[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122688-en":3,"doc-seo-122688-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122688,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Jet quenching with machine learning - Overview","Machine learning techniques are applied to study jet quenching in heavy ion collisions and to extract properties of the quark-gluon plasma (QGP). The overview reviews tasks such as jet momentum reconstruction, classification of quenched versus unquenched jets, identification of jet energy loss, localization of jet creation points, and discrimination between quark- and gluon-initiated jets. Jet-by-jet analysis aims to reduce selection bias, improve jet reconstruction and selection, and advance jet tomographic probes of the QGP.","arXiv :2308 . 10035v1 [hep-ph] 19 Aug 2023  \nOverview: Jet quenching with machine learning  \nYi-Lun Du∗  \nShandong Institute of Advanced Technology, Jinan 250100, China  \nE-mail: [yilun.du@iat.cn](yilun.du@iat.cn)  \nJets are suppressed and modified in heavy ion collisions, which serve as powerful probes to the properties of the quark-gluon plasma (QGP) . Attributed to the abundant information carried by the jet constituents and reconstructed substructures, plenty of interesting applications of machine learning techniques have been made on a jet-by-jet basis to study the jet quenching phenomena. Here wereview recent proceedings on this topic includingthe tasks ofreconstructingjet momentum in heavy ion collisions, classifying quenched jets and unquenched jets, identifying jet energy loss, locating the jet creation points as well as distinguishing between quark-and gluon-initiated jets in the QGP. Such jet-by-jet analyses will allow us to have a better handle on the jet reconstruction and selections to investigate the effects of jet modifications and push forward the long-standing goal of jet tomographic probes of the QGP.  \nHardProbes2023 26-31 March 2023 Ascha􀀛enburg, Germany  \n∗ Speaker  \n© Copyright owned by the author(s) under the terms of the Creative Commons  \nAttribution-NonCommercial-NoDerivatives 4 .0 International License (CC BY-NC-ND 4 .0) . [https://pos.sissa.it/](https://pos.sissa.it/)  \nOverview: Jet quenching with machine learning Yi-Lun Du  \n1. Introduction  \nQCD predicts that nuclear matter will form a new state of matter, i.e., quark-gluon plasma (QGP) at high temperature and density where quarks and gluons are deconfined from hadronic matter to form a strongly-coupled viscous fluid. The experiments of relativistic heavy ion collisions are conducted at RHIC and LHC to explore the nature of the new state of matter. In high-energy particle collisions, jets are collimated sprays of hadrons generated in a hard QCD process. While in heavy ion collisions, energetic partons will lose energy via the interactions with the QGP during their passage. The lost energy will hadronize and be redistributed around the energetic partons. These processes will quench the jet energy and modify the jet substructures. Besides, the interactions of QGP with high-energy partons will also generate the excitation or response of the medium. Mach cones are also expected to form in the expanding QGP when the energetic partons traverse the hot medium at a velocity faster than the speed of sound. Eventually some particles from the medium will stay inside the jets, which poses a challenge to the background subtraction of jets in heavy ion collisions. With such interesting interplay between jets and the QGP, high-energy hadrons or jets are employed as unique probes to the properties of the QGP [1, 2] . Jet quenching is clearly manifest when calculating the ratio of the yields of high-energy hadrons or jets between those measured in heavy ion collisions and proton-proton collisions [3–5] .  \nAdditionally, one can also study the medium modifications of jets by analyzing their substructures, again usually done by comparing the results of jets measured in nucleus-nucleus collisions against those measured in proton-proton collisions. However, when comparing the quenched jets and unquenched jets at the same final, measured energy range, one needs to take into account the presence of a selection bias. Due to the steeply falling jet spectrum, jets losing too much energy will be under-represented after imposing the selection criteria. In other words, the selected, surviving jet samples generally possess the characteristics of the jet substructures that tend to lose less energy, hindering in this way our interpretation about what true medium-induced modifications of jet substructures are. These ambiguities affecting a typical analysis could be mitigated if one can estimate the jet energy loss on a jet-by-jet basis, which allow us to classify and select them accordi","cbCaieQdQVorlevT","https://ap.wps.com/l/cbCaieQdQVorlevT","pdf",160786,1,11,"English","en",105,"# Introduction\n## Jet-medium interactions and quenching observables\n## Selection bias and jet-by-jet energy loss estimation\n## Toward QGP tomography with jet analyses\n## Machine learning applications to jet studies","[{\"question\":\"What physical problem does the document address?\",\"answer\":\"It addresses jet quenching and jet modification caused by interactions between high-energy partons and the quark-gluon plasma in heavy ion collisions.\"},{\"question\":\"Why is selection bias an issue when comparing quenched and unquenched jets?\",\"answer\":\"Because the jet spectrum falls steeply, jets that lose too much energy are under-represented after applying selection criteria, biasing the observed jet substructures toward those losing less energy.\"},{\"question\":\"Which jet-by-jet tasks are highlighted for machine learning approaches?\",\"answer\":\"The overview highlights reconstructing jet momentum, classifying quenched versus unquenched jets, identifying jet energy loss, locating jet creation points, and distinguishing quark- versus gluon-initiated jets in the QGP.\"}]","Jet quenching with machine learning - Overview | PDF",1785812239,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"jet-quenching-with-machine-learning-overview","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/jet-quenching-with-machine-learning-overview/122688/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What physical problem does the document address?","Question",{"text":75,"@type":76},"It addresses jet quenching and jet modification caused by interactions between high-energy partons and the quark-gluon plasma in heavy ion collisions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why is selection bias an issue when comparing quenched and unquenched jets?",{"text":80,"@type":76},"Because the jet spectrum falls steeply, jets that lose too much energy are under-represented after applying selection criteria, biasing the observed jet substructures toward those losing less energy.",{"name":82,"@type":73,"acceptedAnswer":83},"Which jet-by-jet tasks are highlighted for machine learning approaches?",{"text":84,"@type":76},"The overview highlights reconstructing jet momentum, classifying quenched versus unquenched jets, identifying jet energy loss, locating jet creation points, and distinguishing quark- versus gluon-initiated jets in the QGP.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]