Test of Machine Learning at the CERN LINAC4

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One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared beforehand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed. 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Malta) ; <a href="https://cds.cern.ch/search?f=author&p=Vojskovic%2C%20Isabella&ln=fr">Vojskovic, Isabella</a> (CERN)</td></tr> <tr><td class="formatRecordLabel"> Publication </td><td style="padding-left:5px;">2022</td></tr> <tr><td class="formatRecordLabel"> Number of pages </td><td style="padding-left:5px;">5</td></tr> <tr><td class="formatRecordLabel"> In: </td><td style="padding-left:5px;"><a href="http://dx.doi.org/10.18429/JACoW-HB2021-TUEC4"><i>JACoW HB</i> 2021 (2022) 181-185</a> </a></td></tr> <tr><td class="formatRecordLabel"> In: </td><td style="padding-left:5px;"><a href="https://cds.cern.ch/record/2836051">64th ICFA Advanced Beam Dynamics Workshop on High Intensity and High Brightness Hadron Beams (HB 2021)</a>, Batavia, Illinois, United States, 4 - 9 Oct 2021, pp.181-185</td></tr> <tr><td class="formatRecordLabel"> DOI </td><td style="padding-left:5px;"><a href="http://dx.doi.org/10.18429/JACoW-HB2021-TUEC4" title="DOI" target="_blank">10.18429/JACoW-HB2021-TUEC4</a> <tr><td class="formatRecordLabel"> Subject category </td><td style="padding-left:5px;">Accelerators and Storage Rings</td></tr> <tr><td class="formatRecordLabel"> Accelerator/Facility, Experiment </td><td style="padding-left:5px;"><a href="https://cds.cern.ch/search?p=CERN%20LINAC4&f=693__a">CERN LINAC4</a></td></tr> <tr><td class="formatRecordLabel"> Abstract </td><td style="padding-left:5px;">The CERN H$^-$ linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared beforehand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed.</td></tr> <tr><td class="formatRecordLabel"> Copyright/License </td><td style="padding-left:5px;">publication: (License: <a href="http://creativecommons.org/licenses/by/3.0/">CC-BY-3.0</a>)</td></tr> </table> <br/>Corresponding record in: <a href="http://inspirehep.net/record/2075241">Inspire</a> <small> </small> <br/> <br/><br/><div align="right"><div style="padding-bottom:2px;padding-top:30px;"><span class="moreinfo" style="margin-right:10px;"> <a href="" class="moreinfo">Retour à la recherche</a> </span></div></div> <div class="bottom-left-folded"><div class="recordlastmodifiedbox" style="position:relative;margin-left:1px"> Notice créée le 2022-11-23, modifiée le 2022-11-23</div></div> <div class="bottom-right-folded" style="text-align:right;padding-bottom:2px;"> <span class="moreinfo" style="margin-right:10px;"><a href="/search?ln=fr&p=recid%3A2841807&rm=wrd" class="moreinfo">Notices similaires</a></span></div> </div> </div> </div> <br/> <br /> <div class="detailedrecordminipanel"> <div class="top-left"></div><div class="top-right"></div> <div class="inside"> <div id="detailedrecordminipanelfile" style="width:33%;float:left;text-align:center;margin-top:0"> <div><small class="detailedRecordActions">Fichiers:</small> <br /><a href="/record/2841807/files/document.pdf"><img style="border:none" src="/img/file-icon-text-34x48.gif" alt="Télécharger le document" /><br />PDF</a><br /></div> </div> <div id="detailedrecordminipanelreview" style="width:30%;float:left;text-align:center"> </div> <div id="detailedrecordminipanelactions" style="width:36%;float:right;text-align:right;"> <ul class="detailedrecordactions"> <li><a href="/yourbaskets/add?ln=fr&recid=2841807">Ajouter au panier personnel</a></li> <li>Exporter vers <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/hx?ln=fr">BibTeX</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/hm?ln=fr">MARC</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/xm?ln=fr">MARCXML</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/xd?ln=fr">DC</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/xe?ln=fr">EndNote</a>,  <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/xn?ln=fr">NLM</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2841807/export/xw?ln=fr">RefWorks</a> </li> </ul> <div style='padding-left: 13px;'>  <div id="bookmark"></div> <div id="bookmark_sciencewise"></div> <style type="text/css"> #bookmark_sciencewise, #bookmark {float: left;} #bookmark_sciencewise li {padding: 2px; width: 25px;} #bookmark_sciencewise ul, #bookmark ul {list-style-image: none;} </style> <script type="text/javascript" src="/js/jquery.bookmark.min.js"></script> <style type="text/css">@import "/css/jquery.bookmark.css";</style> <script type="text/javascript">// <![CDATA[ $.bookmark.addSite('sciencewise', 'ScienceWise.info', 'https://cds.cern.ch/img/sciencewise.png', 'en', 'bookmark', 'http://sciencewise.info/bookmarks/cds:2841807/add'); $('#bookmark_sciencewise').bookmark({sites: ['sciencewise']}); $('#bookmark').bookmark({ sites: ['facebook', 'twitter', 'linkedin', 'google_plusone'], icons: '/img/bookmarks.png', url: 'https://cds.cern.ch/record/2841807', addEmail: true, title: "Test of Machine Learning at the CERN LINAC4", description: "The CERN H$^-$ linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. 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Test of Machine Learning at the CERN LINAC4 - CERN Document Server