diff --git a/examples/creating_a_dds.ipynb b/examples/creating_a_dds.ipynb deleted file mode 100644 index bbd0d8d7..00000000 --- a/examples/creating_a_dds.ipynb +++ /dev/null @@ -1,504 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Creating a Dynamical Decoupling Sequence\n", - "\n", - "This notebook illustrates how to use Q-CTRL Open Controls to create a [Dynamical Decoupling Sequence (DDS)](https://en.wikipedia.org/wiki/Dynamical_decoupling). \n", - "\n", - "Dynamical decoupling is the use of fast pulses, often treated as instant ideal unitary operations, on a qubit to decouple it from its environment and improve its coherence time. The train of pulses is called a sequence, hence DDS. DDS can be used to increase the coherence time of a qubit or they can be used as part of a characterization process to identify coherence time and/or noise spectra.\n", - "\n", - "Q-CTRL Open Controls can be used to create a DDS from a library of well-known dynamical decoupling schemes. Once created, it can be printed, plotted, exported in CSV or JSON format for use on a quantum computer or any of [Q-CTRL's products](https://q-ctrl.com/products/)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from qctrlopencontrols import new_predefined_dds, DynamicDecouplingSequence" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Predefined Dynamical Decoupling Schemes\n", - "\n", - "Q-CTRL Open Controls can create DDSs according to the following protocols:\n", - "\n", - "1. `Ramsey`\n", - "2. `spin echo`\n", - "3. `Carr-Purcell`\n", - "4. `Carr-Purcell-Meiboom-Gill`\n", - "5. `Uhrig`\n", - "6. `periodic`\n", - "7. `Walsh single-axis`\n", - "8. `quadratic`\n", - "9. `X concatenated`\n", - "10. `XY concatenated`\n", - "\n", - "See the [technical documentation](https://docs.q-ctrl.com/control-formats#dynamical-decoupling-sequences) for details." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Creating and Printing a Dynamical Decoupling Sequence\n", - "\n", - "A DDS is defined as a set of instant unitary operations, each defined with by a `rabi_rotation`, a `azimuthal_angle`, a `detuning_angle`, and applied at a particular time (`offset`). The mathematical definition of a sequence is explained in the [technical documentation](http://docs.q-ctrl.com/control-library#dynamical-decoupling-sequences).\n", - "\n", - "Q-CTRL Open controls can generate a DDS from a library of dynamical decoupling schemes, mathematically defined in the [technical documentation](https://docs.q-ctrl.com/control-formats#dynamical-decoupling-sequences). Below we give a few examples of generating DDSs. The schemes are grouped into cells if they have common keywords." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SE DDS:\n", - "Duration = 1e-05\n", - "Offsets = [0.5] x 1e-05\n", - "Rabi Rotations = [1.0] x pi\n", - "Azimuthal Angles = [0.0] x pi\n", - "Detuning Rotations = [0.0] x pi\n" - ] - } - ], - "source": [ - "## Spin echo sequence\n", - "se_dds = new_predefined_dds(scheme='spin echo', duration=10e-6, name='SE DDS')\n", - "print(se_dds)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CP DDS:\n", - "Duration = 1e-05\n", - "Offsets = [0.125,0.375,0.625,0.875] x 1e-05\n", - "Rabi Rotations = [1.0,1.0,1.0,1.0] x pi\n", - "Azimuthal Angles = [0.0,0.0,0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,0.0,0.0,0.0] x pi\n" - ] - } - ], - "source": [ - "## Carr-Purcell sequence\n", - "## 'Carr-Purcell-Meiboom-Gill', 'Uhrig single-axis' or 'Periodic single-axis' schemes use same keywords\n", - "cp_dds = new_predefined_dds(\n", - " scheme='Carr-Purcell', \n", - " duration=10e-6, \n", - " number_of_offsets = 4.,\n", - " name='CP DDS')\n", - "print(cp_dds)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Walsh DDS:\n", - "Duration = 1e-05\n", - "Offsets = [0.125,0.25,0.375,0.5,0.625,0.75,0.875] x 1e-05\n", - "Rabi Rotations = [1.0,1.0,1.0,1.0,1.0,1.0,1.0] x pi\n", - "Azimuthal Angles = [0.0,0.0,0.0,0.0,0.0,0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,0.0,0.0,0.0,0.0,0.0,0.0] x pi\n" - ] - } - ], - "source": [ - "## Walsh single-axis\n", - "walsh_dds = new_predefined_dds(\n", - " scheme='Walsh single-axis', \n", - " duration=10e-6, \n", - " paley_order = 4.,\n", - " name='Walsh DDS')\n", - "print(walsh_dds)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Quadratic DDS:\n", - "Duration = 1e-05\n", - "Offsets = [0.06249999999999998,0.18749999999999994,0.24999999999999994,0.37499999999999994,0.6249999999999999,0.7499999999999999,0.8124999999999999,0.9375] x 1e-05\n", - "Rabi Rotations = [0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0] x pi\n", - "Azimuthal Angles = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] x pi\n", - "Detuning Rotations = [1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0] x pi\n" - ] - } - ], - "source": [ - "## Quadratic sequence\n", - "quadratic_dds = new_predefined_dds(\n", - " scheme='quadratic', \n", - " duration=10e-6, \n", - " number_inner_offsets = 2,\n", - " number_outer_offsets = 2,\n", - " name='Quadratic DDS')\n", - "print(quadratic_dds)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "XC DDS:\n", - "Duration = 1e-05\n", - "Offsets = [0.25,0.75] x 1e-05\n", - "Rabi Rotations = [1.0,1.0] x pi\n", - "Azimuthal Angles = [0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,0.0] x pi\n" - ] - } - ], - "source": [ - "## X concatenated sequence\n", - "## 'XY concatenated' scheme uses the same keyword\n", - "xc_dds = new_predefined_dds(\n", - " scheme='X concatenated', \n", - " duration=10e-6, \n", - " concatenation_order = 2,\n", - " name='XC DDS')\n", - "print(xc_dds)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Ramsey DDS:\n", - "Duration = 1e-06\n", - "Offsets = [] x 1e-06\n", - "Rabi Rotations = [] x pi\n", - "Azimuthal Angles = [] x pi\n", - "Detuning Rotations = [] x pi\n" - ] - } - ], - "source": [ - "## Ramsay DDS\n", - "ramsey_dds = new_predefined_dds(scheme='Ramsey', duration=1e-6, name='Ramsey DDS')\n", - "print(ramsey_dds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plotting a DDS\n", - "\n", - "Once created, Q-CTRL Open Controls provides the method `get_plot_formatted_arrays` to create a set of formatted arrays ready to be immediately plotted with Matplotlib. We use the `quadratic_dds` as a sample sequence to generate plots of the `rabi_rotations`, `azimuthal_angles` and `detuning_rotations`." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0,0.5,'Detuning Rotation (rad)')" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "formatted_plot_data = quadratic_dds.get_plot_formatted_arrays()\n", - "rabi_rotations, azimuthal_angles, detuning_rotations, times = (formatted_plot_data['rabi_rotations'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detuning_rotations'],\n", - " formatted_plot_data['times'])\n", - "\n", - "# prepare the axes\n", - "figure, (rabi_plot_axis, azimuth_plot_axis, detuning_plot_axis) = plt.subplots(\n", - " 1, 3, figsize=(20,5))\n", - "rabi_plot_axis.plot(times, rabi_rotations)\n", - "rabi_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "rabi_plot_axis.set_xlabel('Time (s)')\n", - "rabi_plot_axis.set_ylabel('Rabi Rotations (rad)')\n", - "\n", - "azimuth_plot_axis.plot(times, azimuthal_angles)\n", - "azimuth_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "azimuth_plot_axis.set_xlabel('Time (s)')\n", - "azimuth_plot_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "detuning_plot_axis.plot(times, detuning_rotations)\n", - "detuning_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "detuning_plot_axis.set_xlabel('Time (s)')\n", - "detuning_plot_axis.set_ylabel('Detuning Rotation (rad)')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Exporting the Dynamical Decoupling Sequence\n", - "\n", - "Q-CTRL Open Controls enables exporting DDS in CSV or JSON format. An exported sequence is [formatted](https://docs.q-ctrl.com/control-formats) to be compatible with [Q-CTRL BLACK OPAL](https://app.q-ctrl.com).\n", - "\n", - "An ideal DDS is defined as a sequence of instantaneously-applied pulses (typically rotations around one or more of the Cartesian control axes - x,y,z). However, in reality, the rate of rotation is limited by the `maximum_rabi_rate` and/or `maximum_detuning_rate` for a given pulse. Due to this limiting factor, the target rotation is implemented over a control segment with finite duration. Q-CTRL Open Controls converts a `DynamicDecouplingSequence` into a `DrivenControl` before exporting the resulting `DrivenControl`. This conversion requires the `maximum_rabi_rate` and `maximum_detuning_rate` to be specified and raises an error if the conversion is not successful (i.e. overlapping control segments due to low `maximum_rabi_rate` or `maximum_detuning_rate` etc.).\n", - "\n", - "Q-CTRL Open Controls can export a sequence in either `cartesian` or `cylindrical` coordinates. For details, consult the [technical documentation](https://docs.q-ctrl.com/output-data-formats#q-ctrl-hardware).\n", - "\n", - "In the example below, we chose the `quadratic_dds` (created above) for exporting to a CSV file." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "file_type='CSV'\n", - "filename='example_sequence.csv'\n", - "\n", - "\n", - "quadratic_dds.export_to_file(\n", - " filename=filename, \n", - " file_type=file_type,\n", - " maximum_rabi_rate=2e6*np.pi,\n", - " maximum_detuning_rate=4e6*np.pi)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "rabi_rate,azimuthal_angle,detuning,duration,maximum_rabi_rate\n", - "\n", - "0.0,0.0,0.0,4.999999999999999e-07,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.4999999999999994e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,9.999999999999997e-07,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.4999999999999994e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,2.5000000000000015e-07,6283185.307179586\n", - "\n", - "1.0,0.0,0.0,5.000000000000003e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,8.749999999999997e-07,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.499999999999997e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,2.2500000000000005e-06,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.499999999999993e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,8.750000000000001e-07,6283185.307179586\n", - "\n", - "1.0,0.0,0.0,4.999999999999994e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,2.50000000000001e-07,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.499999999999993e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,1.0000000000000023e-06,6283185.307179586\n", - "\n", - "0.0,0.0,3.141592653589793,2.499999999999993e-07,6283185.307179586\n", - "\n", - "0.0,0.0,0.0,5.000000000000003e-07,6283185.307179586\n" - ] - } - ], - "source": [ - "## Reload the file and check its content to better understand the format\n", - "with open(filename, 'rt') as handle:\n", - " file_content = handle.readlines()\n", - "for line in file_content:\n", - " print(line)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Opening the Exported Sequence in Q-CTRL BLACK OPAL" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The exported CSV files are compatible for analysis by a suite of tools offered by [Q-CTRL BLACK OPAL](https://app.q-ctrl.com). For example, you can upload the exported file in the [1-QUBIT Workspace](https://app.q-ctrl.com/oneQubit) for further analysis. The process to upload a custom control is described in [Uploading and Evaluating Custom Controls](https://help.q-ctrl.com/black-opal/guides/uploading-and-evaluating-custom-controls). For a full capability of BLACK OPAL, consult [Q-CTRL Help](https://help.q-ctrl.com/black-opal)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Custom Definition of Dynamic Decoupling Sequence\n", - "\n", - "An arbitrary `DynamicDecouplingSequence` can be created by providing a `duration` along with arrays for the `rabi_rotations`, `azimuthal_angles`, `detuning_rotations` and offsets." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0,0.5,'Detuning Rotation (rad)')" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "_duration = 1.50\n", - "_rabi_rotations = [np.pi, np.pi, 0., np.pi, np.pi]\n", - "_azimuthal_angles = [np.pi/2, 0., 0., 0., np.pi/2]\n", - "_detuning_rotations = [0., 0., np.pi, 0., 0.]\n", - "_offsets = [0.25, 0.50, 0.75, 1.00, 1.25]\n", - "_name = 'Custom DDS'\n", - "\n", - "custom_dds = DynamicDecouplingSequence(duration=_duration,\n", - " rabi_rotations=_rabi_rotations,\n", - " azimuthal_angles=_azimuthal_angles,\n", - " detuning_rotations=_detuning_rotations,\n", - " offsets=_offsets,\n", - " name=_name)\n", - "\n", - "## let us plot and verify\n", - "formatted_plot_data = custom_dds.get_plot_formatted_arrays()\n", - "rabi_rotations, azimuthal_angles, detuning_rotations, times = (formatted_plot_data['rabi_rotations'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detuning_rotations'],\n", - " formatted_plot_data['times'])\n", - "\n", - "figure, (rabi_plot_axis, azimuth_plot_axis, detuning_plot_axis) = plt.subplots(\n", - " 1, 3, figsize=(20,5))\n", - "\n", - "rabi_plot_axis.plot(times, rabi_rotations)\n", - "rabi_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "rabi_plot_axis.set_xlim([0, _duration])\n", - "rabi_plot_axis.set_xlabel('Time (sec)')\n", - "rabi_plot_axis.set_ylabel('Rabi Rotations (rad)')\n", - "\n", - "azimuth_plot_axis.plot(times, azimuthal_angles)\n", - "azimuth_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "azimuth_plot_axis.set_xlim([0, _duration])\n", - "azimuth_plot_axis.set_xlabel('Time (sec)')\n", - "azimuth_plot_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "detuning_plot_axis.plot(times, detuning_rotations)\n", - "detuning_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "detuning_plot_axis.set_xlim([0, _duration])\n", - "detuning_plot_axis.set_xlabel('Time (sec)')\n", - "detuning_plot_axis.set_ylabel('Detuning Rotation (rad)')\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.6.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/examples/creating_a_driven_control.ipynb b/examples/creating_a_driven_control.ipynb deleted file mode 100644 index 66df69f1..00000000 --- a/examples/creating_a_driven_control.ipynb +++ /dev/null @@ -1,427 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Creating a Driven Control\n", - "\n", - "This notebook illustrates how to use Q-CTRL Open Controls to create a driven control.\n", - "\n", - "A driven control represents a continuous drive on a the transition of a qubit with a tunable detuning. The Open Controls package allows you to generate driven controls that enact dynamically corrected gates (DCG). These dynamically corrected gates are able to achieve an arbitrary rotation of the bloch sphere (around any point on the equator), in a manner that is robust to dephasing and/or control noise. DCGs can be used as drop-in gate replacements to suppress errors in a quantum computation.\n", - "\n", - "Q-CTRL Open Controls can be used to create a driven control from a library of well-known control schemes. Once created, it can be printed, plotted, exported in CSV or JSON format for use on a quantum computer or any of [Q-CTRL's products](https://q-ctrl.com/products/)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from qctrlopencontrols import new_predefined_driven_control, DrivenControl" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Predefined Driven Control Schemes\n", - "\n", - "Q-CTRL Open Controls can create driven controls according to the following dynamically corrected gate protocols:\n", - "\n", - "1. `primitive`\n", - "2. `BB1`\n", - "3. `SK1`\n", - "4. `CORPSE`\n", - "5. `WAMF1`\n", - "6. `SCROFULOUS`\n", - "7. `COPRSE in BB1`\n", - "8. `CORPSE in SK1`\n", - "9. `CORPSE in SCROFULOUS`\n", - "\n", - "See the [technical documentation](https://docs.q-ctrl.com/control-library) for details." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Creating and Printing a Driven Control\n", - "\n", - "A driven control is made of a continuous drive on the qubits transition with a tunable detuning. The continuous drive is described by a piecewise constant function made of a set of segments. Each drive segment has a `rabi_rate` applied at a `azimuthal_angle` for a `duration`, with a `detuning`. The mathematical definition of a driven control is explained in the [technical documentation](http://docs.q-ctrl.com/control-library#dynamical-decoupling-sequences).\n", - "\n", - "Q-CTRL Open controls can generate a driven control from a library of dynamically corrected gate schemes, mathematically defined in the [technical documentation](https://docs.q-ctrl.com/control-formats#dynamical-decoupling-sequences). All dynamically corrected gates are derived from three quantities: \n", - "\n", - "* `maximum_rabi_rate` the maximum achievable rabi rate.\n", - "* `rabi_rotation` the total rotation of the bloch sphere.\n", - "* `azimuthal_angle` the angle to the center point of the rotation on the equator. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Primitive X-pi:\n", - "Rabi Rates = [1.0] x 6.283185307179586\n", - "Azimuthal Angles = [0.0] x pi\n", - "Detunings = [0] x 0.0\n", - "Durations = [1.0] x 0.5\n" - ] - } - ], - "source": [ - "## Primitive Pi pulse in X\n", - "prim = new_predefined_driven_control(\n", - " rabi_rotation=np.pi,\n", - " azimuthal_angle=0,\n", - " maximum_rabi_rate=2 * np.pi,\n", - " scheme='primitive',\n", - " name='Primitive X-pi'\n", - ")\n", - "print(prim)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BB1 X-pi:\n", - "Rabi Rates = [1.0,1.0,1.0,1.0] x 6.283185307179586\n", - "Azimuthal Angles = [0.0,0.5804306232551663,1.7412918697654987,0.5804306232551663] x pi\n", - "Detunings = [0,0,0,0] x 0.0\n", - "Durations = [0.2,0.2,0.4,0.2] x 2.5\n" - ] - } - ], - "source": [ - "## BB1 Pi pulse in X (implements the same effective operation as above)\n", - "bb1_x = new_predefined_driven_control(\n", - " rabi_rotation=np.pi,\n", - " azimuthal_angle=0,\n", - " maximum_rabi_rate=2 * np.pi,\n", - " scheme='BB1',\n", - " name='BB1 X-pi'\n", - ")\n", - "print(bb1_x)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BB1 Y-pi/2:\n", - "Rabi Rates = [1.0,1.0,1.0,1.0] x 6.283185307179586\n", - "Azimuthal Angles = [0.5,1.0398930876747683,2.1196792630243046,1.0398930876747683] x pi\n", - "Detunings = [0,0,0,0] x 0.0\n", - "Durations = [0.1111111111111111,0.2222222222222222,0.4444444444444444,0.2222222222222222] x 2.25\n" - ] - } - ], - "source": [ - "## BB1 Pi/2 pulse in Y\n", - "bb1_y = new_predefined_driven_control(\n", - " rabi_rotation=np.pi/2,\n", - " azimuthal_angle=np.pi/2,\n", - " maximum_rabi_rate=2 * np.pi,\n", - " scheme='BB1',\n", - " name='BB1 Y-pi/2'\n", - ")\n", - "print(bb1_y)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SK1 Y-pi/2:\n", - "Rabi Rates = [1.0,1.0,1.0] x 6.283185307179586\n", - "Azimuthal Angles = [0.5,-0.03989308767476825,1.0398930876747683] x pi\n", - "Detunings = [0,0,0] x 0.0\n", - "Durations = [0.1111111111111111,0.4444444444444444,0.4444444444444444] x 2.25\n" - ] - } - ], - "source": [ - "## SK1 Pi/2 pulse in Y\n", - "sk1 = new_predefined_driven_control(\n", - " rabi_rotation=np.pi/2,\n", - " azimuthal_angle=np.pi/2,\n", - " maximum_rabi_rate=2 * np.pi,\n", - " scheme='SK1',\n", - " name='SK1 Y-pi/2'\n", - ")\n", - "print(sk1)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CORPSE X-pi/2:\n", - "Rabi Rates = [1.0,1.0,1.0] x 6.283185307179586\n", - "Azimuthal Angles = [0.0,1.0,0.0] x pi\n", - "Detunings = [0,0,0] x 0.0\n", - "Durations = [0.5284727158825664,0.43811717424831853,0.033410109869114954] x 2.0199465438373845\n" - ] - } - ], - "source": [ - "## CORPSE Pi/2 pulse in X\n", - "corpse = new_predefined_driven_control(\n", - " rabi_rotation=np.pi/2,\n", - " azimuthal_angle=0,\n", - " maximum_rabi_rate=2 * np.pi,\n", - " scheme='CORPSE',\n", - " name='CORPSE X-pi/2'\n", - ")\n", - "print(corpse)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plotting a driven control\n", - "\n", - "Once created, Q-CTRL Open Controls provides the method `get_plot_formatted_arrays` to create a set of formatted arrays ready to be immediately plotted with Matplotlib. We use the `BB1` as a driven control to generate plots of the `rabi_rates`, `azimuthal_angles` and `detunings`." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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G5MIz72T1OXe3HcbQrLt8IwuW9NrgTXPN+rX38e4jf9F2GEPz9Bc/hGe9dpe2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\nAPhZn8OZzbzf0TZO9ztO9wr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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "formatted_plot_data = bb1_x.get_plot_formatted_arrays(coordinates='cylindrical')\n", - "rabi_rates, azimuthal_angles, detunings, times = (formatted_plot_data['rabi_rates'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detunings'],\n", - " formatted_plot_data['times'])\n", - "# prepare the axes\n", - "figure, (x_axis, y_axis, z_axis) = plt.subplots(1, 3, figsize=(20,5))\n", - "\n", - "x_axis.fill_between(times, rabi_rates, 0, alpha=0.15, color='#680cea')\n", - "x_axis.plot(times, rabi_rates, color='#680cea')\n", - "x_axis.set_xlabel('Time (s)')\n", - "x_axis.set_ylabel('Rabi Rate (radHz)')\n", - "\n", - "y_axis.fill_between(times, azimuthal_angles, 0, alpha=0.15, color='#680cea')\n", - "y_axis.plot(times, azimuthal_angles, color='#680cea')\n", - "y_axis.set_xlabel('Time (s)')\n", - "y_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "z_axis.fill_between(times, detunings, 0, alpha=0.15, color='#680cea')\n", - "z_axis.plot(times, detunings, color='#680cea')\n", - "z_axis.set_xlabel('Time (s)')\n", - "z_axis.set_ylabel('Detuning (radHz)')\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Exporting the Driven Control\n", - "\n", - "Q-CTRL Open Controls enables exporting driven controls in CSV or JSON format. An exported driven control is [formatted](https://docs.q-ctrl.com/control-formats) to be compatible with [Q-CTRL BLACK OPAL](https://app.q-ctrl.com).\n", - "\n", - "Q-CTRL Open Controls can export a driven control in either `cartesian` or `cylindrical` coordinates. For details, consult the [technical documentation](https://docs.q-ctrl.com/output-data-formats#q-ctrl-hardware).\n", - "\n", - "In the example below, we chose the `bb1_x` control (created above) for exporting to a CSV file." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "file_type='CSV'\n", - "filename='example_driven_control.csv'\n", - "\n", - "bb1_x.export_to_file(\n", - " filename=filename, \n", - " file_type=file_type,\n", - " coordinates='cartesian')" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "amplitude_x,amplitude_y,detuning,duration,maximum_rabi_rate\n", - "\n", - "6.283185307179586,0.0,0.0,0.5,6.283185307179586\n", - "\n", - "-1.570796326794896,6.083668013960418,0.0,0.5,6.283185307179586\n", - "\n", - "4.319689898685962,-4.562751010470316,0.0,1.0,6.283185307179586\n", - "\n", - "-1.570796326794896,6.083668013960418,0.0,0.5,6.283185307179586\n" - ] - } - ], - "source": [ - "## Reload the file and check its content to better understand the format\n", - "with open(filename, 'rt') as handle:\n", - " file_content = handle.readlines()\n", - "for line in file_content:\n", - " print(line)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Opening the Exported Sequence in Q-CTRL BLACK OPAL" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The exported CSV files are compatible for analysis by a suite of tools offered by [Q-CTRL BLACK OPAL](https://app.q-ctrl.com). For example, you can upload the exported file in the [1-QUBIT Workspace](https://app.q-ctrl.com/oneQubit) for further analysis. The process to upload a custom control is described in [Uploading and Evaluating Custom Controls](https://help.q-ctrl.com/black-opal/guides/uploading-and-evaluating-custom-controls). For a full capability of BLACK OPAL, consult [Q-CTRL Help](https://help.q-ctrl.com/black-opal)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Custom Definition of a Driven Control\n", - "\n", - "An arbitrary `DrivenControl` can be defined defined using arrays of `rabi_rotations`, `azimuthal_angles`, `detuning_rotations` and `durations`." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "_rabi_rates = [np.pi/2,np.pi/2,np.pi,np.pi]\n", - "_azimuthal_angles = [0., -np.pi/2, 0., np.pi/2]\n", - "_detunings = [np.pi/2, 0, -np.pi/2, 0]\n", - "_durations = [0.5, 1, 2, 0.5]\n", - "_name = 'Custon Driven Control'\n", - "\n", - "custom_driven_control = DrivenControl(rabi_rates=_rabi_rates, \n", - " azimuthal_angles=_azimuthal_angles,\n", - " detunings=_detunings,\n", - " durations=_durations,\n", - " name=_name)\n", - "\n", - "## let us plot and verify\n", - "formatted_plot_data = custom_driven_control.get_plot_formatted_arrays(coordinates='cylindrical')\n", - "rabi_rates, azimuthal_angles, detunings, times = (formatted_plot_data['rabi_rates'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detunings'],\n", - " formatted_plot_data['times'])\n", - "\n", - "figure, (x_axis, y_axis, z_axis) = plt.subplots(1, 3, figsize=(20,5))\n", - "\n", - "x_axis.fill_between(times, rabi_rates, 0, alpha=0.15, color='#680cea')\n", - "x_axis.plot(times, rabi_rates, color='#680cea')\n", - "x_axis.set_xlabel('Time (s)')\n", - "x_axis.set_ylabel('Rabi Rate (radHz)')\n", - "\n", - "y_axis.fill_between(times, azimuthal_angles, 0, alpha=0.15, color='#680cea')\n", - "y_axis.plot(times, azimuthal_angles, color='#680cea')\n", - "y_axis.set_xlabel('Time (s)')\n", - "y_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "z_axis.fill_between(times, detunings, 0, alpha=0.15, color='#680cea')\n", - "z_axis.plot(times, detunings, color='#680cea')\n", - "z_axis.set_xlabel('Time (s)')\n", - "z_axis.set_ylabel('Detuning (radHz)')\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": "3.6.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/examples/export_a_dds_to_cirq.ipynb b/examples/export_a_dds_to_cirq.ipynb deleted file mode 100644 index 71f908ad..00000000 --- a/examples/export_a_dds_to_cirq.ipynb +++ /dev/null @@ -1,362 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Export a Dynamical Decoupling Sequence to Cirq\n", - "\n", - "Q-CTRL Open Controls provides easy-to-use methods to construct Dynamical Decoupling Sequences (DDS) according to well-known dynamical decoupling schemes. This is described in the [creating a DDS notebook](creating_a_dds.ipynb). Here we show how a DDS from Q-CTRL Open Controls can be exported as `cirq.Circuit` or `cirq.Schedule` and run in `cirq.Simulator`.\n", - "\n", - "Note : You can install `cirq` by simply running `pip install cirq`. Please consult [Cirq Documentation](https://cirq.readthedocs.io/en/stable/) for installation instruction and general introduction to `cirq` package." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "#General\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.gridspec import GridSpec\n", - "\n", - "#Q-CTRL Open Controls\n", - "from qctrlopencontrols import new_predefined_dds, convert_dds_to_cirq_circuit, convert_dds_to_cirq_schedule\n", - "\n", - "#Cirq : to run the circuit on simulator\n", - "import cirq" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Running a DDS on a Cirq Simulator\n", - "\n", - "This section demonstrates how a DDS can be prepared, a corresponding quantum circuit made and executed on a `cirq` simulator.\n", - "\n", - "Q-CTRL Open Controls defines a DDS as a set of instantaneous unitary operations performed at specific offset times, see the [technical documentation](https://docs.q-ctrl.com/control-library#dynamical-decoupling-sequences) for mathematical details.\n", - "\n", - "`cirq` implements quantum operations through a series of [gates](https://cirq.readthedocs.io/en/stable/gates.html). Standard way to create a circuit is through `cirq.Circuit` that accepts a list of valid gates. If a user wants to add pauses (in time) during a computation they can use identity gates. Alternatively, `cirq` provides `ScheduledOperation` that specifies an operation (application of a gate on one more qubits) at a certain instant measured in \"nano-seconds\" or \"pico-seconds\" from the start of the sequence. A list of `ScheduledOperation` is collated by `cirq.Schedule`. Both `cirq.Circuit` and `cirq.Schedule` can be used in `cirq.Simulator` to simulate the circuit. We provide two methods -`convert_dds_to_cirq_circuit` and `covert_dds_to_cirq_schedule` to select between `cirq.Circuit` and `cirq.Schedule` as desired output from the conversion method.\n", - "\n", - "Converting a DDS into a `cirq.Circuit` or `cirq.Schedule` is an approximate process where the instantaneous unitaries are replaced with finite duration gates. Moreover, in `cirq.Circuit`, the pauses in-between unitaries are replaced with the closest integer number of identity gates. The exact algorithm used to make this approximation is documented in the [source code](../qctrlopencontrols/cirq/cirq_circuit.py).\n", - "\n", - "In this example we will define a Quadratic DDS and convert it into a circuit that we can later run on a simulator. Note that we add a $X_{\\pi/2}$ rotation at both ends of the sequence. See [creating_a_dds.ipynb](creating_a_dds.ipynb) to see how other sequences can be created." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Preparing the Sequences" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Quadratic sequence:\n", - "Duration = 2e-05\n", - "Offsets = [0.0,0.06249999999999998,0.18749999999999994,0.24999999999999994,0.37499999999999994,0.6249999999999999,0.7499999999999999,0.8124999999999999,0.9375,1.0] x 2e-05\n", - "Rabi Rotations = [0.5,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.5] x pi\n", - "Azimuthal Angles = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0] x pi\n" - ] - } - ], - "source": [ - "## Quadratic sequence, total duration: 20us\n", - "quadratic_sequence = new_predefined_dds(\n", - " scheme='quadratic',\n", - " duration=20e-6, \n", - " number_inner_offsets=2,\n", - " number_outer_offsets=2,\n", - " pre_post_rotation=True,\n", - " name='Quadratic sequence')\n", - "print(quadratic_sequence)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Constructing the Circuit Using Q-CTRL Open Controls\n", - "\n", - "To construct a circuit/schedule from a DDS, we need to provide the DDS (`dynamic_decoupling_sequence`). You can also provide a list of target qubits (each of `cirq.Qid` type) to indicate qubits on which the DDS will be applied. `gate_time` is the delay (in seconds) introduced by each of the gates. If measurement is required, use `add_measurement=True`.\n", - "\n", - "See the [source code](../qctrlopencontrols/cirq/cirq_circuit.py) for more information and other parameters that may be useful.\n", - "\n", - "In this example, we will use a single qubit on 1-D lattice. We specify the `gate_time` to be $0.4$ $\\mu$s. Finally we will add a measurement operation. In this example we will convert the DDS into a `cirq.Circuit`." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "## Prepare the conversion related parameters\n", - "'''\n", - "target_qubits : list\n", - " A list of cirq.Qid. In this case we are using a single\n", - " qubit (indexed 0) on 1-D lattice.\n", - "'''\n", - "target_qubits = [cirq.LineQubit(0)]\n", - "\n", - "\n", - "'''\n", - "gate_time : float\n", - " Time delay (in seconds) introduced by identity gate\n", - "'''\n", - "gate_time = 0.4e-6\n", - "\n", - "'''\n", - "add_measurement : bool\n", - " Indicates if the circuit requires a measurement step.\n", - " Required for 'qasm_simulator' and real device backends\n", - "'''\n", - "add_measurement = True\n", - "\n", - "## convert the quadratic sequence to cirq.Circuit\n", - "quadratic_cirq_circuit = convert_dds_to_cirq_circuit(\n", - " dynamic_decoupling_sequence=quadratic_sequence,\n", - " target_qubits=target_qubits,\n", - " gate_time=gate_time,\n", - " add_measurement=add_measurement\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plotting the DDS\n", - "\n", - "We can use Q-CTRL Open Controls to plot the DDS for comparison against its `cirq.Circuit` approximations." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "formatted_plot_data = quadratic_sequence.get_plot_formatted_arrays()\n", - "rabi_rotations, azimuthal_angles, detuning_rotations, times = (\n", - " formatted_plot_data['rabi_rotations'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detuning_rotations'],\n", - " formatted_plot_data['times']\n", - ")\n", - "\n", - "# prepare the axes\n", - "figure, (rabi_plot_axis, azimuth_plot_axis, detuning_plot_axis) = plt.subplots(\n", - " 3, 1, figsize=(20,5))\n", - "\n", - "rabi_plot_axis.plot(times, rabi_rotations)\n", - "rabi_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "rabi_plot_axis.set_xlabel('Time (sec)')\n", - "rabi_plot_axis.set_ylabel('Rabi Rotations (rad)')\n", - "\n", - "azimuth_plot_axis.plot(times, azimuthal_angles)\n", - "azimuth_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "azimuth_plot_axis.set_xlabel('Time (sec)')\n", - "azimuth_plot_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "detuning_plot_axis.plot(times, detuning_rotations)\n", - "detuning_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "detuning_plot_axis.set_xlabel('Time (sec)')\n", - "detuning_plot_axis.set_ylabel('Detuning Rotation (rad)')\n", - "\n", - "plt.suptitle('Quadratic Sequence')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Drawing the Circuit\n", - "\n", - "We can draw a text diagram of the `cirq.Circuit` generated by Q-CTRL Open Controls.\n", - "\n", - "Note that a $X_{\\pi/2}$ rotation will be added at beginning and end, that is, at offsets of $[0, 20]$ $\\mu$s, to create the desired superposition state. The $X_{\\pi/2}$ rotations are implemented using $Rx($0.5\\pi$)$ gate.\n", - "\n", - "The $Rz(\\pi)$ gates are $Z_\\pi$ pulses (a $\\pi$ rotation around $Z$-axis) and $Rx(\\pi)$ gates correspond to $X_{\\pi}$ pulses (a $\\pi$ rotation around $X$-axis). The gates match the pulses in the DDS.\n", - "\n", - "The `I` in the drawing corresponds to the `identity` gate. In the DDS, the first $Z_{\\pi}$-pulse is applied at a delay of $1.25$ $\\mu$s. This is approximated by introducing 3-`Id` gates with a delay of $0.4\\times 3=1.2$ $\\mu s$. Similarly, the second set of 6 Id gates introduces a delay of 2.4$\\mu s$ close to the actual delay of $3.75−1.25=2.50\\mu s$.\n", - "\n", - "At the end of the circuit, we placed a `measurement` ($M$) operator to read out the result." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0: ─Rx(0.5π)─I─I─I─Rz(π)─I─I─I─I─I─I─Rz(π)─I─I─I─Rx(π)─I─I─I─I─I─I─Rz(π)─I─I─I─I─I─I─I─I─I─I─I─I─Rz(π)─I─I─I─I─I─I─Rx(π)─I─I─I─Rz(π)─I─I─I─I─I─I─Rz(π)─I─I─I─Rx(0.5π)─M('qubit-0')─\n" - ] - } - ], - "source": [ - "##Drawing the Quadratic Circuit\n", - "print(quadratic_cirq_circuit.to_text_diagram_drawer().render())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the Circuit on Cirq Simulator using Cirq API\n", - "\n", - "Consult [Simulation](https://cirq.readthedocs.io/en/stable/simulation.html) for a description of available simulation APIs and their properties. Here, we will use the `run` method of `cirq.Simulator` to run the circuit. The circuit is run upto `repetitions` times. The result is printed after the simulation." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "qubit-0=1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n", - "Counter({1: 100})\n" - ] - } - ], - "source": [ - "##### Set the simulator parameters\n", - "'''\n", - "repetitions : int\n", - " The number of times the circuit will be executed\n", - "'''\n", - "repetitions = 100\n", - "\n", - "## Create the simulator\n", - "simulator = cirq.Simulator()\n", - "\n", - "#Run the simulator and collect result\n", - "result = simulator.run(quadratic_cirq_circuit, repetitions=repetitions)\n", - "\n", - "#print the outcome of each repetition\n", - "print(result)\n", - "\n", - "#you can also collect the outcome as histogram (calculated as dict)\n", - "print(result.histogram(key=['qubit-0']))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Creating a Schedule and running on Cirq Simulator\n", - "\n", - "We can create a `cirq.Schedule` from the DDS using `convert_dds_to_cirq_schedule` method." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "qubit-0=1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n", - "Counter({1: 100})\n" - ] - } - ], - "source": [ - "## convert the quadratic sequence to cirq.Schedule\n", - "quadratic_cirq_circuit = convert_dds_to_cirq_schedule(\n", - " dynamic_decoupling_sequence=quadratic_sequence,\n", - " target_qubits=target_qubits,\n", - " gate_time=gate_time,\n", - " add_measurement=add_measurement\n", - ")\n", - "\n", - "##### Set the simulator parameters\n", - "'''\n", - "repetitions : int\n", - " The number of times the circuit will be executed\n", - "'''\n", - "repetitions = 100\n", - "\n", - "## Create the simulator\n", - "simulator = cirq.Simulator()\n", - "\n", - "#Run the simulator and collect result\n", - "result = simulator.run(quadratic_cirq_circuit, repetitions=repetitions)\n", - "\n", - "#print the outcome of each repetition\n", - "print(result)\n", - "\n", - "#you can also collect the outcome as histogram (calculated as dict)\n", - "print(result.histogram(key=['qubit-0']))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.6.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/examples/export_a_dds_to_qiskit.ipynb b/examples/export_a_dds_to_qiskit.ipynb deleted file mode 100755 index 7b07491a..00000000 --- a/examples/export_a_dds_to_qiskit.ipynb +++ /dev/null @@ -1,769 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Export a Dynamical Decoupling Sequence to Qiskit\n", - "\n", - "Q-CTRL Open Controls provides easy-to-use methods to construct Dynamical Decoupling Sequences (DDS) according to well-known dynamical decoupling schemes. This is described in the [creating a DDS notebook](creating_a_dds.ipynb). Here we show how a DDS from Q-CTRL Open Controls can be exported to a Qiskit circuit to run on an IBM Q device. We also show how a DDS can decrease the number of errors, when executing a quantum circuit on a real quantum computer, by extending the coherence time.\n", - "\n", - "Note: To run the DDS on a real device, you need to have an IBM Q account and acquire an API token. [Sign Up](https://quantumexperience.ng.bluemix.net/qx/login) if you have not already done so. Additionally, you will need to have the Qiskit library installed. Consult [Installing Qiskit](https://qiskit.org/documentation/install.html) for more information." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "#General\n", - "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.gridspec import GridSpec\n", - "\n", - "#Q-CTRL Open Controls\n", - "from qctrlopencontrols import new_predefined_dds, convert_dds_to_qiskit_quantum_circuit\n", - "\n", - "#Qiskit\n", - "##To define a backend (simulated or real)\n", - "from qiskit import execute, BasicAer\n", - "\n", - "##To plot the outcome\n", - "from qiskit.tools.visualization import plot_histogram\n", - "\n", - "## To handle account information,find a suitable device and monitor a job\n", - "from qiskit import IBMQ\n", - "from qiskit.providers.ibmq import least_busy\n", - "from qiskit.tools.monitor import job_monitor" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Running a DDS on a Qiskit Simulator\n", - "\n", - "This section demonstrates how a DDS can be prepared and a corresponding Qiskit circuit made and executed on a Qiskit simulator.\n", - "\n", - "Q-CTRL Open Controls defines a DDS as a set of instantaneous unitary operations performed at specific offset times, see the [technical documentation](https://docs.q-ctrl.com/control-library#dynamical-decoupling-sequences) for mathematical details.\n", - "\n", - "Qiskit implements quantum computation through a series of [gates in a quantum circuit](https://qiskit.org/documentation/getting_started.html#circuit-basics). How these gates are physically implemented will depend on the device that it is run on.\n", - "\n", - "On IBM Q devices, individual qubit rotations are completed using two basis elements. $Z$ rotations are performed with (almost) instantaneous clock shifts and $Y$ rotations are performed with microwave pulses over a fixed time. All single qubit gates are a combination of these two.\n", - "\n", - "If a user wants to add pauses (in time) during a computation they can use identity gates and barriers. The barriers ensure that the circuit is not simplified before execution on the machine. Both identity gates and $X$ or $Y$ rotation gates take a fixed time (`gate_time`).\n", - "\n", - "Converting a DDS into a Qiskit circuit is an approximate process where the instantaneous unitaries are replaced with finite duration gates and the pauses in-between unitaries are replaced with the closest integer number of identity gates. The exact algorithm used to make this approximation is documented in the [source code](https://github.com/qctrl/python-open-controls/blob/master/qctrlopencontrols/qiskit/quantum_circuit.py).\n", - "\n", - "In this example we will define a Quadratic DDS and convert it into a circuit that we can later run on a simulator and on a real device. See [creating_a_DDS.ipynb](creating_a_DDS.ipynb) to see how other sequences can be created. We also create a Ramsey DDS of the same duration to compare as a benchmark. For both the sequences, we add a $X_{\\pi/2}$ rotation on either end of the sequence." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Preparing the Sequences" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Quadratic sequence:\n", - "Duration = 2e-05\n", - "Offsets = [0.0,0.06249999999999998,0.18749999999999994,0.24999999999999994,0.37499999999999994,0.6249999999999999,0.7499999999999999,0.8124999999999999,0.9375,1.0] x 2e-05\n", - "Rabi Rotations = [0.5,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.5] x pi\n", - "Azimuthal Angles = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0] x pi\n", - "Ramsey sequence:\n", - "Duration = 2e-05\n", - "Offsets = [0.0,1.0] x 2e-05\n", - "Rabi Rotations = [0.5,0.5] x pi\n", - "Azimuthal Angles = [0.0,0.0] x pi\n", - "Detuning Rotations = [0.0,0.0] x pi\n" - ] - } - ], - "source": [ - "## Quadratic sequence, total duration: 20us\n", - "quadratic_sequence = new_predefined_dds(\n", - " scheme='quadratic',\n", - " duration=20e-6, \n", - " number_inner_offsets=2,\n", - " number_outer_offsets=2,\n", - " pre_post_rotation=True,\n", - " name='Quadratic sequence')\n", - "\n", - "# Ramsey sequence, total duration: 20us\n", - "ramsey_sequence = new_predefined_dds(\n", - " scheme='Ramsey',\n", - " duration=20e-6,\n", - " pre_post_rotation=True,\n", - " name='Ramsey sequence')\n", - "\n", - "print(quadratic_sequence)\n", - "print(ramsey_sequence)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Constructing the Circuit Using Q-CTRL Open Controls\n", - "\n", - "To construct a `QuantumCircuit` from a DDS, we need to provide the DDS (`dynamic_decoupling_sequence`). You can also provide a list (`target_qubits`) to indicate qubit indices on which the DDS will be applied. `gate_time` is the delay (in seconds) introduced by each of the `identity` gates. If measurement is required, use `add_measurement=True`. Optionally you can provide a name to the circuit (`circuit_name`).\n", - "\n", - "See the [source code](https://github.com/qctrl/python-open-controls/blob/master/qctrlopencontrols/qiskit/quantum_circuit.py) for more information and other parameters that may be useful.\n", - "\n", - "In this example, we will use $0$th qubit and specify the `gate_time` to be $0.4$ $\\mu$s. Both the DDS will require a measurement operation." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "## Prepare the Qiskit related parameters\n", - "'''\n", - "target_qubits : list\n", - " A list of integers specifying the target qubits within the set of qubit registers\n", - "'''\n", - "target_qubits = [0]\n", - "\n", - "'''\n", - "gate_time : float\n", - " Time delay (in seconds) introduced by identity gate\n", - "'''\n", - "gate_time = 0.4e-6\n", - "\n", - "'''\n", - "add_measurement : bool\n", - " Indicates if the circuit requires a measurement step.\n", - " Required for 'qasm_simulator' and real device backends\n", - "'''\n", - "add_measurement = True\n", - "\n", - "'''\n", - "circuit_name : str\n", - " An optional string as a name to the circuit\n", - "'''\n", - "circuit_name = 'quadratic-sequence-circuit'\n", - "\n", - "## convert the quadratic sequence to QuantumCircuit\n", - "\n", - "quadratic_quantum_circuit = convert_dds_to_qiskit_quantum_circuit(\n", - " dynamic_decoupling_sequence=quadratic_sequence,\n", - " target_qubits=target_qubits,\n", - " gate_time=gate_time,\n", - " add_measurement=add_measurement,\n", - " circuit_name=circuit_name\n", - ")\n", - "\n", - "## convert the ramsey sequence to QuantumCircuit\n", - "circuit_name = 'ramsey-sequence-circuit'\n", - "ramsey_quantum_circuit = convert_dds_to_qiskit_quantum_circuit(\n", - " dynamic_decoupling_sequence=ramsey_sequence,\n", - " target_qubits=target_qubits,\n", - " gate_time=gate_time,\n", - " add_measurement=add_measurement,\n", - " circuit_name=circuit_name\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plotting the DDS\n", - "\n", - "We can use Q-CTRL Open Controls to plot the DDS for comparison against their Qiskit circuit approximations." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "formatted_plot_data = quadratic_sequence.get_plot_formatted_arrays()\n", - "rabi_rotations, azimuthal_angles, detuning_rotations, times = (\n", - " formatted_plot_data['rabi_rotations'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detuning_rotations'],\n", - " formatted_plot_data['times']\n", - ")\n", - "\n", - "# prepare the axes\n", - "figure, (rabi_plot_axis, azimuth_plot_axis, detuning_plot_axis) = plt.subplots(\n", - " 3, 1, figsize=(20,5))\n", - "\n", - "rabi_plot_axis.plot(times, rabi_rotations)\n", - "rabi_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "rabi_plot_axis.set_xlabel('Time (sec)')\n", - "rabi_plot_axis.set_ylabel('Rabi Rotations (rad)')\n", - "\n", - "azimuth_plot_axis.plot(times, azimuthal_angles)\n", - "azimuth_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "azimuth_plot_axis.set_xlabel('Time (sec)')\n", - "azimuth_plot_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "detuning_plot_axis.plot(times, detuning_rotations)\n", - "detuning_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "detuning_plot_axis.set_xlabel('Time (sec)')\n", - "detuning_plot_axis.set_ylabel('Detuning Rotation (rad)')\n", - "\n", - "plt.suptitle('Quadratic Sequence')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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GleQuoFa0v6o2GmIcSdIM4IgkSRIASUaSvD7Je5Ick2TfJJtM07F3T3JVkqVJDh9n/3pJPtvs/16SeU37bkkuTPLD5udzpyOPJKmdqtqwKRZ9EDgc2BKYAxwGfGA6zuE1QpJmFwtJkrSGS/JXSS4CjgA2AK4CbgJ2Bs5KcmKSuVM4/trAccAe9BZo3T/J/DHdXgXcVlVPBN4PvLtpvxnYs6r+EDgIOGlVc0iSpmSvqvpIVd1VVXdW1UeBBVM9qNcISZp9nNomSXo48Kyqume8nUmeBmwD/GwVj78jsLSqrmmOdwq9Lx9X9PVZABzdvP888OEkqaqL+/pcDmyQZL2qum8Vs0iSVs3dSV4BnEJvqtv+wN3TcFyvEZI0yzgiSZLWcFV13IqKSM3+S6rqm1M4xZbAdX3by5q2cftU1f3AHcCjxvR5KXDReF8QkixMsiTJkuXLl08hqiRpBV4O7Av8vHnt07RN1cCvEeB1QpKmU+sRSc06GY8D7gF+WlUPDiyVJGlokvzbRPur6u+GlWVFkmxHbyrD88fbX1WLgEUAIyMjK1wUVpK0aqrqp0zDVLZBmOwaAV4nJGk6TVhISvJI4LX0hq4+DFgOrA88Jsn5wEeq6uyBp5QkDdKFzc9n0Vuf4rPN9j48dGrBqroe2Kpve07TNl6fZUnWAR4J3AKQZA7wJeAvq+p/pyGPJGklJVmf3lpF29H7PgBAVb1yiof2GiFJs8xkU9s+T28Y6Z9W1ZOqaueqGqmqrYB3AQuSvGrgKSVJA1NVJ1bVicD2wC5V9aGq+hCwK/C0aTjFBcA2SbZO8jBgP2DxmD6L6S2UCrA38N9VVUk2Br4GHF5V/zMNWSRJq+Yk4LHAC4Bz6RV87pqG43qNkKRZZsIRSVW12wT7LuS3d7ElSbPfJsBGwK3N9iOatimpqvuTvA44HVgbOL6qLk9yDLCkqhYDnwJOSrK0Of9+zcdfBzwRODLJkU3b86vqpqnmkiStlCdW1T5JFlTViUn+E/jWVA/qNUKSZp/JprY9Y6L9VXXR9MaRJHXoXcDFSc4GAjyb3z4lZ0qq6jTgtDFtR/a9v5feVLqxn3sH8I7pyCBJmpJfNz9vT/IU4Ebg0dNxYK8RkjS7TLbY9nubn+sDI8AP6H252B5YAvzx4KJJkoapqv49ydeBnZqmw6rqxi4zSZJmjEXNw3feRm+q2SOAf+w2kiSpC5NNbXsOQJIvAs+oqh82209hmu5SS5JmlPuAG+jdQNg2ybZVdV7HmSRJHUqyFnBnVd0GnAf8fseRJEkdmmxE0qgnjRaRAKrqsiR/MKBMkqQOJDkEOJTeAqqXAM8Evgs8t8tckqRuVdWDSd4MfK7rLJKk7k321LZRlyb5ZJJdmtcngEsHGUySNHSHAjsA1zYjUp8O3N5tJEnSDHFWkjcm2SrJpqOvrkNJkoav7YikvwL+ht6XDOgNaf3oQBJJkrpyb1Xdm4Qk61XVlUme1HUoSdKM8LLm52v72gqnuUnSGqdVIal5UsL7m5ckafW0LMnGwKnAmUluA67tOJMkaQaoqq27ziBJmhlaTW1Lsk2Szye5Isk1o69JPnN8kpuSXLaC/Unyb0mWJrk0yTNW5ReQJE2PqvqLqrq9qo6m9ySeTwEv7jaVJKlLSXaeZP9GzYN4JElriLZT2/4dOIreiKTn0JvqNlkR6gTgw8CnV7B/D2Cb5rUTvalyO62gryRpgJKsDVxeVU8GqKpzO44kSZoZXprkX4BvABcCy+k92fOJ9L4XPB74h+7iSZKGrW0haYOq+maSVNW1wNFJLgSOXNEHquq8JPMmOOYC4NNVVcD5STZOskVV3dA2vCRpelTVA0muSjK3qn7WdR5J0sxQVa9vFtV+KbAPsAVwD/Aj4ONV9e0u80mShq9tIem+JGsBVyd5HXA98IgpnntL4Lq+7WVNm4UkSerGJsDlSb4P3D3aWFV7dRdJktS1qroV+ETzkiSt4doWkg4FHg78HXAsvWGsBw0q1FhJFgILAebOnTus00rSmuYfuw4gSZIkaWabtJDUrJvxsqp6I/ALeusjTYfrga36tuc0bb+jqhYBiwBGRkZqms4vSaL38IPqWeG6SKN9hplLkiRJ0swz6VPbquoBYMKnNayixcBfNk9veyZwh+sjSVInzk7yt0keMuQzycOSPDfJiQxxFKokSZKkmavt1LaLkywG/ouHrpvxxRV9IMnJwC7AZkmW0Xvq27rN5z4GnAa8EFgK/JLpG+kkSVo5uwOvBE5OsjVwO7ABvZsNZwAfqKqLO8wnSZoBkvwJMI++7xBVtaInNEuSVlNtC0nrA7cAz+1rK2CFhaSq2n+iAzZTJF7b8vySpAGpqnuBjwAfSbIusBlwT1Xd3m0ySdJMkeQk4AnAJcADTXMBFpIkaQ3TqpBUVY4WkqQ1QFX9Gp+eKUn6XSPAfNfLkyRNuEZSkrcl2XSC/c9N8qLpjyVJkiRpBrkMeGzXISRJ3ZtsRNIPga8kuRe4CFhOb5rbNsDTgLOAfx5oQkmSJEld2wy4Isn3gftGG6tqr+4iSZK6MGEhqaq+DHw5yTbAs4AtgDuBzwALq+qewUeUJA1LkscD21TVWUk2ANapqru6ziVJ6tzRXQeQJM0MbddIuhq4esBZJEkdSvJqYCGwKb0FVecAHwN27TKXJKl7VXVukscAOzRN36+qm7rMJEnqxoRrJEmS1iivpTf69E74zU2ER3eaSJI0IyTZF/g+sA+wL/C9JHt3m0qS1IVWI5IkSWuE+6rqV0kASLIOvUc7S5L0VmCH0VFISTant17q5ztNJUkaOkckSZJGnZvkLcAGSXYD/gv4SseZJEkzw1pjprLdgt8lJGmN1Oof/yT/kmSjJOsm+WaS5UkOGHQ4SdJQHU7v6Zw/BP4aOA14W6eJJEkzxTeSnJ7k4CQHA1+jd52QJK1h2k5te35VvTnJXwA/BV4CnEfv6W2SpNVAVT0IfKJ5SZL0G1X1piQvpbeWHsCiqvpSl5kkSd1oW0ga7ffnwH9V1R2ja2hIkma3JD9kgrWQqmr7IcaRJM1QVfUF4Atd55AkdattIemrSa4E7gH+pllc797BxZIkDdGLug4gSZqZkny7qnZOchcPvekQoKpqo46iSZI60qqQVFWHJ/kX4I6qeiDJ3cCCwUaTJA1DVV3bdQZJ0sxUVTs3PzfsOoskaWZoOyIJ4MnAvOZx0KM+Pc15JEkdGeduM8AdwBLgH6rqmuGnkiTNBElOqqoDJ2uTJK3+WhWSkpwEPAG4BHigaS4sJEnS6uQDwDLgP+lNWdiP3r/9FwHHA7t0lkyS1LXt+jeam8t/1FEWSVKH2o5IGgHmV9UKF2OVJM16e1XVU/u2FyW5pKoOS/KWzlJJkjqT5AjgLcAGSe4cbQZ+BSzqLJgkqTNrtex3GfDYQQaRJHXul0n2TbJW89qX3z5YwRsJkrQGqqp3NusjvaeqNmpeG1bVo6rqiK7zSZKGr+2IpM2AK5J8H7hvtLGq9hpIKklSF14BfBD4CL3C0fnAAUk2AF7XZTBJUreq6ogkmwDbAOv3tZ/XXSpJUhfaFpKOHmQISVL3msW091zB7m8PM4skaWZJcghwKDCH3rqpzwS+Czy3y1ySpOFrVUiqqnOTPAbYoWn6flXdNLhYkqRhS7I58GpgHn3Xh6p6ZVeZJEkzxqH0vgucX1XPSfJk4J87ziRJ6kDbp7btC7wHOIfe4nofSvKmqvr8ALNJkobry8C3gLP47RM6JUkCuLeq7k1CkvWq6sokT+o6lCRp+NpObXsrsMPoKKTmrvVZgIUkSVp9PLyqDus6hCRpRlqWZGPgVODMJLcB13acSZLUgbaFpLXGTGW7hfZPfJMkzQ5fTfLCqjqt6yCSpJmlqv6ieXt0krOBRwJf7zCSJKkjbYtB30hyepKDkxwMfA2Y9ItGkt2TXJVkaZLDx9k/N8nZSS5OcmmSF65cfEnSNDqUXjHpniR3JrkryZ1dh5IkdS/JSaPvq+rcqloMHN9hJElSR9outv2mJC8FntU0LaqqL030mSRrA8cBuwHLgAuSLK6qK/q6vQ34XFV9NMl8esWpeSv5O0iSpkFVbdh1BknSjLVd/0bzf/0/6iiLJKlDraenVdUXquoNzWvCIlJjR2BpVV1TVb8CTgEWjD0ssFHz/pHA/7XNI0kanCRPSPK2JJdP0/EmG6G6XpLPNvu/l2Re374jmvarkrxgOvJIktpp/g2+C9i+b7TqXcBN9B7SMF3n8TohSbPEhIWkJN9uft7VXDjuTPvpDlsC1/VtL2va+h0NHJBkGb3RSH+7UuklSdMmyeOSvCHJBcDlwNrAftNw3NERqnsA84H9m1Go/V4F3FZVTwTeD7y7+ez8JsN2wO7AR5rjSZKGoKre2YxYfU9VbVRVGzavR1XVEdNxDq8TkjS7TFhIqqqdm58bNheOjfouIBtN9NmW9gdOqKo5wAuBk5L8TqYkC5MsSbJk+fLl03BaSdKo5t/Ys4FzgE3p/Wf9hqp6e1X9cBpO0WaE6gLgxOb954Fdk6RpP6Wq7quqnwBLm+NJkoaoqo5IsleSf21eL5rGw3udkKRZpNUaSUlOqqoDJ2sb43pgq77tOU1bv1fRu3NAVX03yfrAZvSGyv5GVS0CFgGMjIxUm8ySpNY+DHwXeHlVLQFIMp3/1o43QnWnFfWpqvuT3AE8qmk/f8xnx45unRZv/8rlXPF/ri0uaWab/7iNOGrP7SbvOM2SvJNegeY/mqZDk/xJVb1lGg7vdUKSpskwrhNt10gau7jeOky+uN4FwDZJtk7yMHpDTheP6fMzYNfmmH8ArA845EiShmsL4GTgvc36EscC63acaaU4clWSBu7Pgd2q6viqOp7ezeDpHJU0UF4nJGn6TDgiKckRwFuADfrWRArwK5oRQivS3Cl4HXA6vXU2jq+qy5McAyxpHhn6D8Ankrye3sLbB1eVI44kaYiq6hbgY8DHkswBXgb8PMmPgC9Nw93mNiNUR/ssa25WPBK4peVnp2Xkahd3+CVpltkYuLV5/8hpPK7XCUmaRSZbI2ns4nqj6yO1Wlyvqk6rqm2r6glV9U9N25FNEYmquqKqnlVVT62qp1XVGdPyW0mSVklVLauq91bVCL11J+6dhsO2GaG6GDioeb838N/NjYXFwH7N03q2BrYBvj8NmSRJK+edwMVJTkhyInAh8M/TdGyvE5I0i7RaI6lZXG8Tev8wr9/Xft6ggkmSulVVPwaOmYbjtBmh+il6D1xYSu9u937NZy9P8jngCuB+4LVV9cBUM0mSVk5VnZzkHGCHpumwqrpxmo7tdUKSZpG2i20fAhxKb6joJcAz6S3M+tzBRZMkrS6q6jTgtDFtR/a9vxfYZwWf/SfgnwYaUJI0qaq6gWakUJJtkxxbVa+epmN7nZCkWaLtYtuH0rv7cG1VPQd4OnD7wFJJkiRJ6lyS7ZOckeSyJO9IskWSLwD/TW8UkCRpDdNqRBJwb1Xdm4Qk61XVlUmeNNBkkqShSPKMifZX1UXDyiJJmnE+AXyU3myE3enNTjgReEUzSkiStIZpW0halmRj4FTgzCS3AdcOLpYkaYjeO8G+wmnMkrQmW6+qTmjeX5Xk0Kp6c5eBJEndarvY9l80b49Ocja9x21+fWCpJElD00xZliRpPOsneTqQZvu+/m1HrUrSmqftYtsnVdWBAFV17mgbcOAAs0mShizJU4D5PPQJnZ/uLpEkqWM3AO/r276xb9tRq5K0Bmo7tW27/o0kawN/NP1xJEldSXIUsAu9QtJpwB7AtwELSZK0hnLUqiRprAmf2pbkiCR3AdsnuTPJXc32TcCXh5JQkjQsewO7AjdW1V8BT6U3lVmSJEmSgEkKSVX1zqraEHhPVW1UVRs2r0dV1RFDyihJGo57qupB4P4kG9G7abBVx5kkSZIkzSBtF9s+IslewLObpnOq6quDiyVJ6sCS5gmdnwAuBH5B73HPkiRJkgS0X2z7ncCOwH80TYcm+ZOqesvAkkmShqqqXtO8/ViSbwAbVdWlXWaSJM0MSZ4xTvMdwLVVdf+w80iSutN2se0/B57WTHkgyYnAxYCFJElajSTZEng8zfUhybOr6rxuU0mSZoCPAM8ALgUCPAWLuq4tAAAd90lEQVS4HHhkkr+pqjO6DCdJGp62hSSAjYFbm/cuvipJq5kk7wZeBlwBPNA0F2AhSZL0f8CrqupygCTzgWOANwNfBCwkSdIaom0h6Z3AxUnOpncH4tmAi21L0urlxcCTquq+roNIkmacbUeLSABVdUWSJ1fVNUm6zCVJGrK2i22fnOQcYIem6bCqunFgqSRJXbgGWBewkCRJGuvyJB8FTmm2XwZckWQ94NfdxZIkDVvrqW1VdQOwGCDJtkmOrapXDyyZJGkoknyI3hS2XwKXJPkmfcWkqvq7rrJJkmaMg4HXAH/fbP8P8EZ6RaTndJRJktSBCQtJSbYH/hV4HHAqcBzwYWAn4L0DTydJGoYlzc8LaW4Y9KkhZ5EkzUBVdQ+9//+P9x3gF0OOI0nq0GQjkj4BfBT4LrA7cAlwIvCKqrp3wNkkSUNQVScCJDm0qj7Yvy/Jod2kkiTNJEmeBRxN35M9Aarq97vKJEnqxlqT7F+vqk6oqquaLxd3V9WbLSJJ0mrpoHHaDh52CEnSjPQp4H3AzvTWTR19SZLWMJONSFo/ydPpPakN4L7+7aq6aJDhJEmDl2R/4OXA1kn6p7ZtCNzaTSpJ0gxzR1V9vesQkqTuTVZIuoHenYdRN/ZtF/DcQYSSJA3Vd+j9e78ZD1374i7g0k4SSZJmmrOTvAf4Ig99IIM3liVpDTNhIamqpvQEhiS7Ax8E1gY+WVXvGqfPvvTmWxfwg6p6+VTOKUlaOVV1LXAt8MddZ5EkzVg7NT9H+tq8sSxJa6DJRiStsiRr03vK227AMuCCJIur6oq+PtsARwDPqqrbkjx6UHkkSRNLche/fUrbw4B16a2Nt1F3qSRJM8FUbzBLklYfAyskATsCS6vqGoAkpwALgCv6+rwaOK6qbgOoqpsGmEeSNIGq2nD0fZLQ+zf7md0lkiR1LckBVfWZJG8Yb39VvW+8dknS6muyp7ZNxZbAdX3by5q2ftsC2yb5nyTnN1PhJEkdq55TgRd0nUWS1Knfa35uuIKXJGkNM+GIpCRPrqorkzxjvP3TsLjeOsA2wC7AHOC8JH9YVbePybEQWAgwd+7cKZ5SkjSeJC/p21yL3joY93YUR5I0A1TVx5ufb+86iyRpZphsatsb6BVw3jvOvskW17se2Kpve07T1m8Z8L2q+jXwkyQ/pldYuuAhJ6paBCwCGBkZKSRJg7Bn3/v7gZ/Sm94mSVrDJdmc3rIU8+j7DlFVr+wqkySpG5M9tW1h83NVFte7ANgmydb0Ckj7AWOfyHYqsD/w70k2ozfV7ZpVOJckaYqq6q+6ziBJmrG+DHwLOAt4oOMskqQOtVpsO8n6wGuAnemNRPoW8LGqWuGUh6q6P8nrgNOBtYHjq+ryJMcAS6pqcbPv+UmuoHdBelNV3TKl30iStEqawv/f8rt3m/fqKpMkacZ4eFUd1nUISVL32j617dPAXcCHmu2XAycB+0z0oao6DThtTNuRfe+L3vS5cZ8CIUkaqlOBTwFfAR7sOIskaWb5apIXNv+/lyStwdoWkp5SVfP7ts9uRhFJklYf91bVv3UdQpI0Ix0KvCXJfcCvgdC7L7xRt7EkScPWtpB0UZJnVtX5AEl2ApYMLpYkqQMfTHIUcAZw32jjNDyhU5I0y1XVhl1nkCTNDBMWkpL8kN6aSOsC30nys2b78cCVg48nSRqiPwQOpPdEztGpbZM9oVOStAZI8uzx2qvqvGFnkSR1a7IRSS8aSgpJ0kywD/D7VfWrroNIkmacN/W9Xx/YEbgQbzZI0hpnwkJSVV3bv53k0fQuHJKk1c9lwMbATV0HkSTNLFW1Z/92kq2AD3QUR5LUoVZrJCXZC3gv8Dh6XzAeD/wI2G5w0SRJQ7YxcGWSC3joGkl7dRdJkjRDLQP+oOsQkqTha7vY9rHAM4GzqurpSZ4DHDC4WJKkDhzVdQBJ0syU5EP01s0DWAt4GuDDGCRpDdS2kPTrqrolyVpJ1qqqs5M4lFWSViNVdW7XGSRJM1b/E5vvB06uqv/pKowkqTttC0m3J3kEcB7wH0luAu4eXCxJ0rAk+XZV7ZzkLn57txkgQFXVRh1FkyTNHBtX1Qf7G5IcOrZNkrT6W6tlvwXAL4HXA98A/hfYc8JPSJJmharaufm5YVVt1Pfa0CKSJKlx0DhtBw87hCSpe60KSVV1d1U9WFX3V9WJwIeB3QcbTZI0TEk+leRpY9qO7iiOJGkGSLJ/kq8AWydZ3Pc6G7i163ySpOGbcGpbko2A1wJbAouBM5vtNwI/AP5j0AElSUPzAmAkyfuamwYAewFHdxdJktSx7wA3AJvRe4rzqLuASztJJEnq1GQjkk4CngT8EDgEOBvYB3hxVS0YcDZJ0nDdBDwb2DvJcUnWobdO0ipLsmmSM5Nc3fzcZAX9Dmr6XJ3koKbt4Um+luTKJJcneddUskiSVl5VXVtV51TVHwM/BdZtHs7wI2CDqR7f64QkzT6TFZJ+v6oOrqqPA/sD84EXVNUlg48mSRqyVNUdVbUnsBw4B3jkFI95OPDNqtoG+Gaz/dCTJpsCRwE7ATsCR/V9kfjXqnoy8HTgWUn2mGIeSdIqSPJq4PPAx5umOcCp03BorxOSNMtMVkj69eibqnoAWFZV9w42kiSpI4tH31TV0cC7gZ9M8ZgLgNFpcicCLx6nzwuAM6vq1qq6jd406t2r6pdVdXaT51fARfS+uEiShu+1wLOAOwGq6mrg0dNwXK8TkjTLTFZIemqSO5vXXcD2o++T3DmMgJKk4aiqo8Y03QZcOcXDPqaqbmje3wg8Zpw+WwLX9W0va9p+I8nG9J4W+s3xTpJkYZIlSZYsX758ipElSeO4rynWANBMf65pOK7XCUmaZSZcbLuq1h5WEElS95I8HXg5vfXwfgJ8ocVnzgIeO86ut/ZvVFUlWekvHc2XlZOBf6uqa8brU1WLgEUAIyMj0/HFRpL0UOcmeQuwQZLdgNcAX2nzQa8TkrR6mbCQJEla/SXZlt46ePsDNwOfpbde0nPafL6qnjfBsX+eZIuquiHJFvQW9B7remCXvu059NZnGrUIuLqqPtAmjyRpIA4HXkXvITx/DZwGfLLNB71OSNLqZbKpbZKk1d+VwHOBF1XVzlX1IeCBaTr2YuCg5v1BwJfH6XM68PwkmzSLpz6/aSPJO+gt+P3305RHkrQKqupBeotrv6aq9q6qT1TVdIzs8TohSbOMhSRJ0kuAG4Czk3wiya5ApunY7wJ2S3I18LxmmyQjST4JUFW3AscCFzSvY6rq1iRz6E17mA9clOSSJIdMUy5JUgvpOTrJzcBVwFVJlic5cppO4XVCkmYZp7ZJ0hquqk4FTk3ye/SenvP3wKOTfBT4UlWdMYVj3wLsOk77EuCQvu3jgePH9FnG9BW0JEmr5vX0nta2Q1X9BCDJ7wMfTfL6qnr/VA7udUKSZh9HJEmSAKiqu6vqP6tqT3rrT1wMHNZxLElStw4E9h8tIgE0C1ofAPxlZ6kkSZ2xkCRJ+h1VdVtVLaqq37lLLElao6xbVTePbayq5cC6HeSRJHVsoIWkJLsnuSrJ0iSHT9DvpUkqycgg80iSJElaKb9axX2SpNXUwNZISrI2cBywG7AMuCDJ4qq6Yky/DYFDge8NKoskSZKkVfLUJHeO0x5g/WGHkSR1b5AjknYEllbVNVX1K+AUeou4jnUs8G7g3gFmkSRJkrSSqmrtqtponNeGVeXUNklaAw2ykLQlcF3f9rKm7TeSPAPYqqq+NsAckiRJkiRJmgadLbadZC3gfcA/tOi7MMmSJEuWL18++HCSJEmSJEn6HYMsJF0PbNW3PadpG7Uh8BTgnCQ/BZ4JLB5vwe3myUEjVTWy+eabDzCyJEmSJEmSVmSQhaQLgG2SbJ3kYcB+wOLRnVV1R1VtVlXzqmoecD6wV1UtGWAmSZIkSZIkraKBFZKq6n7gdcDpwI+Az1XV5UmOSbLXoM4rSZIkSZKkwVhnkAevqtOA08a0HbmCvrsMMoskSZIkSZKmprPFtiVJkiRJkjS7WEiSJEmSJElSKxaSJEmSJEmS1IqFJEmSJEmSJLViIUmSJEmSJEmtWEiSJEmSJElSKxaSJEmSJEmS1IqFJEmSJEmSJLViIUmSJEmSJEmtWEiSJEmSJElSKxaSJEmSJEmS1IqFJEmSJEmSJLViIUmSJEmSJEmtWEiSJEmSJElSKxaSJEmSJEmS1IqFJEmSJEmSJLViIUmSJEmSJEmtWEiSJEmSJElSKxaSJEmSJEmS1IqFJEmSJEmSJLViIUmSJEmSJEmtWEiSJEmSJElSKwMtJCXZPclVSZYmOXyc/W9IckWSS5N8M8njB5lHkiRJkiRJq25ghaQkawPHAXsA84H9k8wf0+1iYKSqtgc+D/zLoPJIkiRJkiRpagY5ImlHYGlVXVNVvwJOARb0d6iqs6vql83m+cCcAeaRJEmSJEnSFAyykLQlcF3f9rKmbUVeBXx9gHkkSZIkSZI0Bet0HQAgyQHACPBnK9i/EFgIMHfu3CEmkyRJkiRJ0qhBjki6Htiqb3tO0/YQSZ4HvBXYq6ruG+9AVbWoqkaqamTzzTcfSFhJkiRJkiRNbJCFpAuAbZJsneRhwH7A4v4OSZ4OfJxeEemmAWaRJEmSJEnSFA2skFRV9wOvA04HfgR8rqouT3JMkr2abu8BHgH8V5JLkixeweEkSbNQkk2TnJnk6ubnJivod1DT5+okB42zf3GSywafWJI0TF4nJGn2GegaSVV1GnDamLYj+94/b5DnlyR17nDgm1X1riSHN9uH9XdIsilwFL218gq4MMniqrqt2f8S4BfDjS1JGhKvE5I0ywxyapskSQuAE5v3JwIvHqfPC4Azq+rW5kvBmcDuAEkeAbwBeMcQskqShs/rhCTNMhaSJEmD9JiquqF5fyPwmHH6bAlc17e9rGkDOBZ4L/DLgSWUJHXJ64QkzTIDndomSVr9JTkLeOw4u97av1FVlaRW4rhPA55QVa9PMm+SvguBhQBz585tewpJ0hB4nZCk1YuFJEnSlEy03l2SnyfZoqpuSLIFMN4TOq8HdunbngOcA/wxMJLkp/SuV49Ock5V7TLm81TVImARwMjISOsvIZKkwfM6IUmrF6e2SZIGaTEw+nSdg4Avj9PndOD5STZpntbzfOD0qvpoVT2uquYBOwM/Hu/LgSRpVvM6IUmzjIUkSdIgvQvYLcnVwPOabZKMJPkkQFXdSm+Niwua1zFNmyRp9ed1QpJmGae2SZIGpqpuAXYdp30JcEjf9vHA8RMc56fAUwYQUZLUIa8TkjT7OCJJkiRJkiRJrVhIkiRJkiRJUisWkiRJkiRJktSKhSRJkiRJkiS1YiFJkiRJkiRJrVhIkiRJkiRJUisWkiRJkiRJktSKhSRJkiRJkiS1YiFJkiRJkiRJrVhIkiRJkiRJUisWkiRJkiRJktSKhSRJkiRJkiS1YiFJkiRJkiRJrVhIkiRJkiRJUisWkiRJkiRJktSKhSRJkiRJkiS1MtBCUpLdk1yVZGmSw8fZv16Szzb7v5dk3iDzSJIkSZIkadUNrJCUZG3gOGAPYD6wf5L5Y7q9Critqp4IvB9496DySJIkSZIkaWrWGeCxdwSWVtU1AElOARYAV/T1WQAc3bz/PPDhJKmqGlSol338u4M6tCRJkiRJ0mptkFPbtgSu69te1rSN26eq7gfuAB419kBJFiZZkmTJ8uXLVynM+uu6HJSk2cF/ryRJkiTNVIMckTRtqmoRsAhgZGRklUYrXXnsHtOaSZIkSZIkaU0zyNve1wNb9W3PadrG7ZNkHeCRwC0DzCRJkiRJkqRVNMhC0gXANkm2TvIwYD9g8Zg+i4GDmvd7w/9v7+5jLKvvOo6/P4UKUhCh0JRQCqVFedDSpYRUwBa0KRRTqRoSGqrFblW0YLFpEw3aYKMpJsaqETUNJZGmoRWKig0EsEvbCF1gbVmWbYHCgsqGyFNb2GDR0q9/3N/I2enuzNmd+3Bm5v1Kbube83Q/87vnnk/2zLl3WTfJ70eSJEmSJEnS7pvYR9uq6ntJLgRuAvYArqyqzUk+CmyoquuBTwKfSvIg8DSjk02SJEmSJEkaoIl+R1JV3QDcMG/aRzr3vwucM8kMkiRJkiRJGg//ayBJkiRJkiT14okkSZIkSZIk9eKJJEmSJEmSJPXiiSRJkiRJkiT14okkSZIkSZIk9eKJJEmSJEmSJPXiiSRJkiRJkiT1kqqadYZdkuQJ4N93c/WDgCfHGGcchpgJhpnLTP0NMZeZ+tvdXIdX1cHjDrPc2BNTM8RcZupniJlgmLlWWiZ7AntiSoaYCYaZy0z9DTHXSsvUqyeW3YmkpUiyoapOnHWOriFmgmHmMlN/Q8xlpv6Gmms1GOLYDzETDDOXmfoZYiYYZi4zab4hjr+Z+htiLjP1N8RcqzWTH22TJEmSJElSL55IkiRJkiRJUi+r7UTSJ2YdYAeGmAmGmctM/Q0xl5n6G2qu1WCIYz/ETDDMXGbqZ4iZYJi5zKT5hjj+ZupviLnM1N8Qc63KTKvqO5IkSZIkSZK0+1bbFUmSJEmSJEnaTSvmRFKSM5Pcn+TBJL+7g/l7Jflsm39HkiM6836vTb8/yRlTzPTBJF9Pck+SLyQ5vDPvhSR3t9v1U8x0fpInOs/9vs689yT5Zru9Z1yZeub6eCfTA0m+3Zk39rFKcmWSx5Pcu5P5SfKXLe89SU7ozJvkOC2W67yWZ1OS25Mc35n3SJt+d5INU8x0WpLvdF6jj3TmLfi6TzDThzt57m370IFt3qTG6bAkt7b3/OYkH9jBMjPZr1YLe2JsmabeE0PriLbdwfXEEDuiZy57AntiCOyJsWWyJ7AnxpzLnmBgPVFVy/4G7AE8BBwJ/BCwETh23jK/Bfxtu38u8Nl2/9i2/F7Aa9p29phSptOBfdr935zL1B5vm9E4nQ/81Q7WPRDY0n4e0O4fMK1c85a/CLhywmP1ZuAE4N6dzD8LuBEI8CbgjkmPU89cJ889H/D2uVzt8SPAQTMYq9OAzy/1dR9npnnLvgNYN4VxOgQ4od3fD3hgB++/mexXq+HW8/hnTwywJ3b1WMEUOqJtd3A90SPT1DuiZ67TsCfAnpjprefxz56wJ3Yllz0xvlynYU/AgHpipVyRdBLwYFVtqar/AT4DnD1vmbOBv2v3rwV+Nkna9M9U1fNV9TDwYNvexDNV1a1V9Vx7uB541Ried0mZFnAGcEtVPV1V3wJuAc6cUa53AVeP6bl3qKq+DDy9wCJnA1fVyHrgR5McwmTHadFcVXV7e16Yzj7VZ6x2Zin74zgzTXx/Aqiqx6rqq+3+s8A3gEPnLTaT/WqVsCfGlGkBk9pPB9cRMMyeGGJH9Mm1AHvCnpgme2JMmRZgT2zPnuiZawH2xIx6YqWcSDoU+M/O40f5wQH9/2Wq6nvAd4CX91x3Upm61jI6czhn7yQbkqxP8s4x5NmVTL/ULoO7Nslhu7juJHPRLtd9DbCuM3kSY7WYnWWe5Djtqvn7VAE3J/m3JL8+5Sw/lWRjkhuTHNemzXyskuzD6AD6uc7kiY9TRpfCrwHumDdrOexXy5U9Md5M0+yJ5dgRMPz385A6AuyJ+c97BPbEtNkT481kTyxu6O9ne6KH1doTe+7uihqfJO8GTgTe0pl8eFVtTXIksC7Jpqp6aApx/hm4uqqeT/IbjP7q8jNTeN6+zgWuraoXOtNmNVaDleR0Rgf/UzuTT23j9ArgliT3tTPtk/ZVRq/RtiRnAf8IHDWF5+3jHcBtVdX9a8NExynJvoyK5uKqemZc29XKZk/0Zkf0MLCOAHtiO/aEdoc90Zs90YM9sUtWZU+slCuStgKHdR6/qk3b4TJJ9gT2B57que6kMpHkrcAlwM9X1fNz06tqa/u5Bfgio7ONE89UVU91clwBvLHvupPM1XEu8y4bnNBYLWZnmSc5Tr0keT2j1+7sqnpqbnpnnB4H/oHxXHK9qKp6pqq2tfs3AC9NchADGCsW3p/GPk5JXsrooP/pqrpuB4sMdr9aAeyJMWWaQU8sx46Agb6fh9YR7TnticaemCl7YkyZ7IneBvl+tid22ersiZrAl2VN+8boyqotjC5TnPuSrePmLfN+tv9yvL9v949j+y/H28J4vhyvT6Y1jL4c7Kh50w8A9mr3DwK+yRi+NKxnpkM6938BWF8vfjnXwy3bAe3+gdN6/dpyRzP64rJMeqza9o5g51/49nNs/yVmd056nHrmejWjz+WfPG/6y4D9OvdvB86cUqZXzr1mjA6i/9HGrdfrPolMbf7+jD73/LJpjFP7na8C/nyBZWa2X630W8/jnz0xwJ7oe6xgyh3RtrnQsW8m7+dFMs2kI3rksifKnpj1refxz56wJ3Y120LHPnuify57oobVE2N74Wd9Y/Tt5A8wOpBe0qZ9lNGZeYC9gWvaG+NO4MjOupe09e4H3j7FTP8C/Bdwd7td36afDGxqb4RNwNopZvoYsLk9963A0Z1139vG70HgV6f5+rXHlwKXzVtvImPF6KzyY8D/Mvr86FrgAuCCNj/A5S3vJuDEKY3TYrmuAL7V2ac2tOlHtjHa2F7fS6aY6cLOPrWeTjHt6HWfRqa2zPmMvhizu94kx+lURp+Xvqfz+pw1hP1qtdwWO85gT/TNNPWeWCxTe3wpU+qItu3B9USPTFPviJ657ImyJ4ZwW+xYgz3RN5M9UfbEmHPZEzWsnpg7qydJkiRJkiQtaKV8R5IkSZIkSZImzBNJkiRJkiRJ6sUTSZIkSZIkSerFE0mSJEmSJEnqxRNJkjRhSa5M8niSe8e0vReS3N1u149jm5Kk2bEnJEkLGVpP+L+2aUVK8nLgC+3hK4EXgCfa4+e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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "formatted_plot_data = ramsey_sequence.get_plot_formatted_arrays()\n", - "rabi_rotations, azimuthal_angles, detuning_rotations, times = (\n", - " formatted_plot_data['rabi_rotations'],\n", - " formatted_plot_data['azimuthal_angles'],\n", - " formatted_plot_data['detuning_rotations'],\n", - " formatted_plot_data['times']\n", - ")\n", - "\n", - "# prepare the axes\n", - "figure, (rabi_plot_axis, azimuth_plot_axis, detuning_plot_axis) = plt.subplots(\n", - " 1, 3, figsize=(20,5))\n", - "\n", - "rabi_plot_axis.plot(times, rabi_rotations)\n", - "rabi_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "rabi_plot_axis.set_xlabel('Time (sec)')\n", - "rabi_plot_axis.set_ylabel('Rabi Rotations (rad)')\n", - "\n", - "azimuth_plot_axis.plot(times, azimuthal_angles)\n", - "azimuth_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "azimuth_plot_axis.set_xlabel('Time (sec)')\n", - "azimuth_plot_axis.set_ylabel('Azimuthal Angle (rad)')\n", - "\n", - "detuning_plot_axis.plot(times, detuning_rotations)\n", - "detuning_plot_axis.ticklabel_format(style='sci', axis='x', scilimits=(0, 2))\n", - "detuning_plot_axis.set_xlabel('Time (sec)')\n", - "detuning_plot_axis.set_ylabel('Detuning Rotation (rad)')\n", - "\n", - "plt.suptitle('Ramsey Sequence')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Drawing the Circuits\n", - "\n", - "We can use Qiskit to draw the circuits generated by Q-CTRL Open Controls." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Drawing the Quadratic DDS Circuit\n", - "\n", - "Note that both DDS will be applied with $X_{\\pi/2}$ rotations at beginning and end, that is, at offsets of $[0, 20]$ $\\mu$s, to create the desired superposition state. The $X_{\\pi/2}$ rotations are added to the circuits in the form of pre-post-gates that are implemented via Qiskit's $U3(\\pi/2, -\\pi/2, \\pi/2)$ gate.\n", - "\n", - "The $U1(\\pi)$ gates are $Z_\\pi$ pulses (a $\\pi$ rotation around $Z$-axis) and $U3(\\pi, -\\pi/2, \\pi/2)$ gates correspond to $X_{\\pi}$ pulses (a $\\pi$ rotation around $X$-axis). The gates match the pulses in the DDS.\n", - "\n", - "The `Id` in the drawing corresponds to the `identity` gate. In the DDS, the first $Z_{\\pi}$-pulse is applied at a delay of $1.25$ $\\mu$s. This is approximated by introducing 3-`Id` gates with a delay of $0.4\\times 3=1.2$ $\\mu s$. Similarly, the second set of 6 `Id` gates introduces a delay of $2.4$ $\\mu s$ close to the actual delay of $3.75-1.25=2.50\\mu s$.\n", - "\n", - "The `barrier` gates are special gates that tell the Qiskit compilers not to simplify a circuit at the specified positions.\n", - "\n", - "At the end of each circuit, we place a `measurement` operator to read out the result." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
         ┌───────────────────────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────────────┐»\n",
-       "q0_0: |0>┤ U3(1.5708,-pi/2,pi/2) ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ U1(3.1416) ├»\n",
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-       "«q0_0: ┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ U3(3.1416,-pi/2,pi/2) ├─░─┤ Id ├─░─┤ Id ├»\n",
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-       "«                                                              »\n",
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-       "«q0_0: ┤ U3(1.5708,-pi/2,pi/2) ├─░─┤M├\n",
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" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "##Drawing the Quadratic Circuit\n", - "quadratic_quantum_circuit.draw()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Drawing the Ramsey DDS Circuit\n", - "\n", - "The drawing below shows the Ramsey DDS circuit consists of `Id` or `identity` gates surrounded by $X_{\\pi/2}$-pulses on both ends. The `measurement` operator appears at the end as in the original definition of the circuit. This will help us run the circuit in one of the simulators." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
         ┌───────────────────────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐»\n",
-       "q1_0: |0>┤ U3(1.5708,-pi/2,pi/2) ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├»\n",
-       "         └───────────────────────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘»\n",
-       " c1_0: 0 ══════════════════════════════════════════════════════════════════════»\n",
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-       "«q1_0: ─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├»\n",
-       "«       ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘»\n",
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-       "«q1_0: ─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├»\n",
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-       "«q1_0: ─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├»\n",
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-       "«q1_0: ─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├»\n",
-       "«       ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘»\n",
-       "«c1_0: ════════════════════════════════════════════════════════════════════════»\n",
-       "«                                                                              »\n",
-       "«       ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ ┌────┐ ░ »\n",
-       "«q1_0: ─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─┤ Id ├─░─»\n",
-       "«       ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ └────┘ ░ »\n",
-       "«c1_0: ════════════════════════════════════════════════»\n",
-       "«                                                      »\n",
-       "«      ┌───────────────────────┐ ░ ┌─┐\n",
-       "«q1_0: ┤ U3(1.5708,-pi/2,pi/2) ├─░─┤M├\n",
-       "«      └───────────────────────┘ ░ └╥┘\n",
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" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ramsey_quantum_circuit.draw()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And here we count 50 `Id` operations, implementing a total delay of $50 \\times 0.4 = 20 \\mu s$" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "50\n" - ] - } - ], - "source": [ - "print(ramsey_quantum_circuit.count_ops()['id'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the Circuit on Qiskit Simulator using Qiskit API\n", - "\n", - "Before running our circuits on the real IBM Q hardware, let's run them through a simulator first.\n", - "\n", - "Consult [Simulating Circuits using Qiskit Aer](https://qiskit.org/documentation/getting_started.html#simulating-circuits-using-qiskit-aer) for a description of available simulators and their respective properties.\n", - "\n", - "Here, we will use the `qasm-simulator` to run the circuit. The experiment consists of `number_of_shots` repeats of the circuit operations on a qubit. Each run collects the state of the qubit as measurement. The result is displayed as a histogram." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "## Prepares the simulator backend\n", - "'''\n", - "backend : str\n", - " One of 'unitary_simulator', 'statevector_simulator' or 'qasm_simulator';\n", - " defaults to 'qasm_simulator'\n", - "'''\n", - "backend = 'qasm_simulator'\n", - "backend_simulator = BasicAer.get_backend(backend)\n", - "\n", - "'''\n", - "number_of_shots : int\n", - " Number of repeats the experiment has to be carried out;\n", - " defaults to 1\n", - "'''\n", - "number_of_shots = 1024" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "## Run the quadratic sequence circuit, Get the result (counts of state |1> and |0>), plot the histogram\n", - "job = execute(quadratic_quantum_circuit, backend_simulator, shots=number_of_shots)\n", - "result = job.result()\n", - "counts = result.get_counts(quadratic_quantum_circuit)\n", - "plot_histogram(counts)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "## Run the ramsey sequence circuit, Get the result (counts of state |1> and |0>), plot the histogram\n", - "job = execute(ramsey_quantum_circuit, backend_simulator, shots=number_of_shots)\n", - "result = job.result()\n", - "counts = result.get_counts(ramsey_quantum_circuit)\n", - "plot_histogram(counts)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Running a Dynamical Decoupling Sequence on a Real Device\n", - "\n", - "Now that we've verified that our circuits run on the simulators, let's take a look at what happens when we run them on the real IBM Q devices.\n", - "\n", - "We use the same DDS and circuit defined above and use Qiskit's APIs to run the circuit. See [Running Circuits on IBM Q Devices](https://qiskit.org/documentation/getting_started.html#running-circuits-on-ibm-q-devices) for a more detailed explanation of the APIs used here." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Select a Suitable Device Based on Account Type and Configuration Using Qiskit API\n", - "\n", - "We use a basic configuration and choose the least busy device." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Least busy device is ibmqx2\n" - ] - } - ], - "source": [ - "# NBVAL_SKIP\n", - "'''\n", - "account_token : str\n", - " Token to enable IBM Q device access\n", - "'''\n", - "account_token = 'insert-your-ibmq-token-here'\n", - "IBMQ.enable_account(account_token)\n", - "available_devices = IBMQ.backends(\n", - " filters=lambda x: not x.configuration().simulator and x.status().operational is True\n", - ")\n", - "#print(available_devices)\n", - "backend = least_busy(available_devices)\n", - "print('Least busy device is {}'.format(backend.name()))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the Circuits on a Real Device Using Qiskit API" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Job Status: job has successfully run\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# NBVAL_SKIP\n", - "'''\n", - "number_of_shots : int\n", - " Number of repeats the experiment has to be carried out;\n", - " defaults to 1\n", - "'''\n", - "number_of_shots = 1024\n", - "\n", - "# Run on a device\n", - "job = execute(quadratic_quantum_circuit, backend, shots=number_of_shots)\n", - "job_monitor(job)\n", - "result = job.result()\n", - "counts = result.get_counts(quadratic_quantum_circuit)\n", - "plot_histogram(counts)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Job Status: job has successfully run\n" - ] - }, - { - "data": { - "image/png": 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Z3V9EBEBm/nFfFidJ0mDVkz3QHwA7Lhra3UhEkiQNGT0Zieiq7t5LkjSUOTSfJEkF9OQc6G7Pe3bmOVBJ0lDR06exSJKkTnp1DlSSJJV4DlSSpAK8D1SSpAK8D1SSpAK8D1SSpAJ6NRbuDhFxBNBQnlyVmY/3XUmSJA1+vQrQiBgH/CNwFvDyfzfHvwAXZeaGXS4sSdI+pLdX4f4DMBU4ETig/DoJOByfBypJGkJ6ewj3LcBpmflwp7YHI+J/APf2XVmSJA1uvd0DbQe6e5j2FsDDt5KkIaO3Afq3wDURcdiOhvL7q8vzJEkaEooMJn84sCYinixPHwa8APwBpXOkkiTt8xxMXpKkAio+mHxEfBj4FFALrAAuy8yf76LvHOD+bmY1ZOZvOvV7F/AF4AjgceB/ZuYP+7JuSZI6q+hg8hExF7gWmAc0Ag8BCyNi4h4WnU4pcHe8Vnda5/HA7cB3gWPK/94REW/o8w2QJKmsVwEaEVURcVVE/GdEvBAR2zu/erCKy4GbMvPGzFyVmR8F2oAP7WG5pzPzqU6vzp91GXB/Zn6xvM4vAj8tt0uS1C96ex/oF4C5wJeAr1M6FDsZeDfwN7tbMCKqgOOAr3aZdQ9wwh4+99cRsT+wEvi7zOx8WPd44Btd+v8Y+Mgu6rgYuBigtraWJUuWAFBXV8fIkSN57LHHABgzZgxTpkxh6dKlAAwbNoyZM2fS3NzM88+X7uRpaGjg2WefZf369QBMmDCBqqoqWlpaABg7diwTJ06kqakJgBEjRnD00UezatUqtm7dCsBRRx1Fe3s77e3tAEyaNImIYM2aNQCMGzeO2tpali9fDsD+++/P9OnTWbFiBdu2lcb4nzFjBm1tbWzYULqTaPLkyWQma9euBaCmpoaamhpWrlwJwIEHHkhDQwPLli3jxRdfBGDmzJk88cQTbNy4EYApU6bQ0dHBunXrABg/fjzV1dWsWrUKgIMOOoj6+nqamprYvr3090xjYyMtLS1s2rQJgKlTp7JlyxZaW1vZ8fMePXo0zc3NAIwaNYpp06axdOlSMpOIoLGxkdWrV7N582YA6uvree6552hra/N78nvqs+9J+6YNGzb0ye9TT0XmLp9O9urOEb8FPpSZ/xYRm4FjMvPxiPgQpQEWzt3NsnXAk5QejfZAp/YrgfMzs76bZeqBU4BHgCrgfcAl5XX8vNynA/hAZt7SabkLgBszc//dbU9jY2MuWrSop5svaR9xxc1jB7oE9YP579/YJ+uprq5enJmz9tSvt3ug4yntBQL8Hji4/P7fgC/3cl17lJnNQHOnpocjYjKlPd9uLzySJKkSensR0RNAXfn9Y5SG9oPSYdSte1j2GWA7pRDubDzwVC9q+CUwrdP0U32wTkmSeqW3AfpD4LTy+2uBq8qHdW9iD4MoZGYHsBg4vcus0yldjdtTx1C68GiHh/tgnZIk9UqvDuFm5mc7vf9+RKyjdAHQf2bmv/RgFV8DvhMRvwIepHQ+sw64ASAibimv+4Ly9GXAGkr3i1YB7wXOBt7VaZ3XAg9ExGeAfwbeSem86Zt7s22SJPVGoQdq75CZ/w78ey/6315+puhfU7qfcznw1sxcW+7S9X7QKuArwARKh4hXAG/LzLs7rfOhiHg38HeUxuN9HJibmb8stlWSJO1ZrwM0Io6ldI/lUeWmVcDXM3NJT5bPzOuB63cxb06X6fnA/B6s8/s45KAkqYJ6O5DC+ZRuKakF7i6/xgO/ioj39n15kiQNTr3dA/0i8DeZOa9zY0R8ltIh1Fv7qjBJkgaz3l6FWwN8r5v2Oyg9zkySpCGhtwF6PzCnm/Y5wM9eazGSJO0tevJA7XM6TS4EvhQRs/jvq2/fCJwDfL7Pq5MkaZAq+kDtnQOyd/INdnF1rSRJ+5qePFC7os8MlSRpb2A4SpJUQK8DNCLeFhEPRMQzEdEeET+LiLf2R3GSJA1WvR1I4QOUBpR/HPg08Bngt8API+Kivi9PkqTBqbcDKXwauDwzr+vU9o8RsZhSmP5Tn1UmSdIg1ttDuBMpPTy7q4XApNdejiRJe4ciD9Tu+uxNgD8F1nbTLknSPqm3h3C/Cnyj/ESWHQ+sfhPwPuCjfVmYJEmDWW8fqP33EfE08AlKow9B6XFm52XmnX1dnCRJg1WPAzQihlM6VPtAZv6w/0qSJGnw6/E50Mx8CVgAjOq/ciRJ2jv09iKiJmBqfxQiSdLepLcB+nng6og4OyL+MCKqO7/6oT5Jkgal3l6F+6/lfxcA2ak9ytPD+qIoSZIGu94G6Cn9UoUkSXuZHgVoRIwEvgKcDYwA7gX+KjOf6cfaJEkatHp6DvQq4EJKh3BvozQa0bf6qSZJkga9nh7CPQf4y8z8fwAR8V3gwYgYlpnb+606SZIGqZ7ugf4h8PMdE5n5K+AloK4/ipIkabDraYAOAzq6tL1E7y9CkiRpn9DTAAzg1ojY1qntAODGiNiyoyEzz+rL4iRJGqx6GqA3d9N2a18WIknS3qRHAZqZf9HfhUiStDfp7VB+kiQJA1SSpEIMUEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCqh4gEbEhyPitxHxQkQsjogTd9P3nIi4JyLaI2JzRPwyIs7q0ufCiMhuXgf0/9ZIkoaqigZoRMwFrgXmAY3AQ8DCiJi4i0VOBhYBbyv3vxv4YTehuwWo7fzKzBf6fgskSSoZXuHPuxy4KTNvLE9/NCLOAD4EfLZr58z8WJemqyLibcDZwM9f2TWf6o+CJUnqTsUCNCKqgOOAr3aZdQ9wQi9WNQrY2KXtwIhYCwwDHgX+JjOX7qKOi4GLAWpra1myZAkAdXV1jBw5ksceewyAMWPGMGXKFJYuLa1m2LBhzJw5k+bmZp5//nkAGhoaePbZZ1m/fj0AEyZMoKqqipaWFgDGjh3LxIkTaWpqAmDEiBEcffTRrFq1iq1btwJw1FFH0d7eTnt7OwCTJk0iIlizZg0A48aNo7a2luXLlwOw//77M336dFasWMG2bdsAmDFjBm1tbWzYsAGAyZMnk5msXbsWgJqaGmpqali5cmXph3XggTQ0NLBs2TJefPFFAGbOnMkTTzzBxo2lH+2UKVPo6Ohg3bp1AIwfP57q6mpWrVoFwEEHHUR9fT1NTU1s374dgMbGRlpaWti0aRMAU6dOZcuWLbS2trLj5z169Giam5tLX+SoUUybNo2lS5eSmUQEjY2NrF69ms2bNwNQX1/Pc889R1tbm9+T31OffU/aN23YsKFPfp96KjKzjzdhFx8UUQc8CZycmQ90ar8SOD8z63uwjkuB/w3MyMy15bbjgT8CmiiF68eAtwIzM3P17tbX2NiYixYtKrhFkvZWV9w8dqBLUD+Y//6u+1bFVFdXL87MWXvqV+lDuIVFxLuArwBzd4QnQGY+DDzcqd9DlPZCPwr8VaXrlCQNDZW8iOgZYDswvkv7eGC35y8j4lzgO8AFmXnX7vpm5nbg18C04qVKkrR7FQvQzOwAFgOnd5l1OqWrcbsVEedRCs8LM/P7e/qciAjgj4G24tVKkrR7lT6E+zXgOxHxK+BB4BKgDrgBICJuAcjMC8rT76YUnp8EHoiIQ8vr6cjMZ8t9/hfw78BqYDSlw7Z/TOnKXkmS+kVFAzQzb4+IccBfU7pfcznw1k7nNLveD3oJpRqvKb92+Bkwp/z+YODbwKHAJmApcFJm/qo/tkGSJBiAi4gy83rg+l3Mm7O76V0s83Hg431RmyRJPeVYuJIkFWCASpJUgAEqSVIBBqgkSQUYoJIkFWCASpJUgAEqSVIBBqgkSQUYoJIkFWCASpJUgAEqSVIBBqgkSQUYoJIkFWCASpJUgAEqSVIBBqgkSQUYoJIkFWCASpJUgAEqSVIBBugQd++99zJ79myOO+44rrnmmlfNf+ihh5gzZw41NTXceeedr5h32223MWvWLGbNmsVtt932qmX//M//nBNOOKHfapekgTR8oAvQwNm+fTtXXHEFCxYsoK6ujtNOO40zzjiDI488cmefCRMm8M1vfpPrrrvuFctu3LiR+fPns2jRIiKCU045hTPPPJODDz4YgLvuuouDDjqootsjSZXkHugQtnjxYg4//HAmT55MVVUV55xzDgsXLnxFn4kTJzJ9+nT22++V/6ksWrSIOXPmMHbsWA4++GDmzJnDfffdB8Dvf/97rr/+ej7xiU9UbFskqdIM0CGsra2Nww47bOd0XV0dbW1tPVq2tbX1Vcu2trYCMG/ePC699FJGjhzZtwVL0iBigKpPLVu2jDVr1vD2t799oEuRpH5lgA5htbW1PPnkkzunW1tbqa2t7dGydXV1r1q2rq6ORx55hEcffZSZM2dy5pln8vjjj/OOd7yjz2uXpIFmgA5hxx57LC0tLaxdu5aOjg4WLFjAGWec0aNlTz31VO6//35+97vf8bvf/Y7777+fU089lYsuuoiVK1fS1NTEwoULOeKII7jrrrv6eUskqfIM0CFs+PDhzJ8/n3PPPZc3vvGNnH322TQ0NDBv3rydFxMtWbKE6dOnc+edd3L55Zdz/PHHAzB27Fg++clPctppp3HaaafxqU99irFjxw7k5khSRUVmDnQNA6axsTEXLVo00GVIqrArbvaPvX3R/Pdv7JP1VFdXL87MWXvq5x6oJEkFOJBCH/Cv2X1TX/01K2nf5B6oJEkFGKCSJBVggEqSVIABKklSAQaoJEkFGKCSJBVggEqSVIABKklSAQaoJEkFGKCSJBVggEqSVIABKklSAQaoJEkFGKCSJBVggEqSVIABKklSAQaoJEkFGKCSJBVggEqSVIABKklSAQaoJEkFGKCSJBVQ8QCNiA9HxG8j4oWIWBwRJ+6h/8nlfi9EREtEXPJa1ylJ0mtV0QCNiLnAtcA8oBF4CFgYERN30f9w4O5yv0bgS8A3IuJdRdcpSVJfqPQe6OXATZl5Y2auysyPAm3Ah3bR/xKgNTM/Wu5/I3Az8MnXsE5Jkl6zigVoRFQBxwH3dJl1D3DCLhY7vpv+PwZmRcSIguuUJOk1G17BzzoEGAas79K+HviTXSxzKHBvN/2Hl9cXvV1nRFwMXFye/H11dXVzT4rXTocAzwx0EZXwDx8f6AqkPuHvbO9N6kmnSgbooJCZ3wa+PdB17K0i4teZOWug65DUM/7O9p9KBugzwHZgfJf28cBTu1jmqV30f6m8viiwTkmSXrOKnQPNzA5gMXB6l1mnU7pytjsP76L/rzPzxYLrlCTpNav0IdyvAd+JiF8BD1K6yrYOuAEgIm4ByMwLyv1vAD4SEdcAfw+8CbgQeE9P16k+5+Fvae/i72w/icys7AdGfBi4AqgFlgMfz8wHyvN+CpCZczr1Pxn4OjAdaAW+nJk39HSdkiT1h4oHqCRJ+wLHwpUkqQADVJKkAgxQ7VFETIuIrrcKSdKQ5jlQdSsi/gB4H/BxoJ3SvbdtwPeBH2Tm8wNYniQNOANU3YqIm4CjgH8BNgDjgGOABmAdMD8zfzJgBUrSADNA9SoREcBm4K2dbjEKYALwRuCDlMaKnJuZjw5YoZJeISJGA5vT/7FXhOdA1Z2jgN8CHTsasuS/MvMO4O2UAnbuANUnqXtfAS6KiKPLYfoqETGuwjXtswxQdacFeBr4evkColf8d1IeQvFm4MyBKE7Sq0XEeygdHboauBP4SkS8MyKOiIgDy30OBP4xIo4ewFL3GR7CVbci4o2UhkPcSmkYxfuAjZn5+4gYCdwCvJCZ7x3AMiWVRcSNlB6uMR84B3g/cATQDNxN6Xe4Hrg2M6sGqs59iQGqXYqIGcDfAGcBz1Ma3L+d0rNW24APZOaygatQEkBEDKc0nOnozPxMp/bplPZKzwUOAA4Gbs7MvxyQQvcxBqj2qHxLy9uAs4EXKI03fEdm/mZAC5O0U0SMBcZn5m8iogp4sfPFRBExF7gNONaL//qGAapeiYj9MvPlga5D0p6Vr1+IzNweER+kdPh25EDXta+o9OPMtJczPKW9R5ff11HA/xql1mGbAAAAOElEQVSoWvZF7oFK0hAQESOA7f4R3HcMUEmSCvA+UEmSCjBAJUkqwACVJKkAA1SSpAIMUEmSCvj/YHPRHDVyBeoAAAAASUVORK5CYII=\n", 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" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# NBVAL_SKIP\n", - "'''\n", - "number_of_shots : int\n", - " Number of repeats the experiment has to be carried out;\n", - " defaults to 1\n", - "'''\n", - "number_of_shots = 1024\n", - "\n", - "# Run on a device\n", - "job = execute(ramsey_quantum_circuit, backend, shots=number_of_shots)\n", - "job_monitor(job)\n", - "result = job.result()\n", - "counts = result.get_counts(ramsey_quantum_circuit)\n", - "plot_histogram(counts)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Close the Account\n", - "\n", - "Just to make sure, close the account after the task is over." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "# NBVAL_SKIP\n", - "IBMQ.disable_accounts(token=account_token)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Reducing Errors by Increasing the Coherence Time\n", - "\n", - "In the ideal noiseless simulator, both the Ramsey DDS and Quadratic DDS produced exactly the same outcome, the $|1 \\rangle$ state with probability 1. However, in a real device, we can see a marked difference. The Quadratic DDS produced a probability distribution closer to the expected outcome. This is because the Quadratic DDS is able to cancel the effects of magnetic noise in the environment - extending the [T2 time](https://en.wikipedia.org/wiki/Spin–spin_relaxation), and effectively increasing the coherence of the qubit." - ] - } - ], - "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": "3.6.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/examples/notebook-sanitize.cfg b/examples/notebook-sanitize.cfg deleted file mode 100644 index d079c0f2..00000000 --- a/examples/notebook-sanitize.cfg +++ /dev/null @@ -1,7 +0,0 @@ -[regex1] -regex: \d{1,2}/\d{1,2}/\d{2,4} -replace: DATE-STAMP - -[regex2] -regex: \d{2}:\d{2}:\d{2} -replace: TIME-STAMP diff --git a/poetry.lock b/poetry.lock index 56c11beb..1600ae8f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,12 +1,3 @@ -[[package]] -category = "dev" -description = "Disable App Nap on OS X 10.9" -marker = "sys_platform == \"darwin\"" -name = "appnope" -optional = false -python-versions = "*" -version = "0.1.0" - [[package]] category = "main" description = "Fast ASN.1 parser and serializer with definitions for private keys, public keys, certificates, CRL, OCSP, CMS, PKCS#3, PKCS#7, PKCS#8, PKCS#12, PKCS#5, X.509 and TSP" @@ -45,13 +36,10 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "19.1.0" -[[package]] -category = "dev" -description = "Specifications for callback functions passed in to an API" -name = "backcall" -optional = false -python-versions = "*" -version = "0.1.0" +[package.extras] +dev = ["coverage", "hypothesis", "pympler", "pytest", "six", "zope.interface", "sphinx", "pre-commit"] +docs = ["sphinx", "zope.interface"] +tests = ["coverage", "hypothesis", "pympler", "pytest", "six", "zope.interface"] [[package]] category = "main" @@ -117,14 +105,6 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "0.4.1" -[[package]] -category = "dev" -description = "Code coverage measurement for Python" -name = "coverage" -optional = false -python-versions = "*" -version = "4.4.2" - [[package]] category = "main" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." @@ -138,6 +118,13 @@ asn1crypto = ">=0.21.0" cffi = ">=1.8,<1.11.3 || >1.11.3" six = ">=1.4.1" +[package.extras] +docs = ["sphinx (>=1.6.5,<1.8.0 || >1.8.0)", "sphinx-rtd-theme"] +docstest = ["doc8", "pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling (>=4.0.1)"] +idna = ["idna (>=2.1)"] +pep8test = ["flake8", "flake8-import-order", "pep8-naming"] +test = ["pytest (>=3.6.0,<3.9.0 || >3.9.0,<3.9.1 || >3.9.1,<3.9.2 || >3.9.2)", "pretend", "iso8601", "pytz", "hypothesis (>=1.11.4,<3.79.2 || >3.79.2)"] + [[package]] category = "main" description = "Composable style cycles" @@ -233,48 +220,8 @@ version = "0.18" [package.dependencies] zipp = ">=0.5" -[[package]] -category = "dev" -description = "IPython Kernel for Jupyter" -name = "ipykernel" -optional = false -python-versions = ">=3.4" -version = "5.1.1" - -[package.dependencies] -ipython = ">=5.0.0" -jupyter-client = "*" -tornado = ">=4.2" -traitlets = ">=4.1.0" - -[[package]] -category = "dev" -description = "IPython: Productive Interactive Computing" -name = "ipython" -optional = false -python-versions = ">=3.5" -version = "7.5.0" - -[package.dependencies] -appnope = "*" -backcall = "*" -colorama = "*" -decorator = "*" -jedi = ">=0.10" -pexpect = "*" -pickleshare = "*" -prompt-toolkit = ">=2.0.0,<2.1.0" -pygments = "*" -setuptools = ">=18.5" -traitlets = ">=4.2" - -[[package]] -category = "dev" -description = "Vestigial utilities from IPython" -name = "ipython-genutils" -optional = false -python-versions = "*" -version = "0.2.0" +[package.extras] +docs = ["sphinx", "docutils (0.12)", "rst.linker"] [[package]] category = "dev" @@ -284,16 +231,11 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "4.3.20" -[[package]] -category = "dev" -description = "An autocompletion tool for Python that can be used for text editors." -name = "jedi" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -version = "0.13.3" - -[package.dependencies] -parso = ">=0.3.0" +[package.extras] +pipfile = ["pipreqs", "requirementslib"] +pyproject = ["toml"] +requirements = ["pipreqs", "pip-api"] +xdg_home = ["appdirs (>=1.4.0)"] [[package]] category = "main" @@ -303,31 +245,8 @@ optional = false python-versions = "*" version = "2.6.0" -[[package]] -category = "dev" -description = "Jupyter protocol implementation and client libraries" -name = "jupyter-client" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" -version = "5.2.4" - -[package.dependencies] -jupyter-core = "*" -python-dateutil = ">=2.1" -pyzmq = ">=13" -tornado = ">=4.1" -traitlets = "*" - -[[package]] -category = "dev" -description = "Jupyter core package. A base package on which Jupyter projects rely." -name = "jupyter-core" -optional = false -python-versions = "*" -version = "4.4.0" - -[package.dependencies] -traitlets = "*" +[package.extras] +format = ["rfc3987", "strict-rfc3339", "webcolors"] [[package]] category = "main" @@ -356,6 +275,12 @@ optional = false python-versions = "*" version = "2.19.2" +[package.extras] +dev = ["python-dateutil", "simplejson", "pytest", "pytz", "flake8 (3.7.4)", "tox"] +lint = ["flake8 (3.7.4)"] +reco = ["python-dateutil", "simplejson"] +tests = ["pytest", "pytz"] + [[package]] category = "main" description = "An unofficial extension to Marshmallow to allow for polymorphic fields" @@ -409,36 +334,6 @@ optional = false python-versions = "*" version = "1.1.0" -[[package]] -category = "dev" -description = "The Jupyter Notebook format" -name = "nbformat" -optional = false -python-versions = "*" -version = "4.4.0" - -[package.dependencies] -ipython-genutils = "*" -jsonschema = ">=2.4,<2.5.0 || >2.5.0" -jupyter-core = "*" -traitlets = ">=4.1" - -[[package]] -category = "dev" -description = "A py.test plugin to validate Jupyter notebooks" -name = "nbval" -optional = false -python-versions = "*" -version = "0.9.1" - -[package.dependencies] -coverage = "*" -ipykernel = "*" -jupyter-client = "*" -nbformat = "*" -pytest = ">=2.8" -six = "*" - [[package]] category = "main" description = "Python package for creating and manipulating graphs and networks" @@ -450,6 +345,19 @@ version = "2.3" [package.dependencies] decorator = ">=4.3.0" +[package.extras] +all = ["numpy", "scipy", "pandas", "matplotlib", "pygraphviz", "pydot", "pyyaml", "gdal", "lxml", "nose"] +gdal = ["gdal"] +lxml = ["lxml"] +matplotlib = ["matplotlib"] +nose = ["nose"] +numpy = ["numpy"] +pandas = ["pandas"] +pydot = ["pydot"] +pygraphviz = ["pygraphviz"] +pyyaml = ["pyyaml"] +scipy = ["scipy"] + [[package]] category = "main" description = "Creates NTLM authentication structures" @@ -458,6 +366,9 @@ optional = false python-versions = ">=2.6,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*" version = "1.3.0" +[package.extras] +cryptography = ["cryptography (<2.2)", "cryptography"] + [[package]] category = "main" description = "NumPy is the fundamental package for array computing with Python." @@ -478,34 +389,6 @@ version = "19.0" pyparsing = ">=2.0.2" six = "*" -[[package]] -category = "dev" -description = "A Python Parser" -name = "parso" -optional = false -python-versions = "*" -version = "0.4.0" - -[[package]] -category = "dev" -description = "Pexpect allows easy control of interactive console applications." -marker = "sys_platform != \"win32\"" -name = "pexpect" -optional = false -python-versions = "*" -version = "4.7.0" - -[package.dependencies] -ptyprocess = ">=0.5" - -[[package]] -category = "dev" -description = "Tiny 'shelve'-like database with concurrency support" -name = "pickleshare" -optional = false -python-versions = "*" -version = "0.7.5" - [[package]] category = "main" description = "Python Imaging Library (Fork)" @@ -525,6 +408,9 @@ version = "0.12.0" [package.dependencies] importlib-metadata = ">=0.12" +[package.extras] +dev = ["pre-commit", "tox"] + [[package]] category = "main" description = "Python Lex & Yacc" @@ -533,18 +419,6 @@ optional = false python-versions = "*" version = "3.11" -[[package]] -category = "dev" -description = "Library for building powerful interactive command lines in Python" -name = "prompt-toolkit" -optional = false -python-versions = "*" -version = "2.0.9" - -[package.dependencies] -six = ">=1.9.0" -wcwidth = "*" - [[package]] category = "main" description = "Protocol Buffers" @@ -565,14 +439,8 @@ optional = false python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "5.6.3" -[[package]] -category = "dev" -description = "Run a subprocess in a pseudo terminal" -marker = "sys_platform != \"win32\"" -name = "ptyprocess" -optional = false -python-versions = "*" -version = "0.6.0" +[package.extras] +enum = ["enum34"] [[package]] category = "dev" @@ -637,14 +505,6 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "2.1.1" -[[package]] -category = "dev" -description = "Pygments is a syntax highlighting package written in Python." -name = "pygments" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -version = "2.4.2" - [[package]] category = "dev" description = "pylama -- Code audit tool for python" @@ -724,6 +584,9 @@ wcwidth = "*" python = ">=2.8" version = ">=4.0.0" +[package.extras] +testing = ["argcomplete", "hypothesis (>=3.56)", "nose", "requests", "mock"] + [[package]] category = "main" description = "Extensions to the standard Python datetime module" @@ -743,14 +606,6 @@ optional = false python-versions = "*" version = "2019.1" -[[package]] -category = "dev" -description = "Python bindings for 0MQ" -name = "pyzmq" -optional = false -python-versions = ">=2.7,!=3.0*,!=3.1*,!=3.2*" -version = "18.0.1" - [[package]] category = "main" description = "Qiskit provider for accessing the quantum devices and simulators at IBMQ" @@ -786,6 +641,10 @@ pylatexenc = ">=1.4" scipy = ">=1.0" sympy = ">=1.3" +[package.extras] +full-featured-simulators = ["qiskit-aer (>=0.1)"] +visualization = ["matplotlib (>=2.1)", "nxpd (>=0.2)", "ipywidgets (>=7.3.0)", "pydot"] + [[package]] category = "main" description = "Python HTTP for Humans." @@ -800,6 +659,10 @@ chardet = ">=3.0.2,<3.1.0" idna = ">=2.5,<2.9" urllib3 = ">=1.21.1,<1.25.0 || >1.25.0,<1.25.1 || >1.25.1,<1.26" +[package.extras] +security = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)"] +socks = ["PySocks (>=1.5.6,<1.5.7 || >1.5.7)", "win-inet-pton"] + [[package]] category = "main" description = "This package allows for HTTP NTLM authentication using the requests library." @@ -870,27 +733,6 @@ version = "1.4" [package.dependencies] mpmath = ">=0.19" -[[package]] -category = "dev" -description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." -name = "tornado" -optional = false -python-versions = ">= 3.5" -version = "6.0.2" - -[[package]] -category = "dev" -description = "Traitlets Python config system" -name = "traitlets" -optional = false -python-versions = "*" -version = "4.3.2" - -[package.dependencies] -decorator = "*" -ipython-genutils = "*" -six = "*" - [[package]] category = "dev" description = "a fork of Python 2 and 3 ast modules with type comment support" @@ -935,6 +777,10 @@ optional = false python-versions = "*" version = "1.22" +[package.extras] +secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"] +socks = ["PySocks (>=1.5.6,<1.5.7 || >1.5.7,<2.0)"] + [[package]] category = "dev" description = "Measures number of Terminal column cells of wide-character codes" @@ -967,24 +813,25 @@ optional = false python-versions = ">=2.7" version = "0.5.1" +[package.extras] +docs = ["sphinx", "jaraco.packaging (>=3.2)", "rst.linker (>=1.9)"] +testing = ["pathlib2", "contextlib2", "unittest2"] + [metadata] -content-hash = "ef2d6c5f5983834f5985bc7121c4e3a14fa1143aac0340566bddcaaaad955667" +content-hash = "432d177b4e1c25d1c57edbb077d1200ebaaa9ff2478834db6019aa43eaff948b" python-versions = ">=3.7.3" [metadata.hashes] -appnope = ["5b26757dc6f79a3b7dc9fab95359328d5747fcb2409d331ea66d0272b90ab2a0", "8b995ffe925347a2138d7ac0fe77155e4311a0ea6d6da4f5128fe4b3cbe5ed71"] asn1crypto = ["2f1adbb7546ed199e3c90ef23ec95c5cf3585bac7d11fb7eb562a3fe89c64e87", "9d5c20441baf0cb60a4ac34cc447c6c189024b6b4c6cd7877034f4965c464e49"] astroid = ["6560e1e1749f68c64a4b5dee4e091fce798d2f0d84ebe638cf0e0585a343acf4", "b65db1bbaac9f9f4d190199bb8680af6f6f84fd3769a5ea883df8a91fe68b4c4"] atomicwrites = ["03472c30eb2c5d1ba9227e4c2ca66ab8287fbfbbda3888aa93dc2e28fc6811b4", "75a9445bac02d8d058d5e1fe689654ba5a6556a1dfd8ce6ec55a0ed79866cfa6"] attrs = ["69c0dbf2ed392de1cb5ec704444b08a5ef81680a61cb899dc08127123af36a79", "f0b870f674851ecbfbbbd364d6b5cbdff9dcedbc7f3f5e18a6891057f21fe399"] -backcall = ["38ecd85be2c1e78f77fd91700c76e14667dc21e2713b63876c0eb901196e01e4", "bbbf4b1e5cd2bdb08f915895b51081c041bac22394fdfcfdfbe9f14b77c08bf2"] cachetools = ["428266a1c0d36dc5aca63a2d7c5942e88c2c898d72139fca0e97fdd2380517ae", "8ea2d3ce97850f31e4a08b0e2b5e6c34997d7216a9d2c98e0f3978630d4da69a"] certifi = ["59b7658e26ca9c7339e00f8f4636cdfe59d34fa37b9b04f6f9e9926b3cece1a5", "b26104d6835d1f5e49452a26eb2ff87fe7090b89dfcaee5ea2212697e1e1d7ae"] cffi = ["041c81822e9f84b1d9c401182e174996f0bae9991f33725d059b771744290774", "046ef9a22f5d3eed06334d01b1e836977eeef500d9b78e9ef693f9380ad0b83d", "066bc4c7895c91812eff46f4b1c285220947d4aa46fa0a2651ff85f2afae9c90", "066c7ff148ae33040c01058662d6752fd73fbc8e64787229ea8498c7d7f4041b", "2444d0c61f03dcd26dbf7600cf64354376ee579acad77aef459e34efcb438c63", "300832850b8f7967e278870c5d51e3819b9aad8f0a2c8dbe39ab11f119237f45", "34c77afe85b6b9e967bd8154e3855e847b70ca42043db6ad17f26899a3df1b25", "46de5fa00f7ac09f020729148ff632819649b3e05a007d286242c4882f7b1dc3", "4aa8ee7ba27c472d429b980c51e714a24f47ca296d53f4d7868075b175866f4b", "4d0004eb4351e35ed950c14c11e734182591465a33e960a4ab5e8d4f04d72647", "4e3d3f31a1e202b0f5a35ba3bc4eb41e2fc2b11c1eff38b362de710bcffb5016", "50bec6d35e6b1aaeb17f7c4e2b9374ebf95a8975d57863546fa83e8d31bdb8c4", "55cad9a6df1e2a1d62063f79d0881a414a906a6962bc160ac968cc03ed3efcfb", "5662ad4e4e84f1eaa8efce5da695c5d2e229c563f9d5ce5b0113f71321bcf753", "59b4dc008f98fc6ee2bb4fd7fc786a8d70000d058c2bbe2698275bc53a8d3fa7", "73e1ffefe05e4ccd7bcea61af76f36077b914f92b76f95ccf00b0c1b9186f3f9", "a1f0fd46eba2d71ce1589f7e50a9e2ffaeb739fb2c11e8192aa2b45d5f6cc41f", "a2e85dc204556657661051ff4bab75a84e968669765c8a2cd425918699c3d0e8", "a5457d47dfff24882a21492e5815f891c0ca35fefae8aa742c6c263dac16ef1f", "a8dccd61d52a8dae4a825cdbb7735da530179fea472903eb871a5513b5abbfdc", "ae61af521ed676cf16ae94f30fe202781a38d7178b6b4ab622e4eec8cefaff42", "b012a5edb48288f77a63dba0840c92d0504aa215612da4541b7b42d849bc83a3", "d2c5cfa536227f57f97c92ac30c8109688ace8fa4ac086d19d0af47d134e2909", "d42b5796e20aacc9d15e66befb7a345454eef794fdb0737d1af593447c6c8f45", "dee54f5d30d775f525894d67b1495625dd9322945e7fee00731952e0368ff42d", "e070535507bd6aa07124258171be2ee8dfc19119c28ca94c9dfb7efd23564512", "e1ff2748c84d97b065cc95429814cdba39bcbd77c9c85c89344b317dc0d9cbff", "ed851c75d1e0e043cbf5ca9a8e1b13c4c90f3fbd863dacb01c0808e2b5204201"] chardet = ["84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae", "fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691"] cirq = ["2b0d366285bdafd9f6713a67a327aab97628683448d73c13c5c09fc35043f088", "e235d758146bec6bb74f0f5783d735a1953e6dfe39c2569aee295f977a1485c4"] colorama = ["05eed71e2e327246ad6b38c540c4a3117230b19679b875190486ddd2d721422d", "f8ac84de7840f5b9c4e3347b3c1eaa50f7e49c2b07596221daec5edaabbd7c48"] -coverage = ["007eeef7e23f9473622f7d94a3e029a45d55a92a1f083f0f3512f5ab9a669b05", "0388c12539372bb92d6dde68b4627f0300d948965bbb7fc104924d715fdc0965", "079248312838c4c8f3494934ab7382a42d42d5f365f0cf7516f938dbb3f53f3f", "17307429935f96c986a1b1674f78079528833410750321d22b5fb35d1883828e", "1afccd7e27cac1b9617be8c769f6d8a6d363699c9b86820f40c74cfb3328921c", "2ad357d12971e77360034c1596011a03f50c0f9e1ecd12e081342b8d1aee2236", "2b4d7f03a8a6632598cbc5df15bbca9f778c43db7cf1a838f4fa2c8599a8691a", "2e1a5c6adebb93c3b175103c2f855eda957283c10cf937d791d81bef8872d6ca", "309d91bd7a35063ec7a0e4d75645488bfab3f0b66373e7722f23da7f5b0f34cc", "358d635b1fc22a425444d52f26287ae5aea9e96e254ff3c59c407426f44574f4", "3f4d0b3403d3e110d2588c275540649b1841725f5a11a7162620224155d00ba2", "43a155eb76025c61fc20c3d03b89ca28efa6f5be572ab6110b2fb68eda96bfea", "493082f104b5ca920e97a485913de254cbe351900deed72d4264571c73464cd0", "4c4f368ffe1c2e7602359c2c50233269f3abe1c48ca6b288dcd0fb1d1c679733", "5ff16548492e8a12e65ff3d55857ccd818584ed587a6c2898a9ebbe09a880674", "66f393e10dd866be267deb3feca39babba08ae13763e0fc7a1063cbe1f8e49f6", "700d7579995044dc724847560b78ac786f0ca292867447afda7727a6fbaa082e", "81912cfe276e0069dca99e1e4e6be7b06b5fc8342641c6b472cb2fed7de7ae18", "82cbd3317320aa63c65555aa4894bf33a13fb3a77f079059eb5935eea415938d", "845fddf89dca1e94abe168760a38271abfc2e31863fbb4ada7f9a99337d7c3dc", "87d942863fe74b1c3be83a045996addf1639218c2cb89c5da18c06c0fe3917ea", "9721f1b7275d3112dc7ccf63f0553c769f09b5c25a26ee45872c7f5c09edf6c1", "a4497faa4f1c0fc365ba05eaecfb6b5d24e3c8c72e95938f9524e29dadb15e76", "a7cfaebd8f24c2b537fa6a271229b051cdac9c1734bb6f939ccfc7c055689baa", "ab3508df9a92c1d3362343d235420d08e2662969b83134f8a97dc1451cbe5e84", "b0059630ca5c6b297690a6bf57bf2fdac1395c24b7935fd73ee64190276b743b", "b6cebae1502ce5b87d7c6f532fa90ab345cfbda62b95aeea4e431e164d498a3d", "bd4800e32b4c8d99c3a2c943f1ac430cbf80658d884123d19639bcde90dad44a", "cdd92dd9471e624cd1d8c1a2703d25f114b59b736b0f1f659a98414e535ffb3d", "d00e29b78ff610d300b2c37049a41234d48ea4f2d2581759ebcf67caaf731c31", "d1ee76f560c3c3e8faada866a07a32485445e16ed2206ac8378bd90dadffb9f0", "dd707a21332615108b736ef0b8513d3edaf12d2a7d5fc26cd04a169a8ae9b526", "e3ba9b14607c23623cf38f90b23f5bed4a3be87cbfa96e2e9f4eabb975d1e98b", "e9a0e1caed2a52f15c96507ab78a48f346c05681a49c5b003172f8073da6aa6b", "eea9135432428d3ca7ee9be86af27cb8e56243f73764a9b6c3e0bda1394916be", "f29841e865590af72c4b90d7b5b8e93fd560f5dea436c1d5ee8053788f9285de", "f3a5c6d054c531536a83521c00e5d4004f1e126e2e2556ce399bef4180fbe540", "f87f522bde5540d8a4b11df80058281ac38c44b13ce29ced1e294963dd51a8f8", "f8c55dd0f56d3d618dfacf129e010cbe5d5f94b6951c1b2f13ab1a2f79c284da", "f98b461cb59f117887aa634a66022c0bd394278245ed51189f63a036516e32de"] cryptography = ["24b61e5fcb506424d3ec4e18bca995833839bf13c59fc43e530e488f28d46b8c", "25dd1581a183e9e7a806fe0543f485103232f940fcfc301db65e630512cce643", "3452bba7c21c69f2df772762be0066c7ed5dc65df494a1d53a58b683a83e1216", "41a0be220dd1ed9e998f5891948306eb8c812b512dc398e5a01846d855050799", "5751d8a11b956fbfa314f6553d186b94aa70fdb03d8a4d4f1c82dcacf0cbe28a", "5f61c7d749048fa6e3322258b4263463bfccefecb0dd731b6561cb617a1d9bb9", "72e24c521fa2106f19623a3851e9f89ddfdeb9ac63871c7643790f872a305dfc", "7b97ae6ef5cba2e3bb14256625423413d5ce8d1abb91d4f29b6d1a081da765f8", "961e886d8a3590fd2c723cf07be14e2a91cf53c25f02435c04d39e90780e3b53", "96d8473848e984184b6728e2c9d391482008646276c3ff084a1bd89e15ff53a1", "ae536da50c7ad1e002c3eee101871d93abdc90d9c5f651818450a0d3af718609", "b0db0cecf396033abb4a93c95d1602f268b3a68bb0a9cc06a7cff587bb9a7292", "cfee9164954c186b191b91d4193989ca994703b2fff406f71cf454a2d3c7327e", "e6347742ac8f35ded4a46ff835c60e68c22a536a8ae5c4422966d06946b6d4c6", "f27d93f0139a3c056172ebb5d4f9056e770fdf0206c2f422ff2ebbad142e09ed", "f57b76e46a58b63d1c6375017f4564a28f19a5ca912691fd2e4261b3414b618d"] cycler = ["1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d", "cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"] decorator = ["86156361c50488b84a3f148056ea716ca587df2f0de1d34750d35c21312725de", "f069f3a01830ca754ba5258fde2278454a0b5b79e0d7f5c13b3b97e57d4acff6"] @@ -995,14 +842,8 @@ google-auth-httplib2 = ["098fade613c25b4527b2c08fa42d11f3c2037dda8995d86de074522 httplib2 = ["158fbd0ffbba536829d664bf3f32c4f45df41f8f791663665162dfaf21ffd075", "d1146939d270f1f1eb8cbf8f5aa72ff37d897faccca448582bb1e180aeb4c6b2"] idna = ["c357b3f628cf53ae2c4c05627ecc484553142ca23264e593d327bcde5e9c3407", "ea8b7f6188e6fa117537c3df7da9fc686d485087abf6ac197f9c46432f7e4a3c"] importlib-metadata = ["6dfd58dfe281e8d240937776065dd3624ad5469c835248219bd16cf2e12dbeb7", "cb6ee23b46173539939964df59d3d72c3e0c1b5d54b84f1d8a7e912fe43612db"] -ipykernel = ["346189536b88859937b5f4848a6fd85d1ad0729f01724a411de5cae9b618819c", "f0e962052718068ad3b1d8bcc703794660858f58803c3798628817f492a8769c"] -ipython = ["54c5a8aa1eadd269ac210b96923688ccf01ebb2d0f21c18c3c717909583579a8", "e840810029224b56cd0d9e7719dc3b39cf84d577f8ac686547c8ba7a06eeab26"] -ipython-genutils = ["72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8", "eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"] isort = ["c40744b6bc5162bbb39c1257fe298b7a393861d50978b565f3ccd9cb9de0182a", "f57abacd059dc3bd666258d1efb0377510a89777fda3e3274e3c01f7c03ae22d"] -jedi = ["2bb0603e3506f708e792c7f4ad8fc2a7a9d9c2d292a358fbbd58da531695595b", "2c6bcd9545c7d6440951b12b44d373479bf18123a401a52025cf98563fbd826c"] jsonschema = ["000e68abd33c972a5248544925a0cae7d1125f9bf6c58280d37546b946769a08", "6ff5f3180870836cae40f06fa10419f557208175f13ad7bc26caa77beb1f6e02"] -jupyter-client = ["b5f9cb06105c1d2d30719db5ffb3ea67da60919fb68deaefa583deccd8813551", "c44411eb1463ed77548bc2d5ec0d744c9b81c4a542d9637c7a52824e2121b987"] -jupyter-core = ["927d713ffa616ea11972534411544589976b2493fc7e09ad946e010aa7eb9970", "ba70754aa680300306c699790128f6fbd8c306ee5927976cbe48adacf240c0b7"] kiwisolver = 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"cd98476ce7bb4dcd6a7b101f5eecdc073dafea19f311e36eb8fba1a349346277", "ce64cfbea18c535176bdaa10ba740c0fc4c6d998a3f511c17bedb0ae4b3b167c", "dcbb59eac73fd454e8f2c5fba9e3d3320fd4707ed6a9d3ea3717924a6f0903ea", "dd67f34458ae716029e2a71ede998e9092493b62a519236ca52e3c5202096c87", "e3c96056eb5b7284a20e256cb0bf783c8f36ad82a4ae5434a7b7cd02384144a7", "f612d584d7a27e2f39e7b17878430a959c1bc09a74ba09db096b468558e5e126", "f6de8a7d6122297b81566e5bd4df37fd5d62bec14f8f90ebff8ede1c9726cd0a", "fa529d9261682b24c2aaa683667253175c9acebe0a31105394b221090da75832"] psutil = ["028a1ec3c6197eadd11e7b46e8cc2f0720dc18ac6d7aabdb8e8c0d6c9704f000", "503e4b20fa9d3342bcf58191bbc20a4a5ef79ca7df8972e6197cc14c5513e73d", "863a85c1c0a5103a12c05a35e59d336e1d665747e531256e061213e2e90f63f3", "954f782608bfef9ae9f78e660e065bd8ffcfaea780f9f2c8a133bb7cb9e826d7", "b6e08f965a305cd84c2d07409bc16fbef4417d67b70c53b299116c5b895e3f45", "bc96d437dfbb8865fc8828cf363450001cb04056bbdcdd6fc152c436c8a74c61", "cf49178021075d47c61c03c0229ac0c60d5e2830f8cab19e2d88e579b18cdb76", "d5350cb66690915d60f8b233180f1e49938756fb2d501c93c44f8fb5b970cc63", "eba238cf1989dfff7d483c029acb0ac4fcbfc15de295d682901f0e2497e6781a"] -ptyprocess = ["923f299cc5ad920c68f2bc0bc98b75b9f838b93b599941a6b63ddbc2476394c0", "d7cc528d76e76342423ca640335bd3633420dc1366f258cb31d05e865ef5ca1f"] py = ["64f65755aee5b381cea27766a3a147c3f15b9b6b9ac88676de66ba2ae36793fa", "dc639b046a6e2cff5bbe40194ad65936d6ba360b52b3c3fe1d08a82dd50b5e53"] pyasn1 = ["061442c60842f6d11051d4fdae9bc197b64bd41573a12234a753a0cb80b4f30b", "0ee2449bf4c4e535823acc25624c45a8b454f328d59d3f3eeb82d3567100b9bd", "5f9fb05c33e53b9a6ee3b1ed1d292043f83df465852bec876e93b47fd2df7eed", "65201d28e081f690a32401e6253cca4449ccacc8f3988e811fae66bd822910ee", "79b336b073a52fa3c3d8728e78fa56b7d03138ef59f44084de5f39650265b5ff", "8ec20f61483764de281e0b4aba7d12716189700debcfa9e7935780850bf527f3", "9458d0273f95d035de4c0d5e0643f25daba330582cc71bb554fe6969c015042a", "98d97a1833a29ca61cd04a60414def8f02f406d732f9f0bcb49f769faff1b699", "b00d7bfb6603517e189d1ad76967c7e805139f63e43096e5f871d1277f50aea5", "b06c0cfd708b806ea025426aace45551f91ea7f557e0c2d4fbd9a4b346873ce0", "d14d05984581770333731690f5453efd4b82e1e5d824a1d7976b868a2e5c38e8", "da2420fe13a9452d8ae97a0e478adde1dee153b11ba832a95b223a2ba01c10f7", "da6b43a8c9ae93bc80e2739efb38cc776ba74a886e3e9318d65fe81a8b8a2c6e"] pyasn1-modules = ["230730c6e63d283df75459b1b791d73648f801fd46ffcc9eb1abd16c67dfa3a6", "27f09b212203f820bc982937bd41952e856610dbd7c48d9366e8e63a551824c8", "490ed2974883c6e3d0ee53f53b32427f29ea030345c11d690788d1ed31ed666b", "49663b587853cd8783427d2fd115c862916bdd3c01656a8110ecd1950699e28f", "4df864e4dd01e600ffe280191a6630bb5b86d46382c1bcec4d03a700cb35c8b9", "6eeef742c31e285c23ebef32d8e0fee5e4ee1a563bb5171684621165b7e65627", "d1c66c80615ee74b1f3867d31b14e81f5f961a0e1afe5429838f21b5065d0161", "d7aa971a8cd79482ec5ae98705b54fdfaf834c24ed93ebc83f422c7700412b47", "e573fcf31e72c2ede48a58c8559fe9083cd007623c99a3eaf0c8f5719c09a2f8", "e980f089e3ec8116d6a5154c80f002ca941ad3446b5048a5b6d225f24ded85bb", "ef721f68f7951fab9b0404d42590f479e30d9005daccb1699b0a51bb4177db96", "f01c6899938f635b2ff4d158e760625416e20f03c612cfc9da7e97798c84e916", "f309b6c94724aeaf7ca583feb1cc70430e10d7551de5e36edfc1ae6909bcfb3c"] @@ -1034,7 +868,6 @@ pycodestyle = ["95a2219d12372f05704562a14ec30bc76b05a5b297b21a5dfe3f6fac3491ae56 pycparser = ["a988718abfad80b6b157acce7bf130a30876d27603738ac39f140993246b25b3"] pydocstyle = ["2258f9b0df68b97bf3a6c29003edc5238ff8879f1efb6f1999988d934e432bd8", "5741c85e408f9e0ddf873611085e819b809fca90b619f5fd7f34bd4959da3dd4", "ed79d4ec5e92655eccc21eb0c6cf512e69512b4a97d215ace46d17e4990f2039"] pyflakes = ["17dbeb2e3f4d772725c777fabc446d5634d1038f234e77343108ce445ea69ce0", "d976835886f8c5b31d47970ed689944a0262b5f3afa00a5a7b4dc81e5449f8a2"] -pygments = ["71e430bc85c88a430f000ac1d9b331d2407f681d6f6aec95e8bcfbc3df5b0127", "881c4c157e45f30af185c1ffe8d549d48ac9127433f2c380c24b84572ad66297"] pylama = ["9bae53ef9c1a431371d6a8dca406816a60d547147b60a4934721898f553b7d8f", "fd61c11872d6256b019ef1235be37b77c922ef37ac9797df6bd489996dddeb15"] pylatexenc = ["ef2d5260c38e2cb4d2829e8b918914a558557820d4f57cb6588a81e827de2bb3"] pylint = ["5d77031694a5fb97ea95e828c8d10fc770a1df6eb3906067aaed42201a8a6a09", "723e3db49555abaf9bf79dc474c6b9e2935ad82230b10c1138a71ea41ac0fff1"] @@ -1043,7 +876,6 @@ pyparsing = ["1873c03321fc118f4e9746baf201ff990ceb915f433f23b395f5580d1840cb2a", pytest = ["4a784f1d4f2ef198fe9b7aef793e9fa1a3b2f84e822d9b3a64a181293a572d45", "926855726d8ae8371803f7b2e6ec0a69953d9c6311fa7c3b6c1b929ff92d27da"] python-dateutil = ["7e6584c74aeed623791615e26efd690f29817a27c73085b78e4bad02493df2fb", "c89805f6f4d64db21ed966fda138f8a5ed7a4fdbc1a8ee329ce1b74e3c74da9e"] pytz = ["303879e36b721603cc54604edcac9d20401bdbe31e1e4fdee5b9f98d5d31dfda", "d747dd3d23d77ef44c6a3526e274af6efeb0a6f1afd5a69ba4d5be4098c8e141"] -pyzmq = ["1651e52ed91f0736afd6d94ef9f3259b5534ce8beddb054f3d5ca989c4ef7c4f", "5ccb9b3d4cd20c000a9b75689d5add8cd3bce67fcbd0f8ae1b59345247d803af", "5e120c4cd3872e332fb35d255ad5998ebcee32ace4387b1b337416b6b90436c7", "5e2a3707c69a7281a9957f83718815fd74698cba31f6d69f9ed359921f662221", "63d51add9af8d0442dc90f916baf98fdc04e3b0a32afec4bfc83f8d85e72959f", "65c5a0bdc49e20f7d6b03a661f71e2fda7a99c51270cafe71598146d09810d0d", "66828fabe911aa545d919028441a585edb7c9c77969a5fea6722ef6e6ece38ab", "7d79427e82d9dad6e9b47c0b3e7ae5f9d489b1601e3a36ea629bb49501a4daf3", "824ee5d3078c4eae737ffc500fbf32f2b14e6ec89b26b435b7834febd70120cf", "89dc0a83cccec19ff3c62c091e43e66e0183d1e6b4658c16ee4e659518131494", "8b319805f6f7c907b101c864c3ca6cefc9db8ce0791356f180b1b644c7347e4c", "90facfb379ab47f94b19519c1ecc8ec8d10813b69d9c163117944948bdec5d15", "a0a178c7420021fc0730180a914a4b4b3092ce9696ceb8e72d0f60f8ce1655dd", "a7a89591ae315baccb8072f216614b3e59aed7385aef4393a6c741783d6ee9cf", "ba2578f0ae582452c02ed9fac2dc477b08e80ce05d2c0885becf5fff6651ccb0", "c69b0055c55702f5b0b6b354133e8325b9a56dbc80e1be2d240bead253fb9825", "ca434e1858fe222380221ddeb81e86f45522773344c9da63c311d17161df5e06", "d4b8ecfc3d92f114f04d5c40f60a65e5196198b827503341521dda12d8b14939", "d706025c47b09a54f005953ebe206f6d07a22516776faa4f509aaff681cc5468", "d8f27e958f8a2c0c8ffd4d8855c3ce8ac3fa1e105f0491ce31729aa2b3229740", "dbd264298f76b9060ce537008eb989317ca787c857e23cbd1b3ddf89f190a9b1", "e926d66f0df8fdbf03ba20583af0f215e475c667fb033d45fd031c66c63e34c9", "efc3bd48237f973a749f7312f68062f1b4ca5c2032a0673ca3ea8e46aa77187b", "f59bc782228777cbfe04555707a9c56d269c787ed25d6d28ed9d0fbb41cb1ad2", "f8da5322f4ff5f667a0d5a27e871b560c6637153c81e318b35cb012b2a98835c"] qiskit-ibmq-provider = ["5fc05803ead012ed38601ae7fab5846ee23806929b1056a243c53ef615f92986"] qiskit-terra = ["00ec6540c6bd67bc9fbd0cfa96fe7e78b0ba880d2fbc4d9a0dd96e57e22cff5e", "1433898f50c50fcaf8479abf0fee5ddaf58600e7039b74dc2e5cd2b4c0d91cc0", "1bb07d9c9ae27c7cefca991b973489b3c25b0d1a3ee641f9112bd76b7a9742b2", "278ed6f44fb4d7602cfa99f23c8e64c44c05e3231179d457b5be69c599d8882c", "5e6a20bafb8da900edee07834530be92fdb5c3117ddab2094861a7959d81299a", "7901b111c2b699bac20a66d036e043915099a463576cda4808e6198bb61de95a", "839a58ec5a9847d0670cec54883bfefffa0b90e749ab2c26afdd640bbcd4b83e", "948dd75c6ea78356ea8e6e6cd55ed7d7c7c77f8b9c658b49c93009f2d8e27edb", "9ba5111fdd0c417f5257c703b6c64f3f1873c6538792e527ceb3f1cfbc558031", "abf2c59d4a3a5fab2f1d6c7a67118a178a55178c1e4d893ecca5b3dbb6271a76", "b1fc4c3b82ef72b53d37dfaf25489ffaa7601220e7e86d9a3a8563ca0d60f8dd", "b5334e8c8b4b8c5f26aba2f7a289d74e82add1ec8fdcda4d6600e25019c6cb53", "ba87d8e1f8b0a7f1152878f738d4279d5839cca8d51b9a6a512f4df34b7b8c52", "e4259ebda66dc753315b428be528002caf34ed6d01062de9794873c81763b286", "e51ef8b187006a81ad2eb677cade958cff6788b643f901e4f23c9e4319b6a5e3", "ffa218f1b14c736aae025c99aed58f9d38cf287766c00e7d78024c037e012fa0"] requests = ["11e007a8a2aa0323f5a921e9e6a2d7e4e67d9877e85773fba9ba6419025cbeb4", "9cf5292fcd0f598c671cfc1e0d7d1a7f13bb8085e9a590f48c010551dc6c4b31"] @@ -1054,8 +886,6 @@ six = ["3350809f0555b11f552448330d0b52d5f24c91a322ea4a15ef22629740f3761c", "d16a snowballstemmer = ["919f26a68b2c17a7634da993d91339e288964f93c274f1343e3bbbe2096e1128", "9f3bcd3c401c3e862ec0ebe6d2c069ebc012ce142cce209c098ccb5b09136e89"] sortedcontainers = ["566cf5f8dbada3aed99737a19d98f03d15d76bf2a6c27e4fb0f4a718a99be761", "fa96e9920a37bde76bfdcaca919a125c1d2e581af1137e25de54ee0da7835282"] sympy = ["71a11e5686ae7ab6cb8feb5bd2651ef4482f8fd43a7c27e645a165e4353b23e1", "f9b00ec76151c98470e84f1da2d7d03633180b71fb318428ddccce1c867d3eaa"] -tornado = ["1174dcb84d08887b55defb2cda1986faeeea715fff189ef3dc44cce99f5fca6b", "2613fab506bd2aedb3722c8c64c17f8f74f4070afed6eea17f20b2115e445aec", "44b82bc1146a24e5b9853d04c142576b4e8fa7a92f2e30bc364a85d1f75c4de2", "457fcbee4df737d2defc181b9073758d73f54a6cfc1f280533ff48831b39f4a8", "49603e1a6e24104961497ad0c07c799aec1caac7400a6762b687e74c8206677d", "8c2f40b99a8153893793559919a355d7b74649a11e59f411b0b0a1793e160bc0", "e1d897889c3b5a829426b7d52828fb37b28bc181cd598624e65c8be40ee3f7fa"] -traitlets = ["9c4bd2d267b7153df9152698efb1050a5d84982d3384a37b2c1f7723ba3e7835", "c6cb5e6f57c5a9bdaa40fa71ce7b4af30298fbab9ece9815b5d995ab6217c7d9"] typed-ast = ["18511a0b3e7922276346bcb47e2ef9f38fb90fd31cb9223eed42c85d1312344e", "262c247a82d005e43b5b7f69aff746370538e176131c32dda9cb0f324d27141e", "2b907eb046d049bcd9892e3076c7a6456c93a25bebfe554e931620c90e6a25b0", "354c16e5babd09f5cb0ee000d54cfa38401d8b8891eefa878ac772f827181a3c", "4e0b70c6fc4d010f8107726af5fd37921b666f5b31d9331f0bd24ad9a088e631", "630968c5cdee51a11c05a30453f8cd65e0cc1d2ad0d9192819df9978984529f4", "66480f95b8167c9c5c5c87f32cf437d585937970f3fc24386f313a4c97b44e34", "71211d26ffd12d63a83e079ff258ac9d56a1376a25bc80b1cdcdf601b855b90b", "95bd11af7eafc16e829af2d3df510cecfd4387f6453355188342c3e79a2ec87a", "bc6c7d3fa1325a0c6613512a093bc2a2a15aeec350451cbdf9e1d4bffe3e3233", "cc34a6f5b426748a507dd5d1de4c1978f2eb5626d51326e43280941206c209e1", "d755f03c1e4a51e9b24d899561fec4ccaf51f210d52abdf8c07ee2849b212a36", "d7c45933b1bdfaf9f36c579671fec15d25b06c8398f113dab64c18ed1adda01d", "d896919306dd0aa22d0132f62a1b78d11aaf4c9fc5b3410d3c666b818191630a", "ffde2fbfad571af120fcbfbbc61c72469e72f550d676c3342492a9dfdefb8f12"] typing = ["4027c5f6127a6267a435201981ba156de91ad0d1d98e9ddc2aa173453453492d", "57dcf675a99b74d64dacf6fba08fb17cf7e3d5fdff53d4a30ea2a5e7e52543d4", "a4c8473ce11a65999c8f59cb093e70686b6c84c98df58c1dae9b3b196089858a"] typing-extensions = ["07b2c978670896022a43c4b915df8958bec4a6b84add7f2c87b2b728bda3ba64", "f3f0e67e1d42de47b5c67c32c9b26641642e9170fe7e292991793705cd5fef7c", "fb2cd053238d33a8ec939190f30cfd736c00653a85a2919415cecf7dc3d9da71"] diff --git a/pyproject.toml b/pyproject.toml index 1aa9fe0f..8f744637 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,7 +41,6 @@ cirq = "^0.5.0" [tool.poetry.dev-dependencies] pytest = "*" -nbval = "*" pylama = "*" pylint = "*" pylint_runner = "*" diff --git a/setup.py b/setup.py index 973b2bc4..b8724f42 100644 --- a/setup.py +++ b/setup.py @@ -36,5 +36,5 @@ packages=['qctrlopencontrols', 'qctrlopencontrols.base', 'qctrlopencontrols.cirq', 'qctrlopencontrols.driven_controls', 'qctrlopencontrols.dynamic_decoupling_sequences', 'qctrlopencontrols.exceptions', 'qctrlopencontrols.globals', 'qctrlopencontrols.qiskit'], package_data={}, install_requires=['cirq==0.*,>=0.5.0', 'numpy==1.*,>=1.16.0', 'qiskit-ibmq-provider==0.*,>=0.2.2', 'qiskit-terra==0.*,>=0.8.1', 'scipy==1.*,>=1.3.0'], - extras_require={'dev': ['nbval', 'pylama', 'pylint', 'pylint-runner', 'pytest']}, + extras_require={'dev': ['pylama', 'pylint', 'pylint-runner', 'pytest']}, )