{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mitigate crosstalk in dense arrays of semiconductor spin qubits\n",
    "**Using Boulder Opal to model and mitigate crosstalk in dense qubit arrays caused by non-linear response to control signals**\n",
    "\n",
    "Crosstalk is one of the main limitations to the gate fidelity in dense semiconductor spin qubit arrays. This problem is especially relevant when all qubits are driven with a single control line. Advanced experiments avoid crosstalk by only driving one single-qubit gate at a time and reducing the Rabi frequency to [syncronize with crosstalk effects](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.97.085421), but this approach limits the scalability of the spin qubit platform.\n",
    "\n",
    "A recent [publication](https://journals.aps.org/prapplied/abstract/10.1103/PhysRevApplied.19.044078) by Brennant Undseth et al. linked crosstalk to nonlinear response functions in a qubit model.\n",
    "In this application note, we will investigate the influence of a non-linear response to electric signals on crosstalk and show how to mitigate these effects using optimal control.\n",
    "\n",
    "The presented crosstalk model is compatible with the simulation of [error sources](https://docs.q-ctrl.com/boulder-opal/toolkit/design/design-error-robust-quantum-logic-gates/how-to-create-dephasing-and-amplitude-robust-single-qubit-gates) or [leakage](https://docs.q-ctrl.com/boulder-opal/toolkit/design/design-error-robust-quantum-logic-gates/how-to-create-leakage-robust-single-qubit-gates). This allows to simulate multiple sources of decoherence simultaneously and take second-order effects like the crosstalk of noise signals into account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy\n",
    "import warnings\n",
    "import qctrlvisualizer as qv\n",
    "\n",
    "plt.style.use(qv.get_qctrl_style())\n",
    "\n",
    "import boulderopal as bo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation of crosstalk\n",
    "Before considering the control problem, let's begin by modeling the crosstalk effect. Our starting point is the Hamiltonian of a single electron spin in an inhomogeneous magnetic field:\n",
    "\n",
    "$$H = \\frac{E_z}{2 \\hbar} \\sigma_z +\\frac{g \\mu_B B_x}{2 \\hbar} \\sigma_x,$$\n",
    "\n",
    "with $\\sigma_x$ and $\\sigma_z$ denoting Pauli matrices. $E_z$ is the Zeeman energy, $g$ is the material dependent g-factor, $\\mu_B$ is the Bohr's magneton, and $B_x$ is an effective transversal magnetic field component. We assume that the qubit is subjected to electron dipole spin resonance (EDSR) driving, where the transversal magnetic field is driven with a time-dependent electric signal that displaces the electron in an inhomogeneous magnetic field.\n",
    "\n",
    "The relation between the amplitude of the driving electric signal and the amplitude in the oscillations of $B_x$ are usually assumed to be linear, but experiments have shown a nonlinear behavior. Theoretical explanations for the nonlinearity exist, for example tracing it back to an anharmonic confinement potential of the quantum dots. For our purposes it suffices to consider the phenomenological model implemented in the function below. It takes as input a range of real value voltages between -1 and 1 and returns a hyperbolic tangent response to the applied field with an adjustable parameter `tanh_range_parameter`.  This response could be interpreted, for example, as the effective displacement of a quantum dot in an inhomogeneous transversal magnetic field.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def response_function(voltage, tanh_range_parameter=3, graph=None):\n",
    "    if graph is None:\n",
    "        tanh = np.tanh\n",
    "    else:\n",
    "        tanh = graph.tanh\n",
    "    return 1e7 * 2 * np.pi * tanh(tanh_range_parameter * voltage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the response function.\n",
    "voltage_range = np.linspace(-1, 1, 100)\n",
    "qubit_response = response_function(voltage_range)\n",
    "\n",
    "plt.plot(voltage_range, qubit_response / 2 / np.pi * 1e-6)\n",
    "plt.ylabel(\"$g \\mu_B B_x / \\hbar$ (MHz)\")\n",
    "plt.xlabel(\"Gate voltage (a.u.)\")\n",
    "plt.title(\"Qubit response to driving signal\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This phenomenological response function represents well the experimental results of Undseth et al., as we will show by reproducing the Rabi oscillations. In an actual setup, this function should be measured for each quantum dot individually by driving only a single qubit and sweeping amplitude and offset of the signal. If the non-linearity is found to be unstable or difficult to measure accurately, then a variation to the non-linearity could also be added as a noise parameter in the simulation. This would allow us to find pulses that are robust towards errors in the calibration of the non-linearity. For the sake of simplicity, we use the same response function for all simulated qubits.\n",
    "\n",
    "Next, we demonstrate how to validate a phenomenological model by reproducing the experimental results of Undseth et.al.. This requires only two control signals with a constant envelope. In the multiplexer, the constant signals $B_x{q_1}$ and $B_x{q_2}$ are modulated with the driving frequencies and added so that the total field is\n",
    "\n",
    "$$B_x(t) = e^{-i \\omega_{q_1} t} B_x{q_1} + e^{-i \\omega_{q_2} t} B_x{q_2}.$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "control_segment_count = 100\n",
    "time_step = 5e-9  # 5 ns\n",
    "detuning = 2 * np.pi * 20e6  # 20 MHz\n",
    "resonance_frequency = 2 * np.pi * 10e9  # 10 Ghz\n",
    "time_sample_count = 1000\n",
    "\n",
    "lab_frame_time_step = 2 * np.pi / resonance_frequency / 10\n",
    "duration = control_segment_count * time_step\n",
    "simulation_segment_count = int(np.round(duration / lab_frame_time_step))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we define a function that creates a graph that implements our qubit model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simulate_single_qubit_with_offresonant_drive(\n",
    "    graph, total_signal, resonance_frequency, time_sample_count=time_sample_count\n",
    "):\n",
    "    \"\"\"\n",
    "    Implement a Loss–Divincenzo qubit subjected to EDSR.\n",
    "    \"\"\"\n",
    "    drift_hamiltonian = resonance_frequency * graph.pauli_matrix(\"Z\") / 2\n",
    "\n",
    "    control_hamiltonian = total_signal * 0.5 * graph.pauli_matrix(\"X\")\n",
    "\n",
    "    total_hamiltonian = drift_hamiltonian + control_hamiltonian\n",
    "\n",
    "    initial_state = np.asarray([[1], [0]])\n",
    "\n",
    "    time_array = np.linspace(0, duration, time_sample_count, endpoint=False)\n",
    "    unitaries = graph.time_evolution_operators_pwc(\n",
    "        hamiltonian=total_hamiltonian, sample_times=time_array\n",
    "    )\n",
    "\n",
    "    propagated_states = unitaries @ initial_state\n",
    "    propagated_states.name = \"propagated_states\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We add a convenience function to execute the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sweep_amplitudes_1q_sin(\n",
    "    amps_q1,\n",
    "    amps_q2,\n",
    "    angular_freq_q1_drive=resonance_frequency,\n",
    "    angular_freq_q2_drive=resonance_frequency + detuning,\n",
    "    resonance_frequency_sim=resonance_frequency,\n",
    "):\n",
    "    graph = bo.Graph()\n",
    "\n",
    "    # To efficiently simulate many experimental runs simultaneously,\n",
    "    # we use the batching capabilities of Boulder Opal.\n",
    "    q1_amplitude_batch = graph.constant_pwc(\n",
    "        constant=amps_q1[:, None], duration=duration, batch_dimension_count=2\n",
    "    )\n",
    "    q2_amplitude_batch = graph.constant_pwc(\n",
    "        constant=amps_q2[None, :], duration=duration, batch_dimension_count=2\n",
    "    )\n",
    "\n",
    "    # Modulate the driving signal.\n",
    "    time_pwc = graph.discretize_stf(\n",
    "        graph.identity_stf(), duration=duration, segment_count=simulation_segment_count\n",
    "    )\n",
    "    total_signal = graph.real(\n",
    "        graph.exp(-1j * angular_freq_q1_drive * time_pwc) * q1_amplitude_batch\n",
    "        + graph.exp(-1j * angular_freq_q2_drive * time_pwc) * q2_amplitude_batch\n",
    "    )\n",
    "    total_signal = response_function(graph=graph, voltage=total_signal)\n",
    "\n",
    "    simulate_single_qubit_with_offresonant_drive(\n",
    "        graph=graph,\n",
    "        total_signal=total_signal,\n",
    "        resonance_frequency=resonance_frequency_sim,\n",
    "    )\n",
    "\n",
    "    return bo.execute_graph(graph=graph, output_node_names=\"propagated_states\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have the simulation function defined, we consider a Rabi experiment where only one qubit (Q1) is driven and we plot the spin up probability of qubit Q1 as a function of time for various values of the driving field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "amps_q1_non_linearity = np.linspace(0.0, 1.0, 50, endpoint=True)\n",
    "amps_q2_non_linearity = np.asarray([0])\n",
    "result_sim_non_linearity = sweep_amplitudes_1q_sin(\n",
    "    amps_q1=amps_q1_non_linearity, amps_q2=amps_q2_non_linearity\n",
    ")\n",
    "time_steps_ns = np.linspace(0, duration, time_sample_count, endpoint=False) * 1e9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_time_resolved(fig, ax, yy, zz, xx=time_steps_ns, qubit_str=\"Q1\"):\n",
    "    \"\"\"\n",
    "    Plot the time resolved spin population.\n",
    "    \"\"\"\n",
    "    im = ax.pcolor(\n",
    "        xx, yy, zz, shading=\"nearest\", cmap=qv.QCTRL_SEQUENTIAL_COLORMAP, vmin=0, vmax=1\n",
    "    )\n",
    "    ax.set_xlabel(\"Time (ns)\")\n",
    "    ax.set_ylabel(f\"Amplitude {qubit_str} (a.u.)\")\n",
    "    fig.suptitle(f\"Spin up probability of {qubit_str}\")\n",
    "    fig.colorbar(im)\n",
    "\n",
    "\n",
    "states = result_sim_non_linearity[\"output\"][\"propagated_states\"][\"value\"][:, 0, :, 0, 0]\n",
    "fig, ax = plt.subplots()\n",
    "plot_time_resolved(\n",
    "    fig=fig,\n",
    "    ax=ax,\n",
    "    yy=amps_q1_non_linearity,\n",
    "    zz=np.abs(states) ** 2,\n",
    "    qubit_str=\"$B_x{q_1}$\",\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the plot above, the oscillation patterns for the different values of the voltage show that the effective Rabi rate initially rises (linearly) with the driving field before becoming constant in the strongly non-linear region.\n",
    "\n",
    "Next, we want to investigate the influence of the crosstalk model by driving both qubits simultaneously. In this case we drive Q1 with a constant amplitude, ramp up the amplitude of the drive on qubit Q2, and then fit the resulting data to extract the effective Rabi-frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "amps_q1_simultaneous_drive = np.asarray([0.4])\n",
    "amps_q2_simultaneous_drive = np.linspace(0.0, 0.8, 50, endpoint=True)\n",
    "result_sim_simultaneous_drive = sweep_amplitudes_1q_sin(\n",
    "    amps_q1=amps_q1_simultaneous_drive, amps_q2=amps_q2_simultaneous_drive\n",
    ")\n",
    "\n",
    "result_sim_q2_simultaneous_drive = sweep_amplitudes_1q_sin(\n",
    "    amps_q1=amps_q1_simultaneous_drive,\n",
    "    amps_q2=amps_q2_simultaneous_drive,\n",
    "    resonance_frequency_sim=resonance_frequency + detuning,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rabi_fit_func(t, rabi_freq):\n",
    "    \"\"\"\n",
    "    Fit function to extract Rabi frequency.\n",
    "    \"\"\"\n",
    "    return (np.cos(2 * np.pi * rabi_freq * t) + 1) / 2\n",
    "\n",
    "\n",
    "time_array = np.linspace(0, duration, time_sample_count, endpoint=False)\n",
    "\n",
    "# Fit the simulated data for qubit 1.\n",
    "states = result_sim_simultaneous_drive[\"output\"][\"propagated_states\"][\"value\"]\n",
    "n_vals = states.shape[1]\n",
    "\n",
    "rabi_freqs_q1 = np.zeros(shape=(n_vals,))\n",
    "\n",
    "initial_vals_rabi_freq_q1 = np.linspace(10e6, 5e6, n_vals) / 2\n",
    "\n",
    "for i in range(n_vals):\n",
    "    popt, pcov = scipy.optimize.curve_fit(\n",
    "        f=rabi_fit_func,\n",
    "        xdata=time_array,\n",
    "        ydata=np.abs(states[0, i, :, 0, 0]) ** 2,\n",
    "        p0=initial_vals_rabi_freq_q1[i],\n",
    "    )\n",
    "    rabi_freqs_q1[i] = popt[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fit the simulated data for qubit 2.\n",
    "rabi_freqs_q2 = np.zeros(shape=(n_vals,))\n",
    "\n",
    "initial_vals_rabi_freq_q2 = np.linspace(0, 12e6, n_vals) / 2\n",
    "\n",
    "states = result_sim_q2_simultaneous_drive[\"output\"][\"propagated_states\"][\"value\"]\n",
    "n_func_vals = states.shape[2]\n",
    "\n",
    "for i in range(n_vals):\n",
    "    if i < 10:\n",
    "        n_fit_vals = n_func_vals\n",
    "    else:\n",
    "        n_fit_vals = 20000\n",
    "\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\")\n",
    "        popt, pcov = scipy.optimize.curve_fit(\n",
    "            f=rabi_fit_func,\n",
    "            xdata=time_array[:n_fit_vals],\n",
    "            ydata=np.abs(states[0, i, :n_fit_vals, 0, 0]) ** 2,\n",
    "            p0=initial_vals_rabi_freq_q2[i],\n",
    "            maxfev=4000,\n",
    "            full_output=False,\n",
    "        )\n",
    "    rabi_freqs_q2[i] = popt[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x360 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the simulation and fitted data.\n",
    "fig, ax = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(15, 5))\n",
    "\n",
    "for ax_, zz_ in zip(\n",
    "    ax, [result_sim_simultaneous_drive, result_sim_q2_simultaneous_drive]\n",
    "):\n",
    "    plot_time_resolved(\n",
    "        fig=fig,\n",
    "        ax=ax_,\n",
    "        yy=amps_q2_simultaneous_drive,\n",
    "        zz=np.abs(zz_[\"output\"][\"propagated_states\"][\"value\"][0, :, :, 0, 0]) ** 2,\n",
    "        qubit_str=\"$B_x{q_2}$\",\n",
    "    )\n",
    "\n",
    "ax[0].set_title(\"Sim. Q1 spin up probability\")\n",
    "ax[1].set_title(\"Sim. Q2 spin up probability\")\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulated data resembles sufficiently closely the published data (compare Fig. 3, 4, and 5 in [Undseth et.al.](https://journals.aps.org/prapplied/abstract/10.1103/PhysRevApplied.19.044078)), such that we can proceed with this model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(amps_q2_simultaneous_drive, rabi_freqs_q1 * 1e-6, \"o\", label=\"Q1\")\n",
    "ax.plot(amps_q2_simultaneous_drive, rabi_freqs_q2 * 1e-6, \"o\", label=\"Q2\")\n",
    "ax.set_xlabel(r\"Amplitude Q2 (a.u.)\")\n",
    "ax.set_ylabel(\"Rabi frequency (MHz)\")\n",
    "ax.legend()\n",
    "ax.grid();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can clearly observe the strong influence of crosstalk. The effective Rabi frequency on qubit Q1 is reduced when increasing the amplitude of the drive on Q2. The Rabi frequency of qubit Q2 does not rise linearly with the increased amplitude.\n",
    "\n",
    "\n",
    "## Mitigation of crosstalk\n",
    "\n",
    "Based on the model above, we want to apply quantum robust control techniques to mitigate the crosstalk effect in 6-qubit arrays. The optimization is highly efficient, because we can neglect entanglement effects completely, as was demonstrated by [Undseth et al.](https://journals.aps.org/prapplied/abstract/10.1103/PhysRevApplied.19.044078) and the Hilbert space dimension thus scales only linearly with the number of simulated qubits. \n",
    "\n",
    "To mitigate the crosstalk, we will optimize the values of the piecewise constant envelopes of the effective resonant driving fields $B_x(t)$ on the different qubits. To simplify the problem and reduce the number of optimization variables, we will consider envelopes consisting of only two distinct time segments. In this case, we only need to optimize 2 complex degrees of freedom per qubit. For the implementation of the optimization, we proceed similarly to the simulation above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def multiplexing_and_physical_response(\n",
    "    graph, signals, angular_frequencies, simulation_segment_count, duration\n",
    "):\n",
    "    \"\"\"\n",
    "    Create the total drive signal.\n",
    "\n",
    "    For correct batching, the signals must all have the same duration\n",
    "    and the number of signals must match the number of angular_frequencies.\n",
    "    \"\"\"\n",
    "    time_pwc = graph.discretize_stf(\n",
    "        graph.identity_stf(), duration=duration, segment_count=simulation_segment_count\n",
    "    )\n",
    "    total_signal = 0\n",
    "    for angular_frequency, signal in zip(angular_frequencies, signals):\n",
    "        total_signal += graph.cos(angular_frequency * time_pwc) * graph.real(signal)\n",
    "        total_signal += graph.sin(angular_frequency * time_pwc) * graph.imag(signal)\n",
    "\n",
    "    return response_function(graph=graph, voltage=total_signal)\n",
    "\n",
    "\n",
    "def calculate_propagated_states(\n",
    "    graph,\n",
    "    duration,\n",
    "    angular_resonance_frequencies,\n",
    "    total_hamiltonian,\n",
    "    drift_hamiltonian,\n",
    "    sample_times,\n",
    "):\n",
    "    \"\"\"\n",
    "    Calculate the propagated states in the rotating frame.\n",
    "    \"\"\"\n",
    "\n",
    "    unitaries = graph.time_evolution_operators_pwc(\n",
    "        hamiltonian=total_hamiltonian, sample_times=sample_times\n",
    "    )\n",
    "    transformation_unitaries = graph.time_evolution_operators_pwc(\n",
    "        hamiltonian=drift_hamiltonian, sample_times=sample_times\n",
    "    )\n",
    "\n",
    "    transformation_unitaries_conjugated = graph.adjoint(transformation_unitaries)\n",
    "\n",
    "    initial_state = np.array([[1], [0]])\n",
    "    propagated_states_rot_frame = (\n",
    "        transformation_unitaries_conjugated @ unitaries @ initial_state\n",
    "    )\n",
    "    propagated_states_rot_frame.name = \"prop_states_rot_frame\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dense_array_graph(\n",
    "    angular_resonance_frequencies,\n",
    "    angular_driving_requencies,\n",
    "    duration,\n",
    "    simulation_segment_count,\n",
    "    control_segment_count,\n",
    "    sample_times,\n",
    "    target_gate=None,\n",
    "):\n",
    "    graph = bo.Graph()\n",
    "\n",
    "    signals = [\n",
    "        graph.complex_optimizable_pwc_signal(\n",
    "            segment_count=control_segment_count, duration=duration, maximum=1\n",
    "        )\n",
    "        for _ in angular_driving_requencies\n",
    "    ]\n",
    "    total_signal = multiplexing_and_physical_response(\n",
    "        graph=graph,\n",
    "        signals=signals,\n",
    "        angular_frequencies=angular_driving_requencies,\n",
    "        simulation_segment_count=simulation_segment_count,\n",
    "        duration=duration,\n",
    "    )\n",
    "\n",
    "    # Drift Hamiltonian.\n",
    "    frequency_batch = graph.constant_pwc(\n",
    "        angular_resonance_frequencies, duration=duration, batch_dimension_count=1\n",
    "    )\n",
    "    drift_hamiltonian = frequency_batch * graph.pauli_matrix(\"Z\") / 2\n",
    "\n",
    "    # Control Hamiltonian.\n",
    "    control_hamiltonian = total_signal * 0.5 * graph.pauli_matrix(\"X\")\n",
    "\n",
    "    # Evolution.\n",
    "    total_hamiltonian = drift_hamiltonian + control_hamiltonian\n",
    "    unitaries = graph.time_evolution_operators_pwc(\n",
    "        hamiltonian=total_hamiltonian, sample_times=[duration]\n",
    "    )\n",
    "\n",
    "    # Rotating frame.\n",
    "    transformation_unitaries = graph.time_evolution_operators_pwc(\n",
    "        hamiltonian=drift_hamiltonian, sample_times=[duration]\n",
    "    )\n",
    "\n",
    "    transformation_unitaries_conjugated = graph.adjoint(transformation_unitaries)\n",
    "\n",
    "    unitaries_rot_frame = (\n",
    "        transformation_unitaries_conjugated @ unitaries @ transformation_unitaries\n",
    "    )\n",
    "\n",
    "    # Infidelity.\n",
    "    if target_gate is None:\n",
    "        target_gate = graph.pauli_matrix(\"X\")\n",
    "\n",
    "    infidelities = graph.unitary_infidelity(unitaries_rot_frame, target_gate)\n",
    "\n",
    "    cost = graph.sum(infidelities, name=\"cost\")\n",
    "\n",
    "    # State evolution for visualization.\n",
    "    calculate_propagated_states(\n",
    "        graph=graph,\n",
    "        duration=duration,\n",
    "        angular_resonance_frequencies=angular_resonance_frequencies,\n",
    "        total_hamiltonian=total_hamiltonian,\n",
    "        drift_hamiltonian=drift_hamiltonian,\n",
    "        sample_times=sample_times,\n",
    "    )\n",
    "\n",
    "    return graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now run the optimization using Boulder Opal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final infidelity: 2.08e-05\n"
     ]
    }
   ],
   "source": [
    "# We assume an equal spacing between the resonance frequencies of the six qubits.\n",
    "qubit_count = 6\n",
    "resonance_frequencies = [\n",
    "    resonance_frequency - i * detuning\n",
    "    # Rather go below the 10Ghz, because they are used to calculate the time step.\n",
    "    for i in range(qubit_count)\n",
    "]\n",
    "lab_frame_time_step = 2 * np.pi / resonance_frequency / 10\n",
    "\n",
    "duration = 400e-9\n",
    "control_segment_count = 2\n",
    "\n",
    "graph = bo.Graph()\n",
    "simulation_segment_count = int(np.round(duration / lab_frame_time_step))\n",
    "\n",
    "graph = dense_array_graph(\n",
    "    angular_driving_requencies=resonance_frequencies,\n",
    "    angular_resonance_frequencies=resonance_frequencies,\n",
    "    duration=duration,\n",
    "    simulation_segment_count=simulation_segment_count,\n",
    "    control_segment_count=control_segment_count,\n",
    "    sample_times=np.linspace(0, duration, 100),\n",
    ")\n",
    "# By chosing the resonance frequencies exactly as the\n",
    "# driving frequencies, we neglect detuning errors or\n",
    "# shifts in the resonance frequency.\n",
    "# These effects can be inserted by a different choice of\n",
    "# parameters.\n",
    "\n",
    "result = bo.run_optimization(\n",
    "    graph=graph,\n",
    "    cost_node_name=\"cost\",\n",
    "    output_node_names=[\"prop_states_rot_frame\"],\n",
    "    max_iteration_count=50,\n",
    "    optimization_count=4,\n",
    "    cost_history_scope=\"ALL\",\n",
    ")\n",
    "print(f\"Final infidelity: {result['cost']:.2e}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting low infidelity shows that we can successfully apply an $X_\\pi$-gate simultaneously on all six qubit with our simple choice of control envelopes with only two segments. This indicates that the mitigation of crosstalk will most likely not require any additional degrees of freedom in realistic pulse optimization scenarios. The solution does not require complicated pulses that may be hard to implement or difficult to calibrate experimentally.\n",
    "    \n",
    "We can now visualize the evolution of the individual qubits on the Bloch sphere. As we requested an $X_\\pi$-gate on each qubit, we expect a $\\pi$ rotation when starting in the logical state $\\ket{0}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div\n",
       "        class=\"qctrlvisualizer\"\n",
       "        style=\"display:flex;flex-direction:column;align-items:center;\"\n",
       "    >\n",
       "        <div\n",
       "            class=\"qctrlvisualizer-wrapper\"\n",
       "            style=\"width:300px;height:300px;margin:0.5rem 0\"\n",
       "            id=\"qctrlvisualizer-wrapper-3cfa6994b0a046d4b30615207580ad62\"\n",
       "        ></div>\n",
       "        <input\n",
       "            class=\"qctrlvisualizer-progress-bar\"\n",
       "            style=\"margin:0.5rem 0\"\n",
       "            id=\"qctrlvisualizer-progress-bar-3cfa6994b0a046d4b30615207580ad62\"\n",
       "            type=\"range\"\n",
       "            min=\"0\"\n",
       "            max=\"1\"\n",
       "            step=\"0.01\"\n",
       "            value=\"0\"\n",
       "        >\n",
       "        <button\n",
       "            class=\"qctrlvisualizer-button qctrlvisualizer-button-play\"\n",
       "            style=\"margin:0.5rem 0\"\n",
       "            id=\"qctrlvisualizer-button-3cfa6994b0a046d4b30615207580ad62\"\n",
       "        >Play</button>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "\n    function visualizerLoader() {\n      if ((typeof Visualizer) == \"function\") {\n        console.log(\"Using preloaded Q-CTRL Visualizer JavaScript package.\");\n        displayBlochSphere();\n        return;\n      }\n\n      try {\n        console.log(\"Attempting to load https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js with require.js.\");\n        requirejs([\"https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js\"], displayBlochSphere, displayErrorMessage);\n      } catch(error) {\n        var existing_script = document.getElementById(\"qctrlvisualizer-script\");\n\n        if (existing_script !== null) {\n          console.log(\n            \"Script tag for the Q-CTRL Visualizer JavaScript package already exists.\"\n            + \" Delaying execution of function until script is loaded.\"\n          );\n          existing_script.addEventListener(\"load\", displayBlochSphere);\n          existing_script.addEventListener(\"error\", displayErrorMessage);\n          return;\n        }\n\n        console.log(\"Attempting to load https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js with script tag.\");\n        var script = document.createElement(\"script\");\n        script.onload = displayBlochSphere;\n        script.onerror = displayErrorMessage;\n        script.id = \"qctrlvisualizer-script\";\n        script.src = \"https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js\";\n        document.head.appendChild(script);\n      }\n    }\n\n    function displayBlochSphere() { \n    let isPlaying = false;\n    let progress = 0;\n\n    const visualizationData = {\"data\": {\"qubits\": [{\"name\": \"qubit1\", \"x\": [0.0, 0.06548876633723304, 0.1766729789248043, 0.2031144205593497, 0.13485466624987438, 0.20803045535919013, 0.3011223781476154, 0.29157281605563334, 0.20223262926639474, 0.2316158462136743, 0.2538163488426431, 0.21010765608603676, 0.14123331681571125, 0.13070648303636606, 0.19470788477955223, 0.2224736302152478, 0.21253790749786192, 0.20991101183174998, 0.22657199684792928, 0.2279419916323278, 0.2416736227138684, 0.24975341808204077, 0.22834062021464263, 0.24833924122042703, 0.3177438244136049, 0.3684238093530019, 0.3219914985733547, 0.27226963482854827, 0.2734918624787993, 0.325269095990892, 0.23147193437057934, 0.16316916766150966, 0.2061492409455142, 0.3138450003603713, 0.2378951401983912, 0.23482464990459367, 0.33800826000423434, 0.4679247988760608, 0.433822056802564, 0.32472332048890845, 0.2864439157917494, 0.3437190910723722, 0.30076336486474037, 0.2001359013665093, 0.19824197376057082, 0.27665799321655266, 0.26864458310471007, 0.23858800373467864, 0.2719046080883373, 0.3219041998332837, 0.3524588026368136, 0.3684561332170151, 0.3419774370584191, 0.3476394970951358, 0.3480208325739931, 0.33669407838714716, 0.3032000334353988, 0.3011440989172108, 0.27999007255033675, 0.28560231388300183, 0.20409992695473642, 0.18651597154570493, 0.22143179313396577, 0.11637781046887766, 0.19819695413331592, 0.1985789454990793, 0.10193170963679772, 0.06239788704150472, -0.05445888139920085, -0.08845944719890747, -0.12678753485635613, -0.11882289449881143, -0.17248404283615743, -0.27252422359931205, -0.18763782827714093, -0.24917447639109203, -0.2489720522805799, -0.19674013975424756, -0.2527376362017259, -0.28442249667973984, -0.31873197903232153, -0.3460849533017113, -0.3474063488069867, -0.3494378136557492, -0.34694793767727455, -0.31428205842371026, -0.32402857090513115, -0.32012069488774536, -0.2788742148130068, -0.3215151237080632, -0.30193641646259406, -0.2491981453376582, -0.2121780899374484, -0.11447939162052029, -0.10707962547783018, -0.06575308123878085, -0.07999960885404839, 0.01368861953886911, 0.07193016034271792, 0.00144213436894964], \"y\": [0.0, 0.03165121514765164, -0.0620376085559306, -0.20738773072701355, -0.32406600067145286, -0.34908211299682346, -0.4447506508762282, -0.5674556895213899, -0.6362837311985599, -0.6951754696058781, -0.7871484052382997, -0.852421549435075, -0.8641661520944619, -0.8317337186628143, -0.860385713236909, -0.9155038867928661, -0.9544675024455218, -0.964086670586411, -0.9717227238218811, -0.9698509746798276, -0.9527607378646076, -0.9394859516304519, -0.8991474884140156, -0.8350693962613787, -0.8007372633553647, -0.8241312586852637, -0.8215067502457036, -0.760269086301474, -0.6622629701319996, -0.5919581205293133, -0.5651030042903022, -0.4573367300535938, -0.3269000745607874, -0.2600576213643758, -0.16265928784606687, -0.014349302402745248, 0.08861618979424102, 0.08089189086967304, 0.040459385995435714, 0.11762049530283676, 0.2551894422090431, 0.37362917509707966, 0.40017004926580113, 0.48351536790098376, 0.6083334819835757, 0.6831253473860283, 0.7309383612140746, 0.8145610476106848, 0.8768830553258582, 0.892020771803295, 0.9015479763974531, 0.8950671862377899, 0.9172741439301518, 0.9359532280651514, 0.9336596634861829, 0.9119874836391981, 0.8905764903331215, 0.8351295200134801, 0.7614717959109387, 0.6656386264983752, 0.5943666663155686, 0.6393516075455771, 0.5365458711788814, 0.49461309103920065, 0.49291058593092774, 0.3609677328818786, 0.25745294494417853, 0.11360482941943362, 0.021108129447262005, -0.08755690316462839, -0.22924082147335217, -0.36707292523471724, -0.4883955093548818, -0.4662760787556906, -0.5190560590085607, -0.6141755340759741, -0.5817713918758334, -0.6780346187139746, -0.7599010724470061, -0.8314755153759329, -0.8830172376452343, -0.9062444319831079, -0.9319490879957549, -0.9362709797850877, -0.9204722092343778, -0.9089344885541336, -0.9175465290605623, -0.8758946956859855, -0.8803155265617457, -0.8551171677613466, -0.787500257502668, -0.7186669654409723, -0.6175782793802406, -0.5568673362428342, -0.4446145968885154, -0.31462337582645467, -0.17022943275189753, -0.056351416555296026, -0.11548654527013792, 0.0006869595190413983], \"z\": [1.0, 0.9973512029687959, 0.9823125743074373, 0.9569403645498233, 0.9363735612454356, 0.913709476818958, 0.8435177365793831, 0.7700515134505089, 0.7444763106186265, 0.6805036122176386, 0.5621162239175629, 0.4787820745529058, 0.4829803430740618, 0.5395691211810197, 0.4709832948873616, 0.3351986233958903, 0.2093308975100011, 0.16270912300767804, 0.06648366907087389, -0.08620635338515259, -0.18395879013734062, -0.23449813825727178, -0.373355534630937, -0.49090398725067574, -0.5077978900331629, -0.43019944811754807, -0.47058276014766415, -0.5897967127456779, -0.6975743398024292, -0.7374181979946572, -0.7918834119628169, -0.8741961668125147, -0.922300835796545, -0.9131655651197025, -0.9575739440631703, -0.9719318295637384, -0.9369618920088162, -0.8800584552118286, -0.900089696151439, -0.938466932937397, -0.923486995952018, -0.8615442100961646, -0.8656820028321418, -0.852149347232911, -0.7685248821860226, -0.675869894691229, -0.6273429684598586, -0.5287400724280424, -0.3964139142168856, -0.3172958064696754, -0.2509662102746327, -0.25118680303165075, -0.2041067794619525, -0.056020843764627404, 0.0846234770948025, 0.23434147577147507, 0.33903282229451226, 0.46029438025213953, 0.5846077858767575, 0.6894610483706585, 0.7778634107556538, 0.7459499408738259, 0.8143012275029557, 0.861286302808539, 0.8472054778222459, 0.9111908132906164, 0.9608995304987725, 0.9915646456121763, 0.9982928814284442, 0.9922241253427628, 0.9650769745352055, 0.9225717247484347, 0.8554057992623816, 0.841615806609331, 0.8338901924167319, 0.7487993680958006, 0.7743093469544403, 0.7082106842161507, 0.5988940201272145, 0.47723402091208394, 0.34451485246165925, 0.24278845648207958, 0.10382546024784578, -0.0359147156882087, -0.17988340827307625, -0.2739797132510336, -0.2304644272971781, -0.361014158693466, -0.38376261674395684, -0.40669725181055055, -0.5372873950229169, -0.6491672181708587, -0.7573490126697302, -0.8226744427315179, -0.889298495469782, -0.946936462332514, -0.9821517208720071, -0.9983171537898617, -0.9907012213066206, -0.9999987241686427]}]}};\n    const themeSettings = {\"highlightColor\": \"#EB6467\", \"pathColor\": \"#EB6467\"};\n    const labels = {\"xAxis\": true, \"yAxis\": true, \"zAxis\": true, \"theta\": true, \"phi\": true, \"northPole\": true, \"southPole\": true, \"nonErrorState\": false};\n\n    const wrapper = document.getElementById(\"qctrlvisualizer-wrapper-3cfa6994b0a046d4b30615207580ad62\");\n    const progressBar = document.getElementById(\"qctrlvisualizer-progress-bar-3cfa6994b0a046d4b30615207580ad62\");\n    const button = document.getElementById(\"qctrlvisualizer-button-3cfa6994b0a046d4b30615207580ad62\");\n\n    function updateButton () {\n      button.classList.remove(...[\n        \"qctrlvisualizer-button-play\",\n        \"qctrlvisualizer-button-pause\",\n        \"qctrlvisualizer-button-replay\"\n      ]);\n      if (isPlaying) {\n        button.classList.add(\"qctrlvisualizer-button-pause\");\n        button.innerHTML = \"Pause\";\n        return;\n      }\n      if (progress>=1) {\n        button.classList.add(\"qctrlvisualizer-button-replay\");\n        button.innerHTML = \"Replay\";\n        return;\n      }\n      button.classList.add(\"qctrlvisualizer-button-play\");\n      button.innerHTML = \"Play\";\n    }\n\n    button.onclick = () => {\n      isPlaying = !isPlaying;\n      if (progress >= 1) progress = 0;\n      updateButton();\n      visualizer.update({ isPlaying, progress });\n    };\n\n    progressBar.oninput = ({ target }) => {\n      progress = +target.value;\n      visualizer.update({ progress });\n      updateButton();\n    };\n\n    const onUpdate = ({ target, data }) => {\n      progress = data.progress;\n      progressBar.value = progress;\n      if (progress >= 1) {\n        isPlaying = false;\n        target.update({ isPlaying });\n        updateButton();\n      }\n    };\n\n    const visualizer = new Visualizer({\n      visualizationData,\n      wrapper,\n      onUpdate,\n      labels,\n    }).init();\n\n    visualizer.update({ themeSettings });\n     }\n\n    function displayErrorMessage() {\n      console.log(\"Failed to load https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js.\");\n      const wrapper = document.getElementById(\"qctrlvisualizer-wrapper-3cfa6994b0a046d4b30615207580ad62\");\n      wrapper.innerHTML = \"Could not load JavaScript at https://cdn.jsdelivr.net/npm/@qctrl/visualizer@3.1.14/umd/visualizer.min.js.\";\n    }\n\n    visualizerLoader();\n    ",
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "states = result[\"output\"][\"prop_states_rot_frame\"][\"value\"]\n",
    "\n",
    "n_qubit = 0  # Choose the qubit number to visualize.\n",
    "qv.display_bloch_sphere(states=states[n_qubit, :, :, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For a compact representation, we can also plot the spin up probability of the qubits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_array = np.linspace(0, duration, 100, endpoint=False)\n",
    "populations = {f\"Q{i}\": np.abs(states[i, :, 1, 0]) ** 2 for i in range(qubit_count)}\n",
    "qv.plot_population_dynamics(sample_times=time_array, populations=populations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In summary, we proposed a crosstalk model based on the nonlinear response of electrons in quantum dots to an electric driving signal. We demonstrated a resource efficient implementation in Boulder Opal and used quantum optimal control techniques to mitigate the crosstalk.\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
