Search | arXiv e-print repository

<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"/> <meta name="viewport" content="width=device-width, initial-scale=1"/>  <link rel="apple-touch-icon" sizes="180x180" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/apple-touch-icon.png"> <link rel="icon" type="image/png" sizes="32x32" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/favicon-32x32.png"> <link rel="icon" type="image/png" sizes="16x16" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/favicon-16x16.png"> <link rel="manifest" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/site.webmanifest"> <link rel="mask-icon" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/safari-pinned-tab.svg" color="#b31b1b"> <link rel="shortcut icon" href="https://static.arxiv.org/static/base/1.0.0a5/images/icons/favicon.ico"> <meta name="msapplication-TileColor" content="#b31b1b"> <meta name="msapplication-config" content="images/icons/browserconfig.xml"> <meta name="theme-color" content="#b31b1b">  <title>Search | arXiv e-print repository</title> <script defer src="https://static.arxiv.org/static/base/1.0.0a5/fontawesome-free-5.11.2-web/js/all.js"></script> <link rel="stylesheet" href="https://static.arxiv.org/static/base/1.0.0a5/css/arxivstyle.css" /> <script type="text/x-mathjax-config"> MathJax.Hub.Config({ messageStyle: "none", extensions: ["tex2jax.js"], jax: ["input/TeX", "output/HTML-CSS"], tex2jax: { inlineMath: [ ['$','$'], ["\$","\$"] ], displayMath: [ ['$$','$$'], ["\\[","\\]"] ], processEscapes: true, ignoreClass: '.*', processClass: 'mathjax.*' }, TeX: { extensions: ["AMSmath.js", "AMSsymbols.js", "noErrors.js"], noErrors: { inlineDelimiters: ["$","$"], multiLine: false, style: { "font-size": "normal", "border": "" } } }, "HTML-CSS": { availableFonts: ["TeX"] } }); </script> <script src='//static.arxiv.org/MathJax-2.7.3/MathJax.js'></script> <script src="https://static.arxiv.org/static/base/1.0.0a5/js/notification.js"></script> <link rel="stylesheet" href="https://static.arxiv.org/static/search/0.5.6/css/bulma-tooltip.min.css" /> <link rel="stylesheet" href="https://static.arxiv.org/static/search/0.5.6/css/search.css" /> <script src="https://code.jquery.com/jquery-3.2.1.slim.min.js" integrity="sha256-k2WSCIexGzOj3Euiig+TlR8gA0EmPjuc79OEeY5L45g=" crossorigin="anonymous"></script> <script src="https://static.arxiv.org/static/search/0.5.6/js/fieldset.js"></script> <style> radio#cf-customfield_11400 { display: none; } </style> </head> <body> <header><a href="#main-container" class="is-sr-only">Skip to main content</a>  <div class="attribution level is-marginless" role="banner"> <div class="level-left"> <a class="level-item" href="https://cornell.edu/"><img src="https://static.arxiv.org/static/base/1.0.0a5/images/cornell-reduced-white-SMALL.svg" alt="Cornell University" width="200" aria-label="logo" /></a> </div> <div class="level-right is-marginless"><p class="sponsors level-item is-marginless"><span id="support-ack-url">We gratefully acknowledge support from<br /> the Simons Foundation, <a href="https://info.arxiv.org/about/ourmembers.html">member institutions</a>, and all contributors. <a href="https://info.arxiv.org/about/donate.html">Donate</a></span></p></div> </div>  <div class="identity level is-marginless"> <div class="level-left"> <div class="level-item"> <a class="arxiv" href="https://arxiv.org/" aria-label="arxiv-logo"> <img src="https://static.arxiv.org/static/base/1.0.0a5/images/arxiv-logo-one-color-white.svg" aria-label="logo" alt="arxiv logo" width="85" style="width:85px;"/> </a> </div> </div> <div class="search-block level-right"> <form class="level-item mini-search" method="GET" action="https://arxiv.org/search"> <div class="field has-addons"> <div class="control"> <input class="input is-small" type="text" name="query" placeholder="Search..." aria-label="Search term or terms" /> <p class="help"><a href="https://info.arxiv.org/help">Help</a> | <a href="https://arxiv.org/search/advanced">Advanced Search</a></p> </div> <div class="control"> <div class="select is-small"> <select name="searchtype" aria-label="Field to search"> <option value="all" selected="selected">All fields</option> <option value="title">Title</option> <option value="author">Author</option> <option value="abstract">Abstract</option> <option value="comments">Comments</option> <option value="journal_ref">Journal reference</option> <option value="acm_class">ACM classification</option> <option value="msc_class">MSC classification</option> <option value="report_num">Report number</option> <option value="paper_id">arXiv identifier</option> <option value="doi">DOI</option> <option value="orcid">ORCID</option> <option value="author_id">arXiv author ID</option> <option value="help">Help pages</option> <option value="full_text">Full text</option> </select> </div> </div> <input type="hidden" name="source" value="header"> <button class="button is-small is-cul-darker">Search</button> </div> </form> </div> </div>  <div class="container"> <div class="user-tools is-size-7 has-text-right has-text-weight-bold" role="navigation" aria-label="User menu"> <a href="https://arxiv.org/login">Login</a> </div> </div> </header> <main class="container" id="main-container"> <div class="level is-marginless"> <div class="level-left"> <h1 class="title is-clearfix"> Showing 1–22 of 22 results for author: <span class="mathjax">Dorigo, T</span> </h1> </div> <div class="level-right is-hidden-mobile">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> <div class="content"> <form method="GET" action="/search/physics" aria-role="search"> Searching in archive <strong>physics</strong>. <a href="/search/?searchtype=author&query=Dorigo%2C+T">Search in all archives.</a> <div class="field has-addons-tablet"> <div class="control is-expanded"> <label for="query" class="hidden-label">Search term or terms</label> <input class="input is-medium" id="query" name="query" placeholder="Search term..." type="text" value="Dorigo, T"> </div> <div class="select control is-medium"> <label class="is-hidden" for="searchtype">Field</label> <select class="is-medium" id="searchtype" name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> </div> <div class="control"> <button class="button is-link is-medium">Search</button> </div> </div> <div class="field"> <div class="control is-size-7"> <label class="radio"> <input checked id="abstracts-0" name="abstracts" type="radio" value="show"> Show abstracts </label> <label class="radio"> <input id="abstracts-1" name="abstracts" type="radio" value="hide"> Hide abstracts </label> </div> </div> <div class="is-clearfix" style="height: 2.5em"> <div class="is-pulled-right"> <a href="/search/advanced?terms-0-term=Dorigo%2C+T&terms-0-field=author&size=50&order=-announced_date_first">Advanced Search</a> </div> </div> <input type="hidden" name="order" value="-announced_date_first"> <input type="hidden" name="size" value="50"> </form> <div class="level breathe-horizontal"> <div class="level-left"> <form method="GET" action="/search/"> <div style="display: none;"> <select id="searchtype" name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Dorigo, T"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.10817">arXiv:2502.10817</a> <span> [<a href="https://arxiv.org/pdf/2502.10817">pdf</a>, <a href="https://arxiv.org/format/2502.10817">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Hadron Identification Prospects With Granular Calorimeters </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=De+Vita%2C+A">Andrea De Vita</a>, <a href="/search/physics?searchtype=author&query=Abhishek"> Abhishek</a>, <a href="/search/physics?searchtype=author&query=Aehle%2C+M">Max Aehle</a>, <a href="/search/physics?searchtype=author&query=Awais%2C+M">Muhammad Awais</a>, <a href="/search/physics?searchtype=author&query=Breccia%2C+A">Alessandro Breccia</a>, <a href="/search/physics?searchtype=author&query=Carroccio%2C+R">Riccardo Carroccio</a>, <a href="/search/physics?searchtype=author&query=Chen%2C+L">Long Chen</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Gauger%2C+N+R">Nicolas R. Gauger</a>, <a href="/search/physics?searchtype=author&query=Keidel%2C+R">Ralf Keidel</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Lupi%2C+E">Enrico Lupi</a>, <a href="/search/physics?searchtype=author&query=Nardi%2C+F">Federico Nardi</a>, <a href="/search/physics?searchtype=author&query=Nguyen%2C+X+T">Xuan Tung Nguyen</a>, <a href="/search/physics?searchtype=author&query=Sandin%2C+F">Fredrik Sandin</a>, <a href="/search/physics?searchtype=author&query=Schmidt%2C+K">Kylian Schmidt</a>, <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a>, <a href="/search/physics?searchtype=author&query=willmore%2C+J">Joseph willmore</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.10817v1-abstract-short" style="display: inline;"> In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a homogeneous lead tungstate calorimeter with high transverse and longitudinal segmentation, we investigated the discrimination of protons, positive pions, and positive ka… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.10817v1-abstract-full').style.display = 'inline'; document.getElementById('2502.10817v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.10817v1-abstract-full" style="display: none;"> In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a homogeneous lead tungstate calorimeter with high transverse and longitudinal segmentation, we investigated the discrimination of protons, positive pions, and positive kaons at 100 GeV. The analysis focuses on the impact of calorimeter granularity by progressively merging detector cells and extracting features like energy deposition patterns andtiming information. Two machine learning approaches, XGBoost and fully connected deep neural networks, were employed to assess the classification performance across particle pairs. The results indicate that fine segmentation improves particle discrimination, with higher granularity yielding more detailed characterization of energy showers. Additionally, the results highlight the importance of shower radius, energy fractions, and timing variables in distinguishing particle types. The XGBoost model demonstrated computational efficiency and interpretability advantages over deep learning for tabular data structures, while achieving similar classification performance. This motivates further work required to combine high- and low-level feature analysis, e.g., using convolutional and graph-based neural networks, and extending the study to a broader range of particle energies and types. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.10817v1-abstract-full').style.display = 'none'; document.getElementById('2502.10817v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.02152">arXiv:2502.02152</a> <span> [<a href="https://arxiv.org/pdf/2502.02152">pdf</a>, <a href="https://arxiv.org/format/2502.02152">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> End-to-End Detector Optimization with Diffusion models: A Case Study in Sampling Calorimeters </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Schmidt%2C+K">Kylian Schmidt</a>, <a href="/search/physics?searchtype=author&query=Kota%2C+N">Nikhil Kota</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=De+Vita%2C+A">Andrea De Vita</a>, <a href="/search/physics?searchtype=author&query=Klute%2C+M">Markus Klute</a>, <a href="/search/physics?searchtype=author&query=Abhishek"> Abhishek</a>, <a href="/search/physics?searchtype=author&query=Aehle%2C+M">Max Aehle</a>, <a href="/search/physics?searchtype=author&query=Awais%2C+M">Muhammad Awais</a>, <a href="/search/physics?searchtype=author&query=Breccia%2C+A">Alessandro Breccia</a>, <a href="/search/physics?searchtype=author&query=Carroccio%2C+R">Riccardo Carroccio</a>, <a href="/search/physics?searchtype=author&query=Chen%2C+L">Long Chen</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Gauger%2C+N+R">Nicolas R. Gauger</a>, <a href="/search/physics?searchtype=author&query=Lupi%2C+E">Enrico Lupi</a>, <a href="/search/physics?searchtype=author&query=Nardi%2C+F">Federico Nardi</a>, <a href="/search/physics?searchtype=author&query=Nguyen%2C+X+T">Xuan Tung Nguyen</a>, <a href="/search/physics?searchtype=author&query=Sandin%2C+F">Fredrik Sandin</a>, <a href="/search/physics?searchtype=author&query=Willmore%2C+J">Joseph Willmore</a>, <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.02152v1-abstract-short" style="display: inline;"> Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce the $\textit{end-to-end}$ optimization framework AIDO that leverages a diffusion model as a surrogate for the full simulation and reco… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.02152v1-abstract-full').style.display = 'inline'; document.getElementById('2502.02152v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.02152v1-abstract-full" style="display: none;"> Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce the $\textit{end-to-end}$ optimization framework AIDO that leverages a diffusion model as a surrogate for the full simulation and reconstruction chain, enabling gradient-based design exploration in both continuous and discrete parameter spaces. Although this framework is applicable to a broad range of detectors, we illustrate its power using the specific example of a sampling calorimeter, focusing on charged pions and photons as representative incident particles. Our results demonstrate that the diffusion model effectively captures critical performance metrics for calorimeter design, guiding the automatic search for layer arrangement and material composition that aligns with known calorimeter principles. The success of this proof-of-concept study provides a foundation for future applications of end-to-end optimization to more complex detector systems, offering a promising path toward systematically exploring the vast design space in next-generation experiments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.02152v1-abstract-full').style.display = 'none'; document.getElementById('2502.02152v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">14 pages, 9 figures, submitted to MDPI particles</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02966">arXiv:2411.02966</a> <span> [<a href="https://arxiv.org/pdf/2411.02966">pdf</a>, <a href="https://arxiv.org/format/2411.02966">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Accelerator Physics">physics.acc-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.5281/zenodo.13970100">10.5281/zenodo.13970100 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> MuCol Milestone Report No. 5: Preliminary Parameters </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Accettura%2C+C">Carlotta Accettura</a>, <a href="/search/physics?searchtype=author&query=Adrian%2C+S">Simon Adrian</a>, <a href="/search/physics?searchtype=author&query=Agarwal%2C+R">Rohit Agarwal</a>, <a href="/search/physics?searchtype=author&query=Ahdida%2C+C">Claudia Ahdida</a>, <a href="/search/physics?searchtype=author&query=Aim%C3%A9%2C+C">Chiara Aim茅</a>, <a href="/search/physics?searchtype=author&query=Aksoy%2C+A">Avni Aksoy</a>, <a href="/search/physics?searchtype=author&query=Alberghi%2C+G+L">Gian Luigi Alberghi</a>, <a href="/search/physics?searchtype=author&query=Alden%2C+S">Siobhan Alden</a>, <a href="/search/physics?searchtype=author&query=Alfonso%2C+L">Luca Alfonso</a>, <a href="/search/physics?searchtype=author&query=Amapane%2C+N">Nicola Amapane</a>, <a href="/search/physics?searchtype=author&query=Amorim%2C+D">David Amorim</a>, <a href="/search/physics?searchtype=author&query=Andreetto%2C+P">Paolo Andreetto</a>, <a href="/search/physics?searchtype=author&query=Anulli%2C+F">Fabio Anulli</a>, <a href="/search/physics?searchtype=author&query=Appleby%2C+R">Rob Appleby</a>, <a href="/search/physics?searchtype=author&query=Apresyan%2C+A">Artur Apresyan</a>, <a href="/search/physics?searchtype=author&query=Asadi%2C+P">Pouya Asadi</a>, <a href="/search/physics?searchtype=author&query=Mahmoud%2C+M+A">Mohammed Attia Mahmoud</a>, <a href="/search/physics?searchtype=author&query=Auchmann%2C+B">Bernhard Auchmann</a>, <a href="/search/physics?searchtype=author&query=Back%2C+J">John Back</a>, <a href="/search/physics?searchtype=author&query=Badea%2C+A">Anthony Badea</a>, <a href="/search/physics?searchtype=author&query=Bae%2C+K+J">Kyu Jung Bae</a>, <a href="/search/physics?searchtype=author&query=Bahng%2C+E+J">E. J. Bahng</a>, <a href="/search/physics?searchtype=author&query=Balconi%2C+L">Lorenzo Balconi</a>, <a href="/search/physics?searchtype=author&query=Balli%2C+F">Fabrice Balli</a>, <a href="/search/physics?searchtype=author&query=Bandiera%2C+L">Laura Bandiera</a> , et al. (369 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02966v1-abstract-short" style="display: inline;"> This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02966v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02966v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02966v1-abstract-full" style="display: none;"> This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02966v1-abstract-full').style.display = 'none'; document.getElementById('2411.02966v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.12450">arXiv:2407.12450</a> <span> [<a href="https://arxiv.org/pdf/2407.12450">pdf</a>, <a href="https://arxiv.org/format/2407.12450">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Accelerator Physics">physics.acc-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Interim report for the International Muon Collider Collaboration (IMCC) </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Accettura%2C+C">C. Accettura</a>, <a href="/search/physics?searchtype=author&query=Adrian%2C+S">S. Adrian</a>, <a href="/search/physics?searchtype=author&query=Agarwal%2C+R">R. Agarwal</a>, <a href="/search/physics?searchtype=author&query=Ahdida%2C+C">C. Ahdida</a>, <a href="/search/physics?searchtype=author&query=Aim%C3%A9%2C+C">C. Aim茅</a>, <a href="/search/physics?searchtype=author&query=Aksoy%2C+A">A. Aksoy</a>, <a href="/search/physics?searchtype=author&query=Alberghi%2C+G+L">G. L. Alberghi</a>, <a href="/search/physics?searchtype=author&query=Alden%2C+S">S. Alden</a>, <a href="/search/physics?searchtype=author&query=Amapane%2C+N">N. Amapane</a>, <a href="/search/physics?searchtype=author&query=Amorim%2C+D">D. Amorim</a>, <a href="/search/physics?searchtype=author&query=Andreetto%2C+P">P. Andreetto</a>, <a href="/search/physics?searchtype=author&query=Anulli%2C+F">F. Anulli</a>, <a href="/search/physics?searchtype=author&query=Appleby%2C+R">R. Appleby</a>, <a href="/search/physics?searchtype=author&query=Apresyan%2C+A">A. Apresyan</a>, <a href="/search/physics?searchtype=author&query=Asadi%2C+P">P. Asadi</a>, <a href="/search/physics?searchtype=author&query=Mahmoud%2C+M+A">M. Attia Mahmoud</a>, <a href="/search/physics?searchtype=author&query=Auchmann%2C+B">B. Auchmann</a>, <a href="/search/physics?searchtype=author&query=Back%2C+J">J. Back</a>, <a href="/search/physics?searchtype=author&query=Badea%2C+A">A. Badea</a>, <a href="/search/physics?searchtype=author&query=Bae%2C+K+J">K. J. Bae</a>, <a href="/search/physics?searchtype=author&query=Bahng%2C+E+J">E. J. Bahng</a>, <a href="/search/physics?searchtype=author&query=Balconi%2C+L">L. Balconi</a>, <a href="/search/physics?searchtype=author&query=Balli%2C+F">F. Balli</a>, <a href="/search/physics?searchtype=author&query=Bandiera%2C+L">L. Bandiera</a>, <a href="/search/physics?searchtype=author&query=Barbagallo%2C+C">C. Barbagallo</a> , et al. (362 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.12450v2-abstract-short" style="display: inline;"> The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accele… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.12450v2-abstract-full').style.display = 'inline'; document.getElementById('2407.12450v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.12450v2-abstract-full" style="display: none;"> The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.12450v2-abstract-full').style.display = 'none'; document.getElementById('2407.12450v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 January, 2025; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 17 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.02966">arXiv:2407.02966</a> <span> [<a href="https://arxiv.org/pdf/2407.02966">pdf</a>, <a href="https://arxiv.org/format/2407.02966">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> </div> </div> <p class="title is-5 mathjax"> Efficient Forward-Mode Algorithmic Derivatives of Geant4 </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Aehle%2C+M">Max Aehle</a>, <a href="/search/physics?searchtype=author&query=Nguyen%2C+X+T">Xuan Tung Nguyen</a>, <a href="/search/physics?searchtype=author&query=Nov%C3%A1k%2C+M">Mih谩ly Nov谩k</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Gauger%2C+N+R">Nicolas R. Gauger</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Klute%2C+M">Markus Klute</a>, <a href="/search/physics?searchtype=author&query=Vassilev%2C+V">Vassil Vassilev</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.02966v1-abstract-short" style="display: inline;"> We have applied an operator-overloading forward-mode algorithmic differentiation tool to the Monte-Carlo particle simulation toolkit Geant4. Our differentiated version of Geant4 allows computing mean pathwise derivatives of user-defined outputs of Geant4 applications with respect to user-defined inputs. This constitutes a major step towards enabling gradient-based optimization techniques in high-e… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.02966v1-abstract-full').style.display = 'inline'; document.getElementById('2407.02966v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.02966v1-abstract-full" style="display: none;"> We have applied an operator-overloading forward-mode algorithmic differentiation tool to the Monte-Carlo particle simulation toolkit Geant4. Our differentiated version of Geant4 allows computing mean pathwise derivatives of user-defined outputs of Geant4 applications with respect to user-defined inputs. This constitutes a major step towards enabling gradient-based optimization techniques in high-energy physics, as well as other application domains of Geant4. This is a preliminary report on the technical aspects of applying operator-overloading AD to Geant4, as well as a first analysis of some results obtained by our differentiated Geant4 prototype. We plan to follow up with a more refined analysis. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.02966v1-abstract-full').style.display = 'none'; document.getElementById('2407.02966v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.05673">arXiv:2310.05673</a> <span> [<a href="https://arxiv.org/pdf/2310.05673">pdf</a>, <a href="https://arxiv.org/format/2310.05673">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> </div> </div> <p class="title is-5 mathjax"> Progress in End-to-End Optimization of Detectors for Fundamental Physics with Differentiable Programming </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Aehle%2C+M">Max Aehle</a>, <a href="/search/physics?searchtype=author&query=Arsini%2C+L">Lorenzo Arsini</a>, <a href="/search/physics?searchtype=author&query=Barreiro%2C+R+B">R. Bel茅n Barreiro</a>, <a href="/search/physics?searchtype=author&query=Belias%2C+A">Anastasios Belias</a>, <a href="/search/physics?searchtype=author&query=Bury%2C+F">Florian Bury</a>, <a href="/search/physics?searchtype=author&query=Cebrian%2C+S">Susana Cebrian</a>, <a href="/search/physics?searchtype=author&query=Demin%2C+A">Alexander Demin</a>, <a href="/search/physics?searchtype=author&query=Dickinson%2C+J">Jennet Dickinson</a>, <a href="/search/physics?searchtype=author&query=Donini%2C+J">Julien Donini</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Doro%2C+M">Michele Doro</a>, <a href="/search/physics?searchtype=author&query=Gauger%2C+N+R">Nicolas R. Gauger</a>, <a href="/search/physics?searchtype=author&query=Giammanco%2C+A">Andrea Giammanco</a>, <a href="/search/physics?searchtype=author&query=Gray%2C+L">Lindsey Gray</a>, <a href="/search/physics?searchtype=author&query=Gonz%C3%A1lez%2C+B+S">Borja S. Gonz谩lez</a>, <a href="/search/physics?searchtype=author&query=Kain%2C+V">Verena Kain</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Kusch%2C+L">Lisa Kusch</a>, <a href="/search/physics?searchtype=author&query=Liwicki%2C+M">Marcus Liwicki</a>, <a href="/search/physics?searchtype=author&query=Maier%2C+G">Gernot Maier</a>, <a href="/search/physics?searchtype=author&query=Nardi%2C+F">Federico Nardi</a>, <a href="/search/physics?searchtype=author&query=Ratnikov%2C+F">Fedor Ratnikov</a>, <a href="/search/physics?searchtype=author&query=Roussel%2C+R">Ryan Roussel</a>, <a href="/search/physics?searchtype=author&query=de+Austri%2C+R+R">Roberto Ruiz de Austri</a>, <a href="/search/physics?searchtype=author&query=Sandin%2C+F">Fredrik Sandin</a> , et al. (5 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2310.05673v1-abstract-short" style="display: inline;"> In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance -- from the data-generating processes to their reconstruction and the ext… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.05673v1-abstract-full').style.display = 'inline'; document.getElementById('2310.05673v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.05673v1-abstract-full" style="display: none;"> In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance -- from the data-generating processes to their reconstruction and the extraction of inference on the parameters of interest of a measuring instrument -- along with the careful specification of a utility function well aligned with the end goals of the experiment. Building on previous studies originated within the MODE Collaboration, we focus specifically on applications involving instruments for particle physics experimentation, as well as industrial and medical applications that share the detection of radiation as their data-generating mechanism. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.05673v1-abstract-full').style.display = 'none'; document.getElementById('2310.05673v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">70 pages, 17 figures. To be submitted to journal</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2309.14027">arXiv:2309.14027</a> <span> [<a href="https://arxiv.org/pdf/2309.14027">pdf</a>, <a href="https://arxiv.org/format/2309.14027">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1088/2632-2153/ad52e7">10.1088/2632-2153/ad52e7 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> TomOpt: Differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a>, <a href="/search/physics?searchtype=author&query=Lagrange%2C+M">Maxime Lagrange</a>, <a href="/search/physics?searchtype=author&query=Orio%2C+A">Aitor Orio</a>, <a href="/search/physics?searchtype=author&query=Bordignon%2C+A">Anna Bordignon</a>, <a href="/search/physics?searchtype=author&query=Bury%2C+F">Florian Bury</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Giammanco%2C+A">Andrea Giammanco</a>, <a href="/search/physics?searchtype=author&query=Heikal%2C+M">Mariam Heikal</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Lamparth%2C+M">Max Lamparth</a>, <a href="/search/physics?searchtype=author&query=del+%C3%81rbol%2C+P+M+R">Pablo Mart铆nez Ru铆z del 脕rbol</a>, <a href="/search/physics?searchtype=author&query=Nardi%2C+F">Federico Nardi</a>, <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a>, <a href="/search/physics?searchtype=author&query=Zaraket%2C+H">Haitham Zaraket</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2309.14027v3-abstract-short" style="display: inline;"> We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The software exploits differentiable programming for the modeling of muon interactions with detectors and scanned volumes, the inference of volume properties, and the optimisation cycle performing the loss minimisation. In d… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.14027v3-abstract-full').style.display = 'inline'; document.getElementById('2309.14027v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2309.14027v3-abstract-full" style="display: none;"> We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The software exploits differentiable programming for the modeling of muon interactions with detectors and scanned volumes, the inference of volume properties, and the optimisation cycle performing the loss minimisation. In doing so, we provide the first demonstration of end-to-end-differentiable and inference-aware optimisation of particle physics instruments. We study the performance of the software on a relevant benchmark scenario and discuss its potential applications. Our code is available on Github. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.14027v3-abstract-full').style.display = 'none'; document.getElementById('2309.14027v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 25 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">V3: Updated to published version; 29 pages content + appendix + refs</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Mach. Learn.: Sci. Technol. 5 035002 (2024) </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.08533">arXiv:2303.08533</a> <span> [<a href="https://arxiv.org/pdf/2303.08533">pdf</a>, <a href="https://arxiv.org/format/2303.08533">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Accelerator Physics">physics.acc-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> </div> </div> <p class="title is-5 mathjax"> Towards a Muon Collider </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Accettura%2C+C">Carlotta Accettura</a>, <a href="/search/physics?searchtype=author&query=Adams%2C+D">Dean Adams</a>, <a href="/search/physics?searchtype=author&query=Agarwal%2C+R">Rohit Agarwal</a>, <a href="/search/physics?searchtype=author&query=Ahdida%2C+C">Claudia Ahdida</a>, <a href="/search/physics?searchtype=author&query=Aim%C3%A8%2C+C">Chiara Aim猫</a>, <a href="/search/physics?searchtype=author&query=Amapane%2C+N">Nicola Amapane</a>, <a href="/search/physics?searchtype=author&query=Amorim%2C+D">David Amorim</a>, <a href="/search/physics?searchtype=author&query=Andreetto%2C+P">Paolo Andreetto</a>, <a href="/search/physics?searchtype=author&query=Anulli%2C+F">Fabio Anulli</a>, <a href="/search/physics?searchtype=author&query=Appleby%2C+R">Robert Appleby</a>, <a href="/search/physics?searchtype=author&query=Apresyan%2C+A">Artur Apresyan</a>, <a href="/search/physics?searchtype=author&query=Apyan%2C+A">Aram Apyan</a>, <a href="/search/physics?searchtype=author&query=Arsenyev%2C+S">Sergey Arsenyev</a>, <a href="/search/physics?searchtype=author&query=Asadi%2C+P">Pouya Asadi</a>, <a href="/search/physics?searchtype=author&query=Mahmoud%2C+M+A">Mohammed Attia Mahmoud</a>, <a href="/search/physics?searchtype=author&query=Azatov%2C+A">Aleksandr Azatov</a>, <a href="/search/physics?searchtype=author&query=Back%2C+J">John Back</a>, <a href="/search/physics?searchtype=author&query=Balconi%2C+L">Lorenzo Balconi</a>, <a href="/search/physics?searchtype=author&query=Bandiera%2C+L">Laura Bandiera</a>, <a href="/search/physics?searchtype=author&query=Barlow%2C+R">Roger Barlow</a>, <a href="/search/physics?searchtype=author&query=Bartosik%2C+N">Nazar Bartosik</a>, <a href="/search/physics?searchtype=author&query=Barzi%2C+E">Emanuela Barzi</a>, <a href="/search/physics?searchtype=author&query=Batsch%2C+F">Fabian Batsch</a>, <a href="/search/physics?searchtype=author&query=Bauce%2C+M">Matteo Bauce</a>, <a href="/search/physics?searchtype=author&query=Berg%2C+J+S">J. Scott Berg</a> , et al. (272 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.08533v2-abstract-short" style="display: inline;"> A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders desi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.08533v2-abstract-full').style.display = 'inline'; document.getElementById('2303.08533v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.08533v2-abstract-full" style="display: none;"> A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.08533v2-abstract-full').style.display = 'none'; document.getElementById('2303.08533v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 15 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">118 pages, 103 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2301.10358">arXiv:2301.10358</a> <span> [<a href="https://arxiv.org/pdf/2301.10358">pdf</a>, <a href="https://arxiv.org/format/2301.10358">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> </div> </div> <p class="title is-5 mathjax"> Application of Inferno to a Top Pair Cross Section Measurement with CMS Open Data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Layer%2C+L">Lukas Layer</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2301.10358v1-abstract-short" style="display: inline;"> In recent years novel inference techniques have been developed based on the construction of non-linear summary statistics with neural networks by minimising inferencemotivated losses. One such technique is inferno (P. de Castro and T. Dorigo, Comp. Phys. Comm. 244 (2019) 170) which was shown on toy problems to outperform classical summary statistics for the problem of confidence interval estimatio… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.10358v1-abstract-full').style.display = 'inline'; document.getElementById('2301.10358v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2301.10358v1-abstract-full" style="display: none;"> In recent years novel inference techniques have been developed based on the construction of non-linear summary statistics with neural networks by minimising inferencemotivated losses. One such technique is inferno (P. de Castro and T. Dorigo, Comp. Phys. Comm. 244 (2019) 170) which was shown on toy problems to outperform classical summary statistics for the problem of confidence interval estimation in the presence of nuisance parameters. In order to test and benchmark the algorithm in a real world application, a full, systematics-dominated analysis produced by the CMS experiment, "Measurement of the top-antitop production cross section in the tau+jets channel in pp collisions at sqrt(s) = 7 TeV" (CMS Collaboration, The European Physical Journal C, 2013) is reproduced with CMS Open Data. The application of the inferno-powered neural network architecture to this analysis demonstrates the potential to reduce the impact of systematic uncertainties in real LHC analyses. This work also exemplifies the extent to which LHC analyses can be reproduced with open data. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.10358v1-abstract-full').style.display = 'none'; document.getElementById('2301.10358v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 January, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 8 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.13818">arXiv:2203.13818</a> <span> [<a href="https://arxiv.org/pdf/2203.13818">pdf</a>, <a href="https://arxiv.org/format/2203.13818">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> </div> </div> <p class="title is-5 mathjax"> Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Giammanco%2C+A">Andrea Giammanco</a>, <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a>, <a href="/search/physics?searchtype=author&query=Aehle%2C+M">Max Aehle</a>, <a href="/search/physics?searchtype=author&query=Bawaj%2C+M">Mateusz Bawaj</a>, <a href="/search/physics?searchtype=author&query=Boldyrev%2C+A">Alexey Boldyrev</a>, <a href="/search/physics?searchtype=author&query=Manzano%2C+P+d+C">Pablo de Castro Manzano</a>, <a href="/search/physics?searchtype=author&query=Derkach%2C+D">Denis Derkach</a>, <a href="/search/physics?searchtype=author&query=Donini%2C+J">Julien Donini</a>, <a href="/search/physics?searchtype=author&query=Edelen%2C+A">Auralee Edelen</a>, <a href="/search/physics?searchtype=author&query=Fanzago%2C+F">Federica Fanzago</a>, <a href="/search/physics?searchtype=author&query=Gauger%2C+N+R">Nicolas R. Gauger</a>, <a href="/search/physics?searchtype=author&query=Glaser%2C+C">Christian Glaser</a>, <a href="/search/physics?searchtype=author&query=Baydin%2C+A+G">At谋l谋m G. Baydin</a>, <a href="/search/physics?searchtype=author&query=Heinrich%2C+L">Lukas Heinrich</a>, <a href="/search/physics?searchtype=author&query=Keidel%2C+R">Ralf Keidel</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Krause%2C+C">Claudius Krause</a>, <a href="/search/physics?searchtype=author&query=Lagrange%2C+M">Maxime Lagrange</a>, <a href="/search/physics?searchtype=author&query=Lamparth%2C+M">Max Lamparth</a>, <a href="/search/physics?searchtype=author&query=Layer%2C+L">Lukas Layer</a>, <a href="/search/physics?searchtype=author&query=Maier%2C+G">Gernot Maier</a>, <a href="/search/physics?searchtype=author&query=Nardi%2C+F">Federico Nardi</a>, <a href="/search/physics?searchtype=author&query=Pettersen%2C+H+E+S">Helge E. S. Pettersen</a>, <a href="/search/physics?searchtype=author&query=Ramos%2C+A">Alberto Ramos</a> , et al. (11 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.13818v1-abstract-short" style="display: inline;"> The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, given the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.13818v1-abstract-full').style.display = 'inline'; document.getElementById('2203.13818v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.13818v1-abstract-full" style="display: none;"> The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, given the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, "experience-driven" layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized by means of a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this document we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.13818v1-abstract-full').style.display = 'none'; document.getElementById('2203.13818v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">109 pages, 32 figures. To be submitted to Reviews in Physics</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.08033">arXiv:2203.08033</a> <span> [<a href="https://arxiv.org/pdf/2203.08033">pdf</a>, <a href="https://arxiv.org/format/2203.08033">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Accelerator Physics">physics.acc-ph</span> </div> </div> <p class="title is-5 mathjax"> A Muon Collider Facility for Physics Discovery </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Stratakis%2C+D">D. Stratakis</a>, <a href="/search/physics?searchtype=author&query=Mokhov%2C+N">N. Mokhov</a>, <a href="/search/physics?searchtype=author&query=Palmer%2C+M">M. Palmer</a>, <a href="/search/physics?searchtype=author&query=Pastrone%2C+N">N. Pastrone</a>, <a href="/search/physics?searchtype=author&query=Raubenheimer%2C+T">T. Raubenheimer</a>, <a href="/search/physics?searchtype=author&query=Rogers%2C+C">C. Rogers</a>, <a href="/search/physics?searchtype=author&query=Schulte%2C+D">D. Schulte</a>, <a href="/search/physics?searchtype=author&query=Shiltsev%2C+V">V. Shiltsev</a>, <a href="/search/physics?searchtype=author&query=Tang%2C+J">J. Tang</a>, <a href="/search/physics?searchtype=author&query=Yamamoto%2C+A">A. Yamamoto</a>, <a href="/search/physics?searchtype=author&query=Aim%C3%A8%2C+C">C. Aim猫</a>, <a href="/search/physics?searchtype=author&query=Mahmoud%2C+M+A">M. A. Mahmoud</a>, <a href="/search/physics?searchtype=author&query=Bartosik%2C+N">N. Bartosik</a>, <a href="/search/physics?searchtype=author&query=Barzi%2C+E">E. Barzi</a>, <a href="/search/physics?searchtype=author&query=Bersani%2C+A">A. Bersani</a>, <a href="/search/physics?searchtype=author&query=Bertolin%2C+A">A. Bertolin</a>, <a href="/search/physics?searchtype=author&query=Bonesini%2C+M">M. Bonesini</a>, <a href="/search/physics?searchtype=author&query=Caiffi%2C+B">B. Caiffi</a>, <a href="/search/physics?searchtype=author&query=Casarsa%2C+M">M. Casarsa</a>, <a href="/search/physics?searchtype=author&query=Catanesi%2C+M+G">M. G. Catanesi</a>, <a href="/search/physics?searchtype=author&query=Cerri%2C+A">A. Cerri</a>, <a href="/search/physics?searchtype=author&query=Curatolo%2C+C">C. Curatolo</a>, <a href="/search/physics?searchtype=author&query=Dam%2C+M">M. Dam</a>, <a href="/search/physics?searchtype=author&query=Damerau%2C+H">H. Damerau</a>, <a href="/search/physics?searchtype=author&query=De+Matteis%2C+E">E. De Matteis</a> , et al. (44 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.08033v1-abstract-short" style="display: inline;"> Muon colliders provide a unique route to deliver high energy collisions that enable discovery searches and precision measurements to extend our understanding of the fundamental laws of physics. The muon collider design aims to deliver physics reach at the highest energies with costs, power consumption and on a time scale that may prove favorable relative to other proposed facilities. In this conte… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.08033v1-abstract-full').style.display = 'inline'; document.getElementById('2203.08033v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.08033v1-abstract-full" style="display: none;"> Muon colliders provide a unique route to deliver high energy collisions that enable discovery searches and precision measurements to extend our understanding of the fundamental laws of physics. The muon collider design aims to deliver physics reach at the highest energies with costs, power consumption and on a time scale that may prove favorable relative to other proposed facilities. In this context, a new international collaboration has formed to further extend the design concepts and performance studies of such a machine. This effort is focused on delivering the elements of a $\sim$10 TeV center of mass (CM) energy design to explore the physics energy frontier. The path to such a machine may pass through lower energy options. Currently a 3 TeV CM stage is considered. Other energy stages could also be explored, e.g. an s-channel Higgs Factory operating at 125 GeV CM. We describe the status of the R&D and design effort towards such a machine and lay out a plan to bring these concepts to maturity as a tool for the high energy physics community. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.08033v1-abstract-full').style.display = 'none'; document.getElementById('2203.08033v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">23 pages, 3 figures. arXiv admin note: text overlap with arXiv:2201.07895</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.07224">arXiv:2203.07224</a> <span> [<a href="https://arxiv.org/pdf/2203.07224">pdf</a>, <a href="https://arxiv.org/format/2203.07224">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Promising Technologies and R&D Directions for the Future Muon Collider Detectors </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Jindariani%2C+S">Sergo Jindariani</a>, <a href="/search/physics?searchtype=author&query=Meloni%2C+F">Federico Meloni</a>, <a href="/search/physics?searchtype=author&query=Pastrone%2C+N">Nadia Pastrone</a>, <a href="/search/physics?searchtype=author&query=Aim%C3%A8%2C+C">Chiara Aim猫</a>, <a href="/search/physics?searchtype=author&query=Bartosik%2C+N">Nazar Bartosik</a>, <a href="/search/physics?searchtype=author&query=Barzi%2C+E">Emanuela Barzi</a>, <a href="/search/physics?searchtype=author&query=Bertolin%2C+A">Alessandro Bertolin</a>, <a href="/search/physics?searchtype=author&query=Braghieri%2C+A">Alessandro Braghieri</a>, <a href="/search/physics?searchtype=author&query=Buonincontri%2C+L">Laura Buonincontri</a>, <a href="/search/physics?searchtype=author&query=Calzaferri%2C+S">Simone Calzaferri</a>, <a href="/search/physics?searchtype=author&query=Casarsa%2C+M">Massimo Casarsa</a>, <a href="/search/physics?searchtype=author&query=Catanesi%2C+M+G">Maria Gabriella Catanesi</a>, <a href="/search/physics?searchtype=author&query=Cerri%2C+A">Alessandro Cerri</a>, <a href="/search/physics?searchtype=author&query=Chachamis%2C+G">Grigorios Chachamis</a>, <a href="/search/physics?searchtype=author&query=Colaleo%2C+A">Anna Colaleo</a>, <a href="/search/physics?searchtype=author&query=Curatolo%2C+C">Camilla Curatolo</a>, <a href="/search/physics?searchtype=author&query=Da+Molin%2C+G">Giacomo Da Molin</a>, <a href="/search/physics?searchtype=author&query=Delahaye%2C+J">Jean-Pierre Delahaye</a>, <a href="/search/physics?searchtype=author&query=Di+Micco%2C+B">Biagio Di Micco</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Errico%2C+F">Filippo Errico</a>, <a href="/search/physics?searchtype=author&query=Fiorina%2C+D">Davide Fiorina</a>, <a href="/search/physics?searchtype=author&query=Gianelle%2C+A">Alessio Gianelle</a>, <a href="/search/physics?searchtype=author&query=Giraldin%2C+C">Carlo Giraldin</a>, <a href="/search/physics?searchtype=author&query=Hauptman%2C+J">John Hauptman</a> , et al. (36 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.07224v1-abstract-short" style="display: inline;"> Among the post-LHC generation of particle accelerators, the muon collider represents a unique machine with capability to provide very high energy leptonic collisions and to open the path to a vast and mostly unexplored physics programme. However, on the experimental side, such great physics potential is accompanied by unprecedented technological challenges, due to the fact that muons are unstable… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07224v1-abstract-full').style.display = 'inline'; document.getElementById('2203.07224v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.07224v1-abstract-full" style="display: none;"> Among the post-LHC generation of particle accelerators, the muon collider represents a unique machine with capability to provide very high energy leptonic collisions and to open the path to a vast and mostly unexplored physics programme. However, on the experimental side, such great physics potential is accompanied by unprecedented technological challenges, due to the fact that muons are unstable particles. Their decay products interact with the machine elements and produce an intense flux of background particles that eventually reach the detector and may degrade its performance. In this paper, we present technologies that have a potential to match the challenging specifications of a muon collider detector and outline a path forward for the future R&D efforts. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07224v1-abstract-full').style.display = 'none'; document.getElementById('2203.07224v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Contribution to Snowmass 2021, 27 pages, 15 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.02841">arXiv:2203.02841</a> <span> [<a href="https://arxiv.org/pdf/2203.02841">pdf</a>, <a href="https://arxiv.org/format/2203.02841">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> </div> </div> <p class="title is-5 mathjax"> Deep Regression of Muon Energy with a K-Nearest Neighbor Algorithm </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">T. Dorigo</a>, <a href="/search/physics?searchtype=author&query=Guglielmini%2C+S">Sofia Guglielmini</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Layer%2C+L">Lukas Layer</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.02841v1-abstract-short" style="display: inline;"> Within the context of studies for novel measurement solutions for future particle physics experiments, we developed a performant kNN-based regressor to infer the energy of highly-relativistic muons from the pattern of their radiation losses in a dense and granular calorimeter. The regressor is based on a pool of weak kNN learners, which learn by adapting weights and biases to each training event t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.02841v1-abstract-full').style.display = 'inline'; document.getElementById('2203.02841v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.02841v1-abstract-full" style="display: none;"> Within the context of studies for novel measurement solutions for future particle physics experiments, we developed a performant kNN-based regressor to infer the energy of highly-relativistic muons from the pattern of their radiation losses in a dense and granular calorimeter. The regressor is based on a pool of weak kNN learners, which learn by adapting weights and biases to each training event through stochastic gradient descent. The effective number of parameters optimized by the procedure is in the 60 millions range, thus comparable to that of large deep learning architectures. We test the performance of the regressor on the considered application by comparing it to that of several machine learning algorithms, showing comparable accuracy to that achieved by boosted decision trees and neural networks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.02841v1-abstract-full').style.display = 'none'; document.getElementById('2203.02841v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">38 pages, 14 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2107.02119">arXiv:2107.02119</a> <span> [<a href="https://arxiv.org/pdf/2107.02119">pdf</a>, <a href="https://arxiv.org/format/2107.02119">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1140/epjc/s10052-022-09993-5">10.1140/epjc/s10052-022-09993-5 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Calorimetric Measurement of Multi-TeV Muons via Deep Regression </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a>, <a href="/search/physics?searchtype=author&query=Chiandotto%2C+F">Filippo Chiandotto</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Layer%2C+L">Lukas Layer</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2107.02119v2-abstract-short" style="display: inline;"> The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find improved solutions for the detection, identification, and measurement of final-state particles in subnuclear collisions. One such challenge is the precise measurement of muon momentum at very high energy, where an estimate of the curvature provid… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.02119v2-abstract-full').style.display = 'inline'; document.getElementById('2107.02119v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2107.02119v2-abstract-full" style="display: none;"> The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find improved solutions for the detection, identification, and measurement of final-state particles in subnuclear collisions. One such challenge is the precise measurement of muon momentum at very high energy, where an estimate of the curvature provided by conceivable magnetic fields in realistic detectors proves insufficient for achieving good momentum resolution when detecting, e.g., a narrow, high mass resonance decaying to a muon pair. In this work we study the feasibility of an entirely new avenue for the measurement of the energy of muons based on their radiative losses in a dense, finely segmented calorimeter. This is made possible by exploiting spatial information of the clusters of energy from radiated photons in a regression task. The use of a task-specific deep learning architecture based on convolutional layers allows us to treat the problem as one akin to image reconstruction, where images are constituted by the pattern of energy released in successive layers of the calorimeter. A measurement of muon energy with better than 20% relative resolution is shown to be achievable for ultra-TeV muons. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.02119v2-abstract-full').style.display = 'none'; document.getElementById('2107.02119v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 5 July, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">V2 Updating to journal version</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2106.05747">arXiv:2106.05747</a> <span> [<a href="https://arxiv.org/pdf/2106.05747">pdf</a>, <a href="https://arxiv.org/format/2106.05747">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> RanBox: Anomaly Detection in the Copula Space </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Fumanelli%2C+M">Martina Fumanelli</a>, <a href="/search/physics?searchtype=author&query=Maccani%2C+C">Chiara Maccani</a>, <a href="/search/physics?searchtype=author&query=Mojsovska%2C+M">Marija Mojsovska</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a>, <a href="/search/physics?searchtype=author&query=Scarpa%2C+B">Bruno Scarpa</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2106.05747v1-abstract-short" style="display: inline;"> The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an otherwise more uniform population, is of relevance to applications ranging from fundamental research to industrial use cases. Motivated by the specific needs of searches for new phenomena in particle collisions, we propose a… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2106.05747v1-abstract-full').style.display = 'inline'; document.getElementById('2106.05747v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2106.05747v1-abstract-full" style="display: none;"> The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an otherwise more uniform population, is of relevance to applications ranging from fundamental research to industrial use cases. Motivated by the specific needs of searches for new phenomena in particle collisions, we propose a novel approach that targets signals of interest populating compact regions of the feature space. The method consists in a systematic scan of subspaces of a standardized copula of the feature space, where the minimum p-value of a hypothesis test of local uniformity is sought by gradient descent. We characterize the performance of the proposed algorithm and show its effectiveness in several experimental situations. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2106.05747v1-abstract-full').style.display = 'none'; document.getElementById('2106.05747v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 June, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">58 pages, 18 figures, 11 tables. To be submitted to Computer Physics Communications</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2105.07530">arXiv:2105.07530</a> <span> [<a href="https://arxiv.org/pdf/2105.07530">pdf</a>, <a href="https://arxiv.org/format/2105.07530">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1016/j.revip.2021.100063">10.1016/j.revip.2021.100063 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Stakia%2C+A">Anna Stakia</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Banelli%2C+G">Giovanni Banelli</a>, <a href="/search/physics?searchtype=author&query=Bortoletto%2C+D">Daniela Bortoletto</a>, <a href="/search/physics?searchtype=author&query=Casa%2C+A">Alessandro Casa</a>, <a href="/search/physics?searchtype=author&query=de+Castro%2C+P">Pablo de Castro</a>, <a href="/search/physics?searchtype=author&query=Delaere%2C+C">Christophe Delaere</a>, <a href="/search/physics?searchtype=author&query=Donini%2C+J">Julien Donini</a>, <a href="/search/physics?searchtype=author&query=Finos%2C+L">Livio Finos</a>, <a href="/search/physics?searchtype=author&query=Gallinaro%2C+M">Michele Gallinaro</a>, <a href="/search/physics?searchtype=author&query=Giammanco%2C+A">Andrea Giammanco</a>, <a href="/search/physics?searchtype=author&query=Held%2C+A">Alexander Held</a>, <a href="/search/physics?searchtype=author&query=Morales%2C+F+J">Fabricio Jim茅nez Morales</a>, <a href="/search/physics?searchtype=author&query=Kotkowski%2C+G">Grzegorz Kotkowski</a>, <a href="/search/physics?searchtype=author&query=Liew%2C+S+P">Seng Pei Liew</a>, <a href="/search/physics?searchtype=author&query=Maltoni%2C+F">Fabio Maltoni</a>, <a href="/search/physics?searchtype=author&query=Menardi%2C+G">Giovanna Menardi</a>, <a href="/search/physics?searchtype=author&query=Papavergou%2C+I">Ioanna Papavergou</a>, <a href="/search/physics?searchtype=author&query=Saggio%2C+A">Alessia Saggio</a>, <a href="/search/physics?searchtype=author&query=Scarpa%2C+B">Bruno Scarpa</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G+C">Giles C. Strong</a>, <a href="/search/physics?searchtype=author&query=Tosciri%2C+C">Cecilia Tosciri</a>, <a href="/search/physics?searchtype=author&query=Varela%2C+J">Jo茫o Varela</a>, <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a>, <a href="/search/physics?searchtype=author&query=Weiler%2C+A">Andreas Weiler</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2105.07530v2-abstract-short" style="display: inline;"> Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses per… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.07530v2-abstract-full').style.display = 'inline'; document.getElementById('2105.07530v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2105.07530v2-abstract-full" style="display: none;"> Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.07530v2-abstract-full').style.display = 'none'; document.getElementById('2105.07530v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 May, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">101 pages, 21 figures, submitted to Elsevier. [v2]: Updated to published version (in 'Reviews in Physics')</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Rev. Phys. 7 (2021) 100063 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2008.10958">arXiv:2008.10958</a> <span> [<a href="https://arxiv.org/pdf/2008.10958">pdf</a>, <a href="https://arxiv.org/format/2008.10958">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Muon Energy Measurement from Radiative Losses in a Calorimeter for a Collider Detector </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=Kieseler%2C+J">Jan Kieseler</a>, <a href="/search/physics?searchtype=author&query=Layer%2C+L">Lukas Layer</a>, <a href="/search/physics?searchtype=author&query=Strong%2C+G">Giles Strong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2008.10958v1-abstract-short" style="display: inline;"> The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find new solutions for the detection, identification, and measurement of final-state particles in subnuclear collisions. One such challenge is the precise measurement of muon momenta at very high energy, where the curvature provided by conceivable mag… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2008.10958v1-abstract-full').style.display = 'inline'; document.getElementById('2008.10958v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2008.10958v1-abstract-full" style="display: none;"> The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find new solutions for the detection, identification, and measurement of final-state particles in subnuclear collisions. One such challenge is the precise measurement of muon momenta at very high energy, where the curvature provided by conceivable magnetic fields in realistic detectors proves insufficient to achieve the desired resolution. In this work we show the feasibility of an entirely new avenue for the measurement of the energy of muons based on their radiative losses in a dense, finely segmented calorimeter. This is made possible by the use of the spatial information of the clusters of deposited photon energy in the regression task. Using a homogeneous lead-tungstate calorimeter as a benchmark, we show how energy losses may provide significant complementary information for the estimate of muon energies above 1 TeV. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2008.10958v1-abstract-full').style.display = 'none'; document.getElementById('2008.10958v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 August, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">20 pages, 12 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2007.09121">arXiv:2007.09121</a> <span> [<a href="https://arxiv.org/pdf/2007.09121">pdf</a>, <a href="https://arxiv.org/format/2007.09121">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> </div> </div> <p class="title is-5 mathjax"> Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a>, <a href="/search/physics?searchtype=author&query=de+Castro%2C+P">Pablo de Castro</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2007.09121v2-abstract-short" style="display: inline;"> In this work we discuss the impact of nuisance parameters on the effectiveness of machine learning in high-energy physics problems, and provide a review of techniques that allow to include their effect and reduce their impact in the search for optimal selection criteria and variable transformations. The introduction of nuisance parameters complicates the supervised learning task and its correspond… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.09121v2-abstract-full').style.display = 'inline'; document.getElementById('2007.09121v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2007.09121v2-abstract-full" style="display: none;"> In this work we discuss the impact of nuisance parameters on the effectiveness of machine learning in high-energy physics problems, and provide a review of techniques that allow to include their effect and reduce their impact in the search for optimal selection criteria and variable transformations. The introduction of nuisance parameters complicates the supervised learning task and its correspondence with the data analysis goal, due to their contribution degrading the model performances in real data, and the necessary addition of uncertainties in the resulting statistical inference. The approaches discussed include nuisance-parameterized models, modified or adversary losses, semi-supervised learning approaches, and inference-aware techniques. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.09121v2-abstract-full').style.display = 'none'; document.getElementById('2007.09121v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 January, 2021; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 17 July, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">43 pages, 5 figures. v1: original review manuscript. v2: text improvement/fixes from review process</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2002.09973">arXiv:2002.09973</a> <span> [<a href="https://arxiv.org/pdf/2002.09973">pdf</a>, <a href="https://arxiv.org/format/2002.09973">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Geometry Optimization of a Muon-Electron Scattering Experiment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2002.09973v1-abstract-short" style="display: inline;"> A high-statistics determination of the differential cross section of elastic muon-electron scattering as a function of the transferred four-momentum squared, $d 蟽_{el}(渭e \to 渭e)/dq^2$, has been argued to provide an effective constraint to the hadronic contribution to the running of the fine-structure constant, $螖伪_{had}$, a crucial input for precise theoretical predictions of the anomalous magnet… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.09973v1-abstract-full').style.display = 'inline'; document.getElementById('2002.09973v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2002.09973v1-abstract-full" style="display: none;"> A high-statistics determination of the differential cross section of elastic muon-electron scattering as a function of the transferred four-momentum squared, $d 蟽_{el}(渭e \to 渭e)/dq^2$, has been argued to provide an effective constraint to the hadronic contribution to the running of the fine-structure constant, $螖伪_{had}$, a crucial input for precise theoretical predictions of the anomalous magnetic moment of the muon. An experiment called ``MUonE'' is being planned at the north area of CERN for that purpose. We consider the geometry of the detector proposed by the MUonE collaboration and offer a few suggestions on the layout of the passive target material and on the placement of silicon strip sensors, based on a fast simulation of elastic muon-electron scattering events and the investigation of a number of possible solutions for the detector geometry. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.09973v1-abstract-full').style.display = 'none'; document.getElementById('2002.09973v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 23 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">54 pages, 25 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1806.04743">arXiv:1806.04743</a> <span> [<a href="https://arxiv.org/pdf/1806.04743">pdf</a>, <a href="https://arxiv.org/format/1806.04743">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Methodology">stat.ME</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1016/j.cpc.2019.06.007">10.1016/j.cpc.2019.06.007 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> INFERNO: Inference-Aware Neural Optimisation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=de+Castro%2C+P">Pablo de Castro</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1806.04743v2-abstract-short" style="display: inline;"> Complex computer simulations are commonly required for accurate data modelling in many scientific disciplines, making statistical inference challenging due to the intractability of the likelihood evaluation for the observed data. Furthermore, sometimes one is interested on inference drawn over a subset of the generative model parameters while taking into account model uncertainty or misspecificati… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1806.04743v2-abstract-full').style.display = 'inline'; document.getElementById('1806.04743v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1806.04743v2-abstract-full" style="display: none;"> Complex computer simulations are commonly required for accurate data modelling in many scientific disciplines, making statistical inference challenging due to the intractability of the likelihood evaluation for the observed data. Furthermore, sometimes one is interested on inference drawn over a subset of the generative model parameters while taking into account model uncertainty or misspecification on the remaining nuisance parameters. In this work, we show how non-linear summary statistics can be constructed by minimising inference-motivated losses via stochastic gradient descent such they provided the smallest uncertainty for the parameters of interest. As a use case, the problem of confidence interval estimation for the mixture coefficient in a multi-dimensional two-component mixture model (i.e. signal vs background) is considered, where the proposed technique clearly outperforms summary statistics based on probabilistic classification, which are a commonly used alternative but do not account for the presence of nuisance parameters. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1806.04743v2-abstract-full').style.display = 'none'; document.getElementById('1806.04743v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 October, 2018; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 12 June, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Code available at https://github.com/pablodecm/paper-inferno . Version updates: - v2: fixed typos, improve text, link to code and a better synthetic experiment</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1611.08256">arXiv:1611.08256</a> <span> [<a href="https://arxiv.org/pdf/1611.08256">pdf</a>, <a href="https://arxiv.org/format/1611.08256">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Analysis, Statistics and Probability">physics.data-an</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1051/epjconf/201713711009">10.1051/epjconf/201713711009 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Vischia%2C+P">Pietro Vischia</a>, <a href="/search/physics?searchtype=author&query=Dorigo%2C+T">Tommaso Dorigo</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1611.08256v1-abstract-short" style="display: inline;"> For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well mode… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1611.08256v1-abstract-full').style.display = 'inline'; document.getElementById('1611.08256v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1611.08256v1-abstract-full" style="display: none;"> For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well modeled process, and classify each event according to the frequency of it being part of such sub-samples. Comparisons with general MVA algorithms will be shown, as well as a study of the asymptotic properties of the method, making use of a public domain data set that models a typical search for new physics as performed at hadronic colliders such as the Large Hadron Collider (LHC). <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1611.08256v1-abstract-full').style.display = 'none'; document.getElementById('1611.08256v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 November, 2016; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2016. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 5 figures. Proceedings of the XIIth Quark Confinement and Hadron Spectrum conference, 28/8-2/9 2016, Thessaloniki, Greece</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1505.01824">arXiv:1505.01824</a> <span> [<a href="https://arxiv.org/pdf/1505.01824">pdf</a>, <a href="https://arxiv.org/format/1505.01824">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1088/1748-0221/11/04/P04023">10.1088/1748-0221/11/04/P04023 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Trapping in irradiated p-on-n silicon sensors at fluences anticipated at the HL-LHC outer tracker </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Adam%2C+W">W. Adam</a>, <a href="/search/physics?searchtype=author&query=Bergauer%2C+T">T. Bergauer</a>, <a href="/search/physics?searchtype=author&query=Dragicevic%2C+M">M. Dragicevic</a>, <a href="/search/physics?searchtype=author&query=Friedl%2C+M">M. Friedl</a>, <a href="/search/physics?searchtype=author&query=Fruehwirth%2C+R">R. Fruehwirth</a>, <a href="/search/physics?searchtype=author&query=Hoch%2C+M">M. Hoch</a>, <a href="/search/physics?searchtype=author&query=Hrubec%2C+J">J. Hrubec</a>, <a href="/search/physics?searchtype=author&query=Krammer%2C+M">M. Krammer</a>, <a href="/search/physics?searchtype=author&query=Treberspurg%2C+W">W. Treberspurg</a>, <a href="/search/physics?searchtype=author&query=Waltenberger%2C+W">W. Waltenberger</a>, <a href="/search/physics?searchtype=author&query=Alderweireldt%2C+S">S. Alderweireldt</a>, <a href="/search/physics?searchtype=author&query=Beaumont%2C+W">W. Beaumont</a>, <a href="/search/physics?searchtype=author&query=Janssen%2C+X">X. Janssen</a>, <a href="/search/physics?searchtype=author&query=Luyckx%2C+S">S. Luyckx</a>, <a href="/search/physics?searchtype=author&query=Van+Mechelen%2C+P">P. Van Mechelen</a>, <a href="/search/physics?searchtype=author&query=Van+Remortel%2C+N">N. Van Remortel</a>, <a href="/search/physics?searchtype=author&query=Van+Spilbeeck%2C+A">A. Van Spilbeeck</a>, <a href="/search/physics?searchtype=author&query=Barria%2C+P">P. Barria</a>, <a href="/search/physics?searchtype=author&query=Caillol%2C+C">C. Caillol</a>, <a href="/search/physics?searchtype=author&query=Clerbaux%2C+B">B. Clerbaux</a>, <a href="/search/physics?searchtype=author&query=De+Lentdecker%2C+G">G. De Lentdecker</a>, <a href="/search/physics?searchtype=author&query=Dobur%2C+D">D. Dobur</a>, <a href="/search/physics?searchtype=author&query=Favart%2C+L">L. Favart</a>, <a href="/search/physics?searchtype=author&query=Grebenyuk%2C+A">A. Grebenyuk</a>, <a href="/search/physics?searchtype=author&query=Lenzi%2C+T">Th. Lenzi</a> , et al. (663 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1505.01824v1-abstract-short" style="display: inline;"> The degradation of signal in silicon sensors is studied under conditions expected at the CERN High-Luminosity LHC. 200 $渭$m thick n-type silicon sensors are irradiated with protons of different energies to fluences of up to $3 \cdot 10^{15}$ neq/cm$^2$. Pulsed red laser light with a wavelength of 672 nm is used to generate electron-hole pairs in the sensors. The induced signals are used to determi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1505.01824v1-abstract-full').style.display = 'inline'; document.getElementById('1505.01824v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1505.01824v1-abstract-full" style="display: none;"> The degradation of signal in silicon sensors is studied under conditions expected at the CERN High-Luminosity LHC. 200 $渭$m thick n-type silicon sensors are irradiated with protons of different energies to fluences of up to $3 \cdot 10^{15}$ neq/cm$^2$. Pulsed red laser light with a wavelength of 672 nm is used to generate electron-hole pairs in the sensors. The induced signals are used to determine the charge collection efficiencies separately for electrons and holes drifting through the sensor. The effective trapping rates are extracted by comparing the results to simulation. The electric field is simulated using Synopsys device simulation assuming two effective defects. The generation and drift of charge carriers are simulated in an independent simulation based on PixelAV. The effective trapping rates are determined from the measured charge collection efficiencies and the simulated and measured time-resolved current pulses are compared. The effective trapping rates determined for both electrons and holes are about 50% smaller than those obtained using standard extrapolations of studies at low fluences and suggests an improved tracker performance over initial expectations. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1505.01824v1-abstract-full').style.display = 'none'; document.getElementById('1505.01824v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 May, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> 2016 JINST 11 P04023 </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul class="nav-spaced"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> <a href="https://info.arxiv.org/help/contact.html"> Contact</a> </li> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>subscribe to arXiv mailings</title><desc>Click here to subscribe</desc><path d="M476 3.2L12.5 270.6c-18.1 10.4-15.8 35.6 2.2 43.2L121 358.4l287.3-253.2c5.5-4.9 13.3 2.6 8.6 8.3L176 407v80.5c0 23.6 28.5 32.9 42.5 15.8L282 426l124.6 52.2c14.2 6 30.4-2.9 33-18.2l72-432C515 7.8 493.3-6.8 476 3.2z"/></svg> <a href="https://info.arxiv.org/help/subscribe"> Subscribe</a> </li> </ul> </div> </div> </div>   <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/help/license/index.html">Copyright</a></li> <li><a href="https://info.arxiv.org/help/policies/privacy_policy.html">Privacy Policy</a></li> </ul> </div> <div class="column sorry-app-links"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/help/web_accessibility.html">Web Accessibility Assistance</a></li> <li> <p class="help"> <a class="a11y-main-link" href="https://status.arxiv.org" target="_blank">arXiv Operational Status <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 256 512" class="icon filter-dark_grey" role="presentation"><path d="M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z"/></svg></a><br> Get status notifications via <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/email/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg>email</a> or <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/slack/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" class="icon filter-black" role="presentation"><path d="M94.12 315.1c0 25.9-21.16 47.06-47.06 47.06S0 341 0 315.1c0-25.9 21.16-47.06 47.06-47.06h47.06v47.06zm23.72 0c0-25.9 21.16-47.06 47.06-47.06s47.06 21.16 47.06 47.06v117.84c0 25.9-21.16 47.06-47.06 47.06s-47.06-21.16-47.06-47.06V315.1zm47.06-188.98c-25.9 0-47.06-21.16-47.06-47.06S139 32 164.9 32s47.06 21.16 47.06 47.06v47.06H164.9zm0 23.72c25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06H47.06C21.16 243.96 0 222.8 0 196.9s21.16-47.06 47.06-47.06H164.9zm188.98 47.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06h-47.06V196.9zm-23.72 0c0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06V79.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06V196.9zM283.1 385.88c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06v-47.06h47.06zm0-23.72c-25.9 0-47.06-21.16-47.06-47.06 0-25.9 21.16-47.06 47.06-47.06h117.84c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06H283.1z"/></svg>slack</a> </p> </li> </ul> </div> </div> </div>  </div> </footer> <script src="https://static.arxiv.org/static/base/1.0.0a5/js/member_acknowledgement.js"></script> </body> </html>

CINXE.COM

Search | arXiv e-print repository