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Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC - CERN Document Server

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This scheme is planned to be used at the LHC to improve the betatron cleaning efficiency with high-intensity ion beams. Only particles with impinging angles below 2.5 urad relative to the crystalline planes can be efficiently channeled at the LHC nominal top energy of 7 Z TeV. For this reason, crystals must be kept in optimal alignment with respect to the circulating beam envelope to maximize the efficiency of the channeling process. Given the small angular acceptance, achieving optimal channeling conditions is particularly challenging. Furthermore, the different phases of the LHC operational cycle involve important dynamic changes of the local orbit and optics, requiring an optimized control of position and angle of the crystals relative to the beam. To this end, the possibility to apply machine learning to the alignment of the crystals, in a dedicated setup and in standard operation, is considered. In this paper, possible solutions for automatic adaptation to the changing beam parameters are highlighted and plans for the LHC ion runs starting in 2022 are discussed. D'Andrea, Marco; Azzopardi, Gabriella; Di Castro, Mario; Matheson, Eloise; Mirarchi, Daniele; Redaelli, Stefano; Ricci, Gianmarco; Valentino, Gianluca" /> <meta name="keywords" content="collimation, operation, collider, hadron, network" /> <script type="text/javascript" src="https://cds.cern.ch/js/jquery.min.js"></script> <!-- WebNews CSS library --> <link rel="stylesheet" href="https://cds.cern.ch/img/webnews.css" type="text/css" /> <!-- WebNews JS library --> <script type="text/javascript" src="https://cds.cern.ch/js/webnews.js?v=20131009"></script> <meta property="fb:app_id" content="137353533001720"/> <script type="text/x-mathjax-config"> MathJax.Hub.Config({ tex2jax: {inlineMath: [['$','$']], processEscapes: true}, showProcessingMessages: false, messageStyle: "none" }); </script> <script src="/MathJax/MathJax.js?config=TeX-AMS_CHTML" type="text/javascript"> </script> <!-- GoogleScholar --> <meta content="Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC" name="citation_title" /> <meta content="D'Andrea, Marco" name="citation_author" /> <meta content="Di Castro, Mario" name="citation_author" /> <meta content="Valentino, Gianluca" name="citation_author" /> <meta content="Mirarchi, Daniele" name="citation_author" /> <meta content="Redaelli, Stefano" name="citation_author" /> <meta content="Azzopardi, Gabriella" name="citation_author" /> <meta content="Matheson, Eloise" name="citation_author" /> <meta content="Ricci, Gianmarco" name="citation_author" /> <meta content="10.18429/JACoW-IPAC2022-TUPOTK061" name="citation_doi" /> <meta content="JACoW IPAC" name="citation_journal_title" /> <meta content="2022" name="citation_volume" /> <meta content="1362-1365" name="citation_firstpage" /> <meta content="2022" name="citation_publication_date" /> <meta name="citation_online_date" content="2023/01/11"> <meta content="10.18429/JACoW-IPAC2022-TUPOTK061" name="citation_doi" /> <meta name="citation_pdf_url" content="https://cds.cern.ch/record/2845883/files/document.pdf" /> <!-- OpenGraph --> <meta content="Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC" property="og:title" /> <meta content="website" property="og:type" /> <meta content="website" property="og:type" /> <meta content="https://cds.cern.ch/record/2845883" property="og:url" /> <meta content="CERN Document Server" property="og:site_name" /> <meta content="JACoW" property="og:description" /> <meta content="Crystal collimation relies on the use of bent crystals to coherently deflect halo particles onto dedicated collimator absorbers. 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Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC </td> </tr> </table> </div> <div class="pagebody"><div class="pagebodystripemiddle"> <div class="detailedrecordbox"> <div class="detailedrecordtabs"> <div> <ul class="detailedrecordtabs"><li class="on first"><a href="/record/2845883/?ln=en">Information </a></li><li class=""><a href="/record/2845883/files?ln=en">Files </a></li></ul> <div id="tabsSpacer" style="clear:both;height:0px">&nbsp;</div></div> </div> <div class="detailedrecordboxcontent"> <div class="top-left-folded"></div> <div class="top-right-folded"></div> <div class="inside"> <!--<div style="height:0.1em;">&nbsp;</div> <p class="notopgap">&nbsp;</p>--> <abbr class="unapi-id" title="2845883"></abbr> <style type="text/css"> <!-- ul.detailedrecordtabs li.on a{background-color:#4D94CC;color:#fff !important;border-bottom:1px solid #4D94CC!important;} div.detailedrecordboxcontent {padding-top:0px !important;} --> </style> <table class="formatRecordTableFullWidth" > <tr> <td class="formatRecordHeader" style="background-image: url('https://cds.cern.ch/img/journals.jpg');" colspan="2"> <!--YTD: record may have more than one 690C.a tag--> Article </td> </tr> <script type="text/javascript"> $( document ).ready(function() { $('.showAuthor').on('click', function() { var author = '<p>' + $(this).data('name') + '</p>'; var affiliation = $(this).data('affiliation') + '</br>'; var contribution = $(this).data('contribution') + '</br>'; $.magnificPopup.open({ items: { src: '<div id="ovelary-mathjax" class="overlay-white oc-content overlay-white-500">' + author + affiliation + contribution + '</div>', type: 'inline' }, callbacks: { open: function() { var div = document.getElementById("overlay-mathjax") MathJax.Hub.Queue(["Typeset", MathJax.Hub, div]); }, } }) }) }); </script> <tr><td class="formatRecordLabel"> Title </td><td style="padding-left:5px;"><b>Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC</b></td></tr> <tr><td class="formatRecordLabel"><span style="white-space:nowrap;"> Author(s) </span> </td><td style="padding-left:5px;"><a href="https://cds.cern.ch/search?f=author&amp;p=D%27Andrea%2C%20Marco&amp;ln=en">D'Andrea, Marco</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Azzopardi%2C%20Gabriella&amp;ln=en">Azzopardi, Gabriella</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Di%20Castro%2C%20Mario&amp;ln=en">Di Castro, Mario</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Matheson%2C%20Eloise&amp;ln=en">Matheson, Eloise</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Mirarchi%2C%20Daniele&amp;ln=en">Mirarchi, Daniele</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Redaelli%2C%20Stefano&amp;ln=en">Redaelli, Stefano</a> (CERN) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Ricci%2C%20Gianmarco&amp;ln=en">Ricci, Gianmarco</a> (CERN ; U. Rome La Sapienza (main)) ; <a href="https://cds.cern.ch/search?f=author&amp;p=Valentino%2C%20Gianluca&amp;ln=en">Valentino, Gianluca</a> (CERN ; Malta U.)</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;">4</td></tr> <tr><td class="formatRecordLabel"> In: </td><td style="padding-left:5px;"><a href="http://dx.doi.org/10.18429/JACoW-IPAC2022-TUPOTK061"><i>JACoW IPAC</i> 2022 (2022) 1362-1365</a> </a></td></tr> <tr><td class="formatRecordLabel"> In: </td><td style="padding-left:5px;"><a href="https://cds.cern.ch/record/2806400">13th International Particle Accelerator Conference (IPAC 2022)</a>, Bangkok, Thailand, 12 - 17 Jun 2022, pp.1362-1365</td></tr> <tr><td class="formatRecordLabel"> DOI </td><td style="padding-left:5px;"><a href="http://dx.doi.org/10.18429/JACoW-IPAC2022-TUPOTK061" title="DOI" target="_blank">10.18429/JACoW-IPAC2022-TUPOTK061</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%20LHC&amp;f=693__a">CERN LHC</a></td></tr> <tr><td class="formatRecordLabel"> Abstract </td><td style="padding-left:5px;">Crystal collimation relies on the use of bent crystals to coherently deflect halo particles onto dedicated collimator absorbers. This scheme is planned to be used at the LHC to improve the betatron cleaning efficiency with high-intensity ion beams. Only particles with impinging angles below 2.5 urad relative to the crystalline planes can be efficiently channeled at the LHC nominal top energy of 7 Z TeV. For this reason, crystals must be kept in optimal alignment with respect to the circulating beam envelope to maximize the efficiency of the channeling process. Given the small angular acceptance, achieving optimal channeling conditions is particularly challenging. Furthermore, the different phases of the LHC operational cycle involve important dynamic changes of the local orbit and optics, requiring an optimized control of position and angle of the crystals relative to the beam. To this end, the possibility to apply machine learning to the alignment of the crystals, in a dedicated setup and in standard operation, is considered. In this paper, possible solutions for automatic adaptation to the changing beam parameters are highlighted and plans for the LHC ion runs starting in 2022 are discussed.</td></tr> <tr><td class="formatRecordLabel"> Copyright/License </td><td style="padding-left:5px;"><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/2137258">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">Back to search</a> </span></div></div> <div class="bottom-left-folded"><div class="recordlastmodifiedbox" style="position:relative;margin-left:1px">&nbsp;Record created 2023-01-11, last modified 2023-01-11</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=en&amp;p=recid%3A2845883&amp;rm=wrd" class="moreinfo">Similar records</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">Fulltext:</small> <br /><a href="/record/2845883/files/document.pdf"><img style="border:none" src="/img/file-icon-text-34x48.gif" alt="Download fulltext" /><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=en&amp;recid=2845883">Add to personal basket</a></li> <li>Export as <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/hx?ln=en">BibTeX</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/hm?ln=en">MARC</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xm?ln=en">MARCXML</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xd?ln=en">DC</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xe?ln=en">EndNote</a>, <!-- <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xe8x?ln=en">EndNote (8-X)</a>,--> <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xn?ln=en">NLM</a>, <a style="text-decoration:underline;font-weight:normal" href="/record/2845883/export/xw?ln=en">RefWorks</a> </li> </ul> <div style='padding-left: 13px;'> <!-- JQuery Bookmark Button BEGIN --> <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:2845883/add'); $('#bookmark_sciencewise').bookmark({sites: ['sciencewise']}); $('#bookmark').bookmark({ sites: ['facebook', 'twitter', 'linkedin', 'google_plusone'], icons: '/img/bookmarks.png', url: 'https://cds.cern.ch/record/2845883', addEmail: true, title: "Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC", description: "Crystal collimation relies on the use of bent crystals to coherently deflect halo particles onto dedicated collimator absorbers. This scheme is planned to be used at the LHC to improve the betatron cleaning efficiency with high-intensity ion beams. Only particles with impinging angles below 2.5 urad relative to the crystalline planes can be efficiently channeled at the LHC nominal top energy of 7 Z TeV. For this reason, crystals must be kept in optimal alignment with respect to the circulating beam envelope to maximize the efficiency of the channeling process. Given the small angular acceptance, achieving optimal channeling conditions is particularly challenging. Furthermore, the different phases of the LHC operational cycle involve important dynamic changes of the local orbit and optics, requiring an optimized control of position and angle of the crystals relative to the beam. To this end, the possibility to apply machine learning to the alignment of the crystals, in a dedicated setup and in standard operation, is considered. 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