Skip to content
This repository has been archived by the owner on Aug 21, 2023. It is now read-only.

Fixed Broken Links in "01_algorithms_introduction" tutorial. #1111

Merged
merged 2 commits into from
Jan 15, 2021
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
48 changes: 19 additions & 29 deletions tutorials/algorithms/01_algorithms_introduction.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -52,19 +52,9 @@
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\"> ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐\n",
"q_0: ┤ RY(θ[0]) ├─■─┤ RY(θ[2]) ├─■─┤ RY(θ[4]) ├─■─┤ RY(θ[6]) ├\n",
" ├──────────┤ │ ├──────────┤ │ ├──────────┤ │ ├──────────┤\n",
"q_1: ┤ RY(θ[1]) ├─■─┤ RY(θ[3]) ├─■─┤ RY(θ[5]) ├─■─┤ RY(θ[7]) ├\n",
" └──────────┘ └──────────┘ └──────────┘ └──────────┘</pre>"
],
"image/png": "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\n",
"text/plain": [
" ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐\n",
"q_0: ┤ RY(θ[0]) ├─■─┤ RY(θ[2]) ├─■─┤ RY(θ[4]) ├─■─┤ RY(θ[6]) ├\n",
" ├──────────┤ │ ├──────────┤ │ ├──────────┤ │ ├──────────┤\n",
"q_1: ┤ RY(θ[1]) ├─■─┤ RY(θ[3]) ├─■─┤ RY(θ[5]) ├─■─┤ RY(θ[7]) ├\n",
" └──────────┘ └──────────┘ └──────────┘ └──────────┘"
"<Figure size 507.852x144.48 with 1 Axes>"
]
},
"execution_count": 2,
Expand Down Expand Up @@ -128,7 +118,7 @@
"source": [
"Note: if you provide the backend directly then internally a QuantumInstance will be created from it, with default settings, so at all times the algorithms are working through a QuantumInstance.\n",
"\n",
"So now we would be able to call the [run()](https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.VQE.run.html) method, which is common to all algorithms and returns a result specific for the algorithm. In this case since VQE is a MinimumEigensolver we could use the [compute_mininum_eigenvalue()](https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.VQE.compute_minimum_eigenvalue.html) method. The latter is the interface of choice for the application modules, such as Chemistry and Optimization, in order that they can work interchangeably with any algorithm within the specific category."
"So now we would be able to call the [run()](https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.VQE.html#qiskit.aqua.algorithms.VQE.run) method, which is common to all algorithms and returns a result specific for the algorithm. In this case since VQE is a MinimumEigensolver we could use the [compute_mininum_eigenvalue()](https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.VQE.html#qiskit.aqua.algorithms.VQE.compute_minimum_eigenvalue) method. The latter is the interface of choice for the application modules, such as Chemistry and Optimization, in order that they can work interchangeably with any algorithm within the specific category."
]
},
{
Expand Down Expand Up @@ -184,16 +174,16 @@
" 'optimal_parameters': { Parameter(θ[0]): 4.296520551468743,\n",
" Parameter(θ[1]): 4.426962086704216,\n",
" Parameter(θ[2]): 0.5470753710293924,\n",
" Parameter(θ[3]): 6.09294789784282,\n",
" Parameter(θ[4]): -2.598325857134344,\n",
" Parameter(θ[5]): 1.5683261371389359,\n",
" Parameter(θ[7]): 0.3602072316165878,\n",
" Parameter(θ[6]): -4.717618235040379,\n",
" Parameter(θ[7]): 0.3602072316165878},\n",
" Parameter(θ[5]): 1.5683261371389359,\n",
" Parameter(θ[3]): 6.09294789784282,\n",
" Parameter(θ[4]): -2.598325857134344},\n",
" 'optimal_point': array([ 4.29652055, 4.42696209, 0.54707537, 6.0929479 , -2.59832586,\n",
" 1.56832614, -4.71761824, 0.36020723]),\n",
" 'optimal_value': -1.857275017559769,\n",
" 'optimizer_evals': 72,\n",
" 'optimizer_time': 2.040440559387207}\n"
" 'optimizer_time': 1.310880184173584}\n"
]
}
],
Expand Down Expand Up @@ -242,19 +232,19 @@
" 'eigenstate': array([-9.55448660e-05+2.12037105e-17j, 9.93766273e-01+2.25293943e-16j,\n",
" -1.11483565e-01+1.52657541e-16j, -1.77521351e-05+3.71607315e-17j]),\n",
" 'eigenvalue': (-1.857275017559769+0j),\n",
" 'optimal_parameters': { Parameter(θ[2]): 0.5470753710293924,\n",
" Parameter(θ[7]): 0.3602072316165878,\n",
" Parameter(θ[6]): -4.717618235040379,\n",
" Parameter(θ[3]): 6.09294789784282,\n",
" 'optimal_parameters': { Parameter(θ[4]): -2.598325857134344,\n",
" Parameter(θ[5]): 1.5683261371389359,\n",
" Parameter(θ[0]): 4.296520551468743,\n",
" Parameter(θ[6]): -4.717618235040379,\n",
" Parameter(θ[7]): 0.3602072316165878,\n",
" Parameter(θ[1]): 4.426962086704216,\n",
" Parameter(θ[4]): -2.598325857134344},\n",
" Parameter(θ[0]): 4.296520551468743,\n",
" Parameter(θ[2]): 0.5470753710293924,\n",
" Parameter(θ[3]): 6.09294789784282},\n",
" 'optimal_point': array([ 4.29652055, 4.42696209, 0.54707537, 6.0929479 , -2.59832586,\n",
" 1.56832614, -4.71761824, 0.36020723]),\n",
" 'optimal_value': -1.857275017559769,\n",
" 'optimizer_evals': 72,\n",
" 'optimizer_time': 1.5368030071258545}\n"
" 'optimizer_time': 2.8010470867156982}\n"
]
}
],
Expand Down Expand Up @@ -294,8 +284,8 @@
{
"data": {
"text/html": [
"<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>0.23.1</td></tr><tr><td>Terra</td><td>0.16.1</td></tr><tr><td>Aer</td><td>0.7.1</td></tr><tr><td>Ignis</td><td>0.5.1</td></tr><tr><td>Aqua</td><td>0.8.1</td></tr><tr><td>IBM Q Provider</td><td>0.11.1</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.6.1 |Continuum Analytics, Inc.| (default, May 11 2017, 13:09:58) \n",
"[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]</td></tr><tr><td>OS</td><td>Linux</td></tr><tr><td>CPUs</td><td>1</td></tr><tr><td>Memory (Gb)</td><td>5.827335357666016</td></tr><tr><td colspan='2'>Tue Nov 17 08:50:18 2020 EST</td></tr></table>"
"<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>0.23.1</td></tr><tr><td>Terra</td><td>0.16.1</td></tr><tr><td>Aer</td><td>0.7.1</td></tr><tr><td>Ignis</td><td>0.5.1</td></tr><tr><td>Aqua</td><td>0.8.1</td></tr><tr><td>IBM Q Provider</td><td>0.11.1</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 02:25:08) \n",
"[GCC 7.5.0]</td></tr><tr><td>OS</td><td>Linux</td></tr><tr><td>CPUs</td><td>8</td></tr><tr><td>Memory (Gb)</td><td>31.40900421142578</td></tr><tr><td colspan='2'>Fri Jan 15 12:11:24 2021 UTC</td></tr></table>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
Expand All @@ -307,7 +297,7 @@
{
"data": {
"text/html": [
"<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>"
"<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, 2021.</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>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
Expand Down Expand Up @@ -347,7 +337,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
"version": "3.7.8"
}
},
"nbformat": 4,
Expand Down