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README.md

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We use [GitHub issues](https://github.com/Qiskit/qiskit-iqx-tutorials/issues) for
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tracking requests and bugs. Please use our [Slack](https://qiskit.slack.com)
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for discussion and simple questions. To join our Slack community, use the
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[link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk).
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[link](https://join.slack.com/t/qiskit/shared_invite/enQtODQ2NTIyOTgwMTQ3LTI0NzM2NzkzZjJhNDgzZjY5MTQzNDY3MGNiZGQzNTNkZTE4Nzg1MjMwMmFjY2UwZTgyNDlmYWQwYmZjMjE1ZTM).
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For questions that are more suited for a forum, we use the Qiskit tag in the
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[Stack
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Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit).

qiskit/advanced/aer/1_aer_provider.ipynb

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qiskit/advanced/aer/2_device_noise_simulation.ipynb

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qiskit/advanced/aer/3_building_noise_models.ipynb

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qiskit/advanced/aer/4_custom_gate_noise.ipynb

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qiskit/advanced/aer/5_noise_transformation.ipynb

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"source": [
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"## Introduction\n",
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"\n",
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"This notebook shows how to use the Qiskit Aer `noise.utils.approximate_quantum_error` and `noise.utils. approximate_noise_model` to transform quantum noise channels into a different, more suitable, noise channel.\n",
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"This notebook shows how to use the Qiskit Aer utility functions `approximate_quantum_error` and `approximate_noise_model` to transform quantum noise channels into a different, more suitable, noise channel.\n",
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"\n",
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"Our guiding example is Clifford simulation. A Clifford simulator can efficiently simulate quantum computations which include gates only from a limited, non-universal set of gates (the Clifford gates). Not all quantum noises can be added to such simulations; hence, we aim to find a \"close\" noise channel which can be simulated in a Clifford simulator.\n",
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"\n",
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"We begin by importing the transformation functions."
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"We begin by importing the transformation functions from the Aer provider utilities"
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]
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},
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{
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},
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"outputs": [],
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"source": [
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"from qiskit.providers.aer.noise.utils import approximate_quantum_error\n",
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"from qiskit.providers.aer.noise.utils import approximate_noise_model"
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"from qiskit.providers.aer.utils import approximate_quantum_error\n",
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"from qiskit.providers.aer.utils import approximate_noise_model"
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]
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},
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{
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},
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"outputs": [],
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"source": [
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"from qiskit.providers.aer.noise.errors.standard_errors import amplitude_damping_error\n",
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"from qiskit.providers.aer.noise.errors.standard_errors import reset_error\n",
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"from qiskit.providers.aer.noise.errors.standard_errors import pauli_error"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2019-08-19T17:13:36.691234Z",
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"start_time": "2019-08-19T17:13:36.688533Z"
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}
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},
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"outputs": [],
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"source": [
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"import numpy as np"
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"import numpy as np\n",
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"\n",
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"# Import Aer QuantumError functions that will be used\n",
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"from qiskit.providers.aer.noise import amplitude_damping_error\n",
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"from qiskit.providers.aer.noise import reset_error\n",
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"from qiskit.providers.aer.noise import pauli_error"
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]
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},
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{
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"\n",
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"Given quantum channels $\\mathcal{E}_{1},\\dots,\\mathcal{E}_{r}$, and probabilities $p_1, p_2, \\dots, p_r$ such that $0\\le p_i \\le 1$ and $p_1+\\dots +p_r = 1$, a new quantum channel $\\mathcal{C}_\\mathcal{E}$ can be constructed such that $\\mathcal{C}_\\mathcal{E}(\\rho)$ has the effect of choosing the channel $\\mathcal{E}_i$ with probability $p_i$ and applying it to $\\rho$.\n",
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"\n",
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"The noise transformation module solves the following optimization problem: Given a channel $\\mathcal{C}$ (\"goal\") and a list of channels $\\mathcal{E}_{1},\\dots,\\mathcal{E}_{r}$, find the probabilities $p_1, p_2, \\dots, p_r$ minimizing $D(\\mathcal{C}, \\mathcal{C}_\\mathcal{E})$ according to some distance metric $D$ (the Hilbert-Schmidt metric is currently used).\n",
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"The noise transformation function solves the following optimization problem: Given a channel $\\mathcal{C}$ (\"goal\") and a list of channels $\\mathcal{E}_{1},\\dots,\\mathcal{E}_{r}$, find the probabilities $p_1, p_2, \\dots, p_r$ minimizing $D(\\mathcal{C}, \\mathcal{C}_\\mathcal{E})$ according to some distance metric $D$ (the Hilbert-Schmidt metric is currently used).\n",
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"\n",
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"To ensure the approximation is honest, in the sense that the approximate error channel serves as an \"upper bound\" for the actual error channel, we add the additional honesty constraint:\n",
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"\n",
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"metadata": {
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"end_time": "2019-08-19T17:13:57.085790Z",
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{
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"text/html": [
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"<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>0.14.0</td></tr><tr><td>Terra</td><td>0.11.0</td></tr><tr><td>Aer</td><td>0.3.4</td></tr><tr><td>Ignis</td><td>0.2.0</td></tr><tr><td>Aqua</td><td>0.6.1</td></tr><tr><td>IBM Q Provider</td><td>0.4.4</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.7.4 (default, Aug 9 2019, 18:34:13) [MSC v.1915 64 bit (AMD64)]</td></tr><tr><td>OS</td><td>Windows</td></tr><tr><td>CPUs</td><td>2</td></tr><tr><td>Memory (Gb)</td><td>7.9987335205078125</td></tr><tr><td colspan='2'>Tue Dec 10 15:59:30 2019 Eastern Standard Time</td></tr></table>"
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"<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>None</td></tr><tr><td>Terra</td><td>0.12.0.dev0+c028a28</td></tr><tr><td>Aer</td><td>0.4.0</td></tr><tr><td>Ignis</td><td>0.3.0.dev0+829207f</td></tr><tr><td>Aqua</td><td>0.7.0.dev0+2776c5d</td></tr><tr><td>IBM Q Provider</td><td>0.4.6rc1</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 14:38:56) \n",
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"[Clang 4.0.1 (tags/RELEASE_401/final)]</td></tr><tr><td>OS</td><td>Darwin</td></tr><tr><td>CPUs</td><td>6</td></tr><tr><td>Memory (Gb)</td><td>32.0</td></tr><tr><td colspan='2'>Wed Feb 05 11:32:35 2020 EST</td></tr></table>"
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"<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2019.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
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"<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2020.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
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qiskit/advanced/aer/8_pulse_simulator_duffing_model.ipynb

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qiskit/advanced/aqua/amplitude_estimation.ipynb

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"***\n",
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"### Contributors\n",
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"Stefan Woerner<sup>[1]</sup>, Daniel Egger<sup>[1]</sup>, Shaohan Hu<sup>[1]</sup>, Stephen Wood<sup>[1]</sup>, Marco Pistoia<sup>[1]</sup>\n",
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"### Affliation\n",
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"### Affiliation\n",
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"- <sup>[1]</sup>IBMQ"
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]
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qiskit/advanced/aqua/chemistry/dissociation_profile_of_molecule.ipynb

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"### Introduction\n",
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"\n",
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"One of the most compelling possibilities of quantum computation is the the simulation of other quantum systems. Quantum simulation of quantum systems encompasses a wide range of tasks, including most significantly:\n",
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"One of the most compelling possibilities of quantum computation is the simulation of other quantum systems. Quantum simulation of quantum systems encompasses a wide range of tasks, including most significantly:\n",
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" \n",
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"1. Simulation of the time evolution of quantum systems.\n",
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"\n",

qiskit/advanced/aqua/finance/index.ipynb

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"### Contributors\n",
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"Stefan Woerner<sup>[1]</sup>, Daniel Egger<sup>[1]</sup>, Christa Zoufal<sup>[1]</sup>, Andrea Simonetto<sup>[1]</sup>, Jakub Marecek<sup>[1]</sup>, Martin Mevissen<sup>[1]</sup>, Shaohan Hu<sup>[1]</sup>, Stephen Wood<sup>[1]</sup>, Marco Pistoia<sup>[1]</sup>\n",
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"\n",
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"### Affliation\n",
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"### Affiliation\n",
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"- <sup>[1]</sup>IBMQ"
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