AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider
AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider
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DOI：
10.1016/j.nima.2022.167748
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
C. Fanelli;Z. Papandreou;K. Suresh;J. K. Adkins;Y. Akiba;A. Albataineh;M. Amaryan;I. Arsene;C. Gayoso;J. Bae;X. Bai;M. Baker;M. Bashkanov;R. Bellwied;F. Benmokhtar;V. Berdnikov;J. Bernauer;F. Bock;W. Boeglin;M. Borysova;E. Brash;P. Brindza;W. Briscoe;M. Brooks;S. Bueltmann;M. Bukhari;A. Bylinkin;R. Capobianco;W. Chang;Y. Cheon;K. Chen;K.F. Chen;K. Cheng;M. Chiu;T. Chujo;Z. Citron;E. Cline;E. Cohen;T. Cormier;Y. Morales;C. Cotton;J. Crafts;C. Crawford;S. Creekmore;C.Cuevas;J. Cunningham;G. David;C. Dean;M. Demarteau;S. Diehl;N. Doshita;R. Dupré;J. Durham;R. Dzhygadlo;R. Ehlers;Lamiaa El Fassi;A. Emmert;R. Ent;R. Fatémi;S. Fegan;M. Finger;M. Finger;J. Frantz;M. Friedman;I. Friščić;D. Gangadharan;S. Gardner;K. Gates;F. Geurts;R. Gilman;D. Glazier;E. Glimos;Y. Goto;N. Grau;S. Greene;A. Guo;L. Guo;S. Ha;J. Haggerty;T. Hayward;X. He;O. Hen;D. Higinbotham;P. H. Hopchev;T. Horn;A. Hoghmrtsyan;P. J. Hsu;J. Huang;G. Huber;A. Hutson;K. Hwang;C. Hyde;M. Inaba;T. Iwata;H. Jo;K. Joo;N. Kalantarians;G. Kalicy;K. Kawade;S. Kay;A. Kim;B. Kim;C. Kim;M. Kim;Y. Kim;E. Kistenev;V. Klimenko;S. Ko;I. Korover;W. Korsch;G. Krintiras;S. Kuhn;C. Kuo;T. Kutz;J. Lajoie;D. Lawrence;S. Lebedev;H. Lee;J. Lee;S. W. Lee;Y. Lee;W. Li;W. Li;X. Li;Y. Liang;S. Lim;C. Lin;D. Lin;K. Liu;M. Liu;K. Livingston;N. Liyanage;W. Llope;C. Loizides;E. Long;R. Lu;Z. Lu;W. Lynch;D. Marchand;M. Marcisovsky;P. Markowitz;H. Marukyan;P. McGaughey;M. Mihovilovič;R. Milner;A. Milov;Y. Miyachi;A. Mkrtchyan;P. Monaghan;R. Montgomery;D. Morrison;A. Movsisyan;H. Mkrtchyan;C. Camacho;M. Murray;K. Nagai;J. Nagle;I. Nakagawa;C. Nattrass;D. Nguyen;S. Niccolai;R. Nouicer;G. Nukazuka;M. Nycz;V. Okorokov;S. Orešić;J. Osborn;C. O'Shaughnessy;S. Paganis;S. Pate;M. Patel;C. Paus;G. Penman;M. Perdekamp;D. Perepelitsa;H. D. Costa;K. Peters;W. Phelps;E. Piasetzky;C. Pinkenburg;I. Procházka;T. Protzman;M. Purschke;J. Putschke;J. Pybus;R. Rajput-Ghoshal;J. Rasson;B. Raue;K. Read;K. Røed;R. Reed;J. Reinhold;E. Renner;J. Richards;C. Riedl;T. Rinn;J. Roche;G. Roland;G. Ron;M. Rosati;C. Royon;J. Ryu;S. Salur;N. Santiesteban;R. Santos;M. Sarsour;J. Schambach;A. Schmidt;N. Schmidt;C. Schwarz;J. Schwiening;R. Seidl;A. Sickles;P. Simmerling;S. Širca;D. Sharma;Z. Shi;T. Shibata;C. Shih;S. Shimizu;U. Shrestha;K. Slifer;K. Smith;D. Sokhan;R. Soltz;W. Sondheim;J. Song;I. Strakovsky;P. Steinberg;P. Stepanov;J. Stevens;J. Strube;P. Sun;X. Sun;V. Tadevosyan;W. Tang;S. Araya;S. Tarafdar;L. Teodorescu;A. Timmins;L. Tomášek;N. Trotta;R. Trotta;T. Tveter;Ejiro Naomi Umaka;A. Usman;H. W. Hecke;C. Hulse;J. Velkovska;E. Voutier;P. Wang;Q. Wang;Y. Wang;D. Watts;N. Wickramaarachchi;L. Weinstein;M. Williams;C. Wong;L. Wood;M. Wood;C. Woody;B. Wyslouch;Z. Xiao;Y. Yamazaki;Y. Yang;Z. Ye;H. Yoo;M. Yurov;N. Zachariou;W. Zajc;W. Zha;J. Zhang;Y. Zhang;Y. Zhao;X. Zheng;P. Zhuang
中科院分区：
文献类型：
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作者：
C. Fanelli;Z. Papandreou;K. Suresh;J. K. Adkins;Y. Akiba;A. Albataineh;M. Amaryan;I. Arsene;C. Gayoso;J. Bae;X. Bai;M. Baker;M. Bashkanov;R. Bellwied;F. Benmokhtar;V. Berdnikov;J. Bernauer;F. Bock;W. Boeglin;M. Borysova;E. Brash;P. Brindza;W. Briscoe;M. Brooks;S. Bueltmann;M. Bukhari;A. Bylinkin;R. Capobianco;W. Chang;Y. Cheon;K. Chen;K.F. Chen;K. Cheng;M. Chiu;T. Chujo;Z. Citron;E. Cline;E. Cohen;T. Cormier;Y. Morales;C. Cotton;J. Crafts;C. Crawford;S. Creekmore;C.Cuevas;J. Cunningham;G. David;C. Dean;M. Demarteau;S. Diehl;N. Doshita;R. Dupré;J. Durham;R. Dzhygadlo;R. Ehlers;Lamiaa El Fassi;A. Emmert;R. Ent;R. Fatémi;S. Fegan;M. Finger;M. Finger;J. Frantz;M. Friedman;I. Friščić;D. Gangadharan;S. Gardner;K. Gates;F. Geurts;R. Gilman;D. Glazier;E. Glimos;Y. Goto;N. Grau;S. Greene;A. Guo;L. Guo;S. Ha;J. Haggerty;T. Hayward;X. He;O. Hen;D. Higinbotham;P. H. Hopchev;T. Horn;A. Hoghmrtsyan;P. J. Hsu;J. Huang;G. Huber;A. Hutson;K. Hwang;C. Hyde;M. Inaba;T. Iwata;H. Jo;K. Joo;N. Kalantarians;G. Kalicy;K. Kawade;S. Kay;A. Kim;B. Kim;C. Kim;M. Kim;Y. Kim;E. Kistenev;V. Klimenko;S. Ko;I. Korover;W. Korsch;G. Krintiras;S. Kuhn;C. Kuo;T. Kutz;J. Lajoie;D. Lawrence;S. Lebedev;H. Lee;J. Lee;S. W. Lee;Y. Lee;W. Li;W. Li;X. Li;Y. Liang;S. Lim;C. Lin;D. Lin;K. Liu;M. Liu;K. Livingston;N. Liyanage;W. Llope;C. Loizides;E. Long;R. Lu;Z. Lu;W. Lynch;D. Marchand;M. Marcisovsky;P. Markowitz;H. Marukyan;P. McGaughey;M. Mihovilovič;R. Milner;A. Milov;Y. Miyachi;A. Mkrtchyan;P. Monaghan;R. Montgomery;D. Morrison;A. Movsisyan;H. Mkrtchyan;C. Camacho;M. Murray;K. Nagai;J. Nagle;I. Nakagawa;C. Nattrass;D. Nguyen;S. Niccolai;R. Nouicer;G. Nukazuka;M. Nycz;V. Okorokov;S. Orešić;J. Osborn;C. O'Shaughnessy;S. Paganis;S. Pate;M. Patel;C. Paus;G. Penman;M. Perdekamp;D. Perepelitsa;H. D. Costa;K. Peters;W. Phelps;E. Piasetzky;C. Pinkenburg;I. Procházka;T. Protzman;M. Purschke;J. Putschke;J. Pybus;R. Rajput-Ghoshal;J. Rasson;B. Raue;K. Read;K. Røed;R. Reed;J. Reinhold;E. Renner;J. Richards;C. Riedl;T. Rinn;J. Roche;G. Roland;G. Ron;M. Rosati;C. Royon;J. Ryu;S. Salur;N. Santiesteban;R. Santos;M. Sarsour;J. Schambach;A. Schmidt;N. Schmidt;C. Schwarz;J. Schwiening;R. Seidl;A. Sickles;P. Simmerling;S. Širca;D. Sharma;Z. Shi;T. Shibata;C. Shih;S. Shimizu;U. Shrestha;K. Slifer;K. Smith;D. Sokhan;R. Soltz;W. Sondheim;J. Song;I. Strakovsky;P. Steinberg;P. Stepanov;J. Stevens;J. Strube;P. Sun;X. Sun;V. Tadevosyan;W. Tang;S. Araya;S. Tarafdar;L. Teodorescu;A. Timmins;L. Tomášek;N. Trotta;R. Trotta;T. Tveter;Ejiro Naomi Umaka;A. Usman;H. W. Hecke;C. Hulse;J. Velkovska;E. Voutier;P. Wang;Q. Wang;Y. Wang;D. Watts;N. Wickramaarachchi;L. Weinstein;M. Williams;C. Wong;L. Wood;M. Wood;C. Woody;B. Wyslouch;Z. Xiao;Y. Yamazaki;Y. Yang;Z. Ye;H. Yoo;M. Yurov;N. Zachariou;W. Zajc;W. Zha;J. Zhang;Y. Zhang;Y. Zhao;X. Zheng;P. Zhuang
电子离子对撞机（EIC）是一种尖端加速器设施，将研究粘合宇宙中可见物质构件的“胶水”的性质。拟议的实验将在大约 10 年后在布鲁克海文国家实验室实现，探测器设计和研发目前正在进行中。值得注意的是，EIC 是首批从设计和研发阶段就开始利用人工智能 (AI) 的大型设施之一。 EIC 综合色动力学实验 (ECCE) 是一个提出基于 1.5 T 螺线管的探测器设计的联盟。 EIC 探测器提案审查得出的结论是 ECCE 设计将作为 EIC 探测器的参考设计。在此，我们描述了使用 AI 对 ECCE 跟踪器进行全面优化。这项工作需要对模拟探测器系统进行复杂的参数化。我们的方法处理多维设计空间中的优化问题，该空间由多个目标驱动，这些目标对探测器性能进行编码，同时满足多个机械约束。我们描述了我们的策略并展示了 ECCE 跟踪系统获得的结果。人工智能辅助设计与仿真框架无关，可以扩展到其他子探测器或子探测器系统，以进一步优化 EIC 探测器的性能。
The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the “glue” that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5 T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.