0.,0.,0.],[0.,0.,1.]])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Define the optimization target\n", "\n", "It is necessary to create a time grid to work\n", "with. In this example we choose a time interval starting at $t_0 = 0$ and ending\n", "at $t_f = 5$ with $n_t = 500$ equidistant time steps." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "attributes": { "classes": [], "id": "", "n": "5" } }, "outputs": [], "source": [ "t0 = 0.\n", "tf = 5.\n", "nt = 500\n", "tlist = np.linspace(t0, tf, nt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We define the objective to be a state to state transfer from the initial state\n", "$\\Ket{\\Psi_{\\init}} = \\Ket{1}$ into the final state $\\Ket{\\Psi_{\\tgt}} =\n", "\\Ket{3}$ at the\n", "final time $t_{f}$." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "attributes": { "classes": [], "id": "", "n": "6" } }, "outputs": [], "source": [ "objectives = [ krotov.Objective(initial_state=psi0, target=psi1, H=H) ]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Initial guess shapes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\"stimulated Raman adiabatic passage\" (STIRAP) is a\n", "process in which population in $\\Ket{1}$ is transferred into\n", "$\\Ket{3}$ without\n", "having to pass through $\\Ket{2}$ (which could for instance be a rapidly decaying\n", "level).\n", "In order for this process to occur, a temporally finite Stokes pulse of\n", "sufficient amplitude driving the $\\Ket{2} \\leftrightarrow \\Ket{3}$ transition is\n", "applied first, whilst second pump pulse of similar intensity follows some time\n", "later such that the pulses still have a partial temporal overlap.\n", "\n", "In order to\n", "demonstrate the Krotov's optimization method however, we choose an initial guess\n", "consisting of two low intensity and real Blackman pulses which are temporally\n", "disjoint.\n", "\n", "For the real components of the matrix elements, we supply our guess\n", "pulses shaped as Blackman window functions `S(t,offset)`, with an offset\n", "ensuring that the two pulses don't overlap.\n", "The imaginary components are coupled\n", "to pulses that are zero at all times." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "attributes": { "classes": [], "id": "", "n": "7" } }, "outputs": [], "source": [ "def S(t,offset):\n", " \"\"\"Shape envelope function for the field update\"\"\"\n", " return krotov.shapes.blackman(t,1.+offset,4.+offset)\n", "\n", "def shape_field_real(eps,offset):\n", " \"\"\"Applies the total pulse shape to the real part of a guess pulse\"\"\"\n", " field_shaped = lambda t, args: eps(t, args)*S(t,offset)\n", " return field_shaped\n", "\n", "def shape_field_imag(eps,offset):\n", " \"\"\"Initializes the imaginary parts of the guess pulses to zero\"\"\"\n", " field_shaped = lambda t, args: eps(t, args)*0.\n", " return field_shaped\n", "\n", "H[1][1] = shape_field_real(H[1][1],1.)\n", "H[2][1] = shape_field_imag(H[2][1],1.)\n", "H[3][1] = shape_field_real(H[3][1],-1.)\n", "H[4][1] = shape_field_imag(H[4][1],-1.)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We choose an appropriate update factor $\\lambda_{a}$ for the problem at hand and\n", "make sure Krotov considers pulses which start and end with zero amplitude." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "attributes": { "classes": [], "id": "", "n": "8" } }, "outputs": [], "source": [ "def update_shape(t):\n", " \"\"\"Scales the Krotov methods update of the pulse value at the time t\"\"\"\n", " return krotov.shapes.flattop(t,0.,5.,0.3,func='sinsq')" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "attributes": { "classes": [], "id": "", "n": "9" } }, "outputs": [], "source": [ "opt_lambda = 2.0\n", "pulse_options = {\n", " H[1][1]: krotov.PulseOptions(lambda_a=opt_lambda, shape=update_shape),\n", " H[2][1]: krotov.PulseOptions(lambda_a=opt_lambda, shape=update_shape),\n", " H[3][1]: krotov.PulseOptions(lambda_a=opt_lambda, shape=update_shape),\n", " H[4][1]: krotov.PulseOptions(lambda_a=opt_lambda, shape=update_shape),\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is possible to keep track of the fidelity during optimization by printing it\n", "after every iteration:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "attributes": { "classes": [], "id": "", "n": "10" } }, "outputs": [], "source": [ "def print_fidelity(**args):\n", " F_re = np.average(np.array(args['tau_vals']).real)\n", " print(\" F = %f\" % F_re)\n", " return F_re" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simulate dynamics of the guess field" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "attributes": { "classes": [], "id": "", "n": "11" } }, "outputs": [], "source": [ "def plot_pulse(pulse, tlist, plottitle=None):\n", " fig, ax = plt.subplots()\n", " if callable(pulse):\n", " pulse = np.array([pulse(t, args=None) for t in tlist])\n", " ax.plot(tlist, pulse)\n", " ax.set_xlabel('time')\n", " ax.set_ylabel('pulse amplitude')\n", " if(isinstance(plottitle, str)):\n", " ax.set_title(plottitle, fontsize = 15)\n", " plt.show(fig)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "attributes": { "classes": [], "id": "", "n": "12" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_pulse(H[1][1], tlist, plottitle='Re($\\Omega_P$)')\n", "plot_pulse(H[2][1], tlist, plottitle='Im($\\Omega_P$)')\n", "plot_pulse(H[3][1], tlist, plottitle='Re($\\Omega_S$)')\n", "plot_pulse(H[4][1], tlist, plottitle='Im($\\Omega_S$)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After assuring ourselves that our guess pulses appear as expected, we propagate\n", "the system using our guess. Since the pulses are temporally disjoint, we expect\n", "the first pulse to have no effect, whilst the second merely transfers population\n", "out of $\\Ket{1}$ into $\\Ket{2}$ and back again." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "attributes": { "classes": [], "id": "", "n": "13" } }, "outputs": [], "source": [ "guess_dynamics = objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm, e_ops=[proj1, proj2, proj3]\n", ")\n", "guess_states = objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm\n", ")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "attributes": { "classes": [], "id": "", "n": "14" } }, "outputs": [], "source": [ "def plot_population(result):\n", " fig, ax = plt.subplots()\n", " ax.axhline(y=1.0, color='black', lw=0.5, ls='dashed')\n", " ax.axhline(y=0.0, color='black', lw=0.5, ls='dashed')\n", " ax.plot(result.times, result.expect[0], label='1')\n", " ax.plot(result.times, result.expect[1], label='2')\n", " ax.plot(result.times, result.expect[2], label='3')\n", " ax.legend()\n", " ax.set_title('Expected values', fontsize = 15)\n", " ax.set_xlabel('time')\n", " ax.set_ylabel('population')\n", " plt.show(fig)\n", " \n", "def plot_norm(result):\n", " \n", " state_norm = lambda i: result.states[i].norm()\n", " states_norm=np.vectorize(state_norm)\n", " \n", " fig, ax = plt.subplots()\n", " ax.plot(result.times, states_norm(np.arange(len(result.states))))\n", " ax.set_title('Norm loss', fontsize = 15)\n", " ax.set_xlabel('time')\n", " ax.set_ylabel('state norm')\n", " plt.show(fig) " ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "attributes": { "classes": [], "id": "", "n": "15" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_population(guess_dynamics)\n", "plot_norm(guess_states)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Optimize" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now use all the information that we have gathered to initialize\n", "the optimization routine. That is: \n", "\n", "* The `objectives`: transferring population\n", "from $\\ket{1}$ to $\\ket{3}$ at $t_f$. \n", "\n", "* The `pulse_options`: initial pulses\n", "and their shapes restrictions. \n", "\n", "* The `propagator`: in our example we will\n", "choose a simple matrix exponential.\n", "\n", "* The `chi_constructor`: the optimization\n", "functional to use. \n", "\n", "* The `info_hook`: all processes taking place inbetween\n", "iterations, for example printing the fidelity in each step. \n", "\n", "* And the\n", "`iter_stop`: the number of iterations to perform the optimization." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "attributes": { "classes": [], "id": "", "n": "16" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " F = -0.023471\n", " F = 0.252788\n", " F = 0.482934\n", " F = 0.645488\n", " F = 0.747822\n", " F = 0.808026\n", " F = 0.842348\n", " F = 0.861826\n", " F = 0.873076\n", " F = 0.879839\n", " F = 0.884167\n", " F = 0.887170\n", " F = 0.889446\n", " F = 0.891318\n", " F = 0.892959\n", " F = 0.894461\n", " F = 0.895876\n", " F = 0.897232\n", " F = 0.898543\n", " F = 0.899818\n", " F = 0.901063\n" ] } ], "source": [ "oct_result = krotov.optimize_pulses(\n", " objectives, pulse_options, tlist,\n", " propagator=krotov.propagators.expm,\n", " chi_constructor=krotov.functionals.chis_re,\n", " info_hook=krotov.info_hooks.chain(\n", " #krotov.info_hooks.print_debug_information,\n", " print_fidelity),\n", " iter_stop=20\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can check that the algorithm takes into account the non Hermitian behaviour\n", "which leads to a non unitary final state. To improve the fidelity it is\n", "necessary to avoid these dissipative effects as much as possible." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "attributes": { "classes": [], "id": "", "n": "17" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pump pulse amplitude and phase:\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Stokes pulse amplitude and phase:\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def plot_pulse_amplitude_and_phase(pulse_real, pulse_imaginary,tlist):\n", " ax1 = plt.subplot(211)\n", " ax2 = plt.subplot(212)\n", " amplitudes = [np.sqrt(x*x + y*y) for x,y in zip(pulse_real,pulse_imaginary)]\n", " phases = [np.arctan2(y,x)/np.pi for x,y in zip(pulse_real,pulse_imaginary)]\n", " ax1.plot(tlist,amplitudes)\n", " ax1.set_xlabel('time')\n", " ax1.set_ylabel('pulse amplitude')\n", " ax2.plot(tlist,phases)\n", " ax2.set_xlabel('time')\n", " ax2.set_ylabel('pulse phase (π)') \n", " plt.show()\n", " \n", "print(\"pump pulse amplitude and phase:\")\n", "plot_pulse_amplitude_and_phase(\n", " oct_result.optimized_controls[0], oct_result.optimized_controls[1], tlist)\n", "print(\"Stokes pulse amplitude and phase:\")\n", "plot_pulse_amplitude_and_phase(\n", " oct_result.optimized_controls[2], oct_result.optimized_controls[3], tlist)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We check the evolution of the population due to our optimized pulses." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "attributes": { "classes": [], "id": "", "n": "18" } }, "outputs": [], "source": [ "opt_dynamics = oct_result.optimized_objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm, e_ops=[proj1, proj2, proj3])\n", "opt_states = oct_result.optimized_objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "attributes": { "classes": [], "id": "", "n": "19" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_population(opt_dynamics)\n", "plot_norm(opt_states)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we can see the algorithm takes into account the decay in level $\\ket{2}$ and\n", "minimizes the population in this level during the process.\n", "\n", "However, convergence\n", "is relatively slow, and after 20 iterations, we have only\n", "achieved a 90%\n", "fidelity. As we can see from the population dynamics, we do not\n", "fully transfer\n", "the population in state $\\ket{3}$, and there is still non-\n", "negligible population\n", "in state $\\ket{2}$. If we were to continue up to iteration\n", "2000, the\n", "optimization converges much farther:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "attributes": { "classes": [], "id": "", "n": "20" } }, "outputs": [], "source": [ "oct_result = krotov.result.Result.load(\n", " './non_herm_oct_result.dump', objectives\n", ")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "attributes": { "classes": [], "id": "", "n": "21" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Final fidelity: 0.986\n" ] } ], "source": [ "print(\"Final fidelity: %.3f\" % oct_result.info_vals[-1])" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "attributes": { "classes": [], "id": "", "n": "22" } }, "outputs": [], "source": [ "def plot_convergence(result):\n", " fig, ax = plt.subplots()\n", " ax.semilogy(result.iters, 1-np.array(result.info_vals))\n", " ax.set_xlabel('OCT iteration')\n", " ax.set_ylabel('error')\n", " plt.show(fig)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "attributes": { "classes": [], "id": "", "n": "23" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_convergence(oct_result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dynamics now show a very good population transfer and negligible population\n", "in state $\\ket{2}$." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "attributes": { "classes": [], "id": "", "n": "24" } }, "outputs": [], "source": [ "opt_dynamics = oct_result.optimized_objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm, e_ops=[proj1, proj2, proj3])\n", "opt_states = oct_result.optimized_objectives[0].propagate(\n", " tlist, propagator=krotov.propagators.expm)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "attributes": { "classes": [], "id": "", "n": "25" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pump pulse amplitude and phase:\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Stokes pulse amplitude and phase:\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "print(\"pump pulse amplitude and phase:\")\n", "plot_pulse_amplitude_and_phase(\n", " oct_result.optimized_controls[0], oct_result.optimized_controls[1], tlist)\n", "print(\"Stokes pulse amplitude and phase:\")\n", "plot_pulse_amplitude_and_phase(\n", " oct_result.optimized_controls[2], oct_result.optimized_controls[3], tlist)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "attributes": { "classes": [], "id": "", "n": "26" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_population(opt_dynamics)\n", "plot_norm(opt_states)" ] } ], "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": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 2 }