AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider

@article{Fanelli2022AIassistedOO,
  title={AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider},
  author={Cristiano Fanelli and Zisis Papandreou and K. Suresh and James Kevin Adkins and Yasuyuki Akiba and Areej Albataineh and Moskov J. Amaryan and I. C. Arsene and C Ayerbe Gayoso and J. Bae and X K Bai and Mark David Baker and M. Bashkanov and Rene Bellwied and F. Benmokhtar and Vladimir Berdnikov and Jan C. Bernauer and F. Bock and Werner U. Boeglin and Maryna Borysova and Edward Brash and Paul Brindza and William J. Briscoe and Michael L. Brooks and Stephen L. Bueltmann and Masroor H. S. Bukhari and Alexander Bylinkin and Roberto Capobianco and W. C. Chang and Yongjin Cheon and K. Chen and K.F. Chen and Kai-yu Cheng and M. Chiu and T. Chujo and Zvi Hirsh Citron and E. Cline and E.O. Cohen and Thomas Michael Cormier and Y. Corrales Morales and Chandler W. Cotton and J. Crafts and C B Crawford and Santiel J. Creekmore and C.Cuevas and J. Cunningham and G. David and Cameron Thomas Dean and Marcel Demarteau and Stefan Diehl and N. Doshita and R. Dupr{\'e} and J. Matthew Durham and Roman Dzhygadlo and R. J. Ehlers and Lamiaa El Fassi and Alexander Emmert and Rolf Ent and Renee Fat{\'e}mi and S. D. Fegan and M. Finger and M. Finger and Janet Elizabeth Frantz and M. Friedman and I. Fri{\vs}{\vc}i{\'c} and D. Gangadharan and Simon Gardner and Kameron Gates and F. J. M. Geurts and Robert Gilman and D. I. Glazier and E. Glimos and Y. Goto and Nathan Grau and Senta Victoria Greene and A. Q. Guo and L. Guo and S. K. Ha and J. S. Haggerty and Timothy B. Hayward and X. He and O. Hen and Douglas W. Higinbotham and P. H. Hopchev and T. Horn and A. Hoghmrtsyan and Pai-hsien Jennifer Hsu and J. Huang and G M Huber and Alek Hutson and K. Y. Hwang and C. H. Hyde and M. Inaba and Tetsurou Iwata and H. S. Jo and K. S. Joo and N. Kalantarians and G. Kalicy and Kentaro Kawade and S. J. D. Kay and A. Kim and B. Kim and C. Kim and M. Kim and Y. Kim and Edouard Kistenev and V. Klimenko and Sanghyun Ko and Igor Korover and Wolfgang Korsch and Georgios K Krintiras and Sebastian E. Kuhn and Chung Ming Kuo and Tyler Kutz and John G. Lajoie and David Lawrence and Semen Lebedev and H. Lee and J. S. H. Lee and S. W. Lee and Y.-J. Lee and W. Li and W. B. Li and X. Li and Y. T. Liang and S. Lim and C.-h. Lin and Dandan Lin and K. Liu and M. Liu and Kay Livingston and Nilanga K. Liyanage and William Llope and C. Loizides and E. Long and R. Lu and Z. Lu and Warren A. Lynch and Dominique Marchand and Michal Marcisovsky and P. E. C. Markowitz and Hrachya Marukyan and Patrick McGaughey and M. Mihovilovi{\vc} and R. G. Milner and Alexander Milov and Yoshiyuki Miyachi and A. H. Mkrtchyan and Peter Monaghan and Rachel Montgomery and Dave Morrison and Aram Movsisyan and Hamlet Mkrtchyan and Carlos Mu{\~n}oz Camacho and Michael Murray and K. Nagai and James Lawrence Nagle and I. Nakagawa and C. Nattrass and Dien Nguyen and Silvia Niccolai and Rachid Nouicer and Genki Nukazuka and Michael Nycz and V. A. Okorokov and Susan Oresic and J. D. Osborn and Christopher O'Shaughnessy and Stathes D. Paganis and Stephen F. Pate and M. Patel and Christoph Paus and G. G. Penman and M. Grosse Perdekamp and Dennis Perepelitsa and H. Pereira Da Costa and Klaus Peters and William Phelps and Eliezer Piasetzky and C. Pinkenburg and Ivo Proch{\'a}zka and Thomas F. Protzman and Martin L. Purschke and Joern Putschke and J.R. Pybus and Renuka Rajput-Ghoshal and Joseph E. Rasson and Brian A. Raue and K. F. Read and Ketil R{\o}ed and Rolf K. Reed and J{\"o}rg Reinhold and E. L. Renner and Jade Richards and Caroline Kathrin Riedl and Timothy Thomas Rinn and J. Roche and G Roland and Guy Ron and M. Rosati and C. Royon and J. H. Ryu and Sevil Salur and N. Santiesteban and R. Felix dos Santos and M. Sarsour and Joachim J Schambach and A. Schmidt and N. M. Schmidt and Cornelius Schwarz and J Schwiening and Reinhard Seidl and Anne Marie Sickles and P. Simmerling and S. {\vS}irca and D. Sharma and Z. Shi and Toshi-aki Shibata and Chih Wei Shih and S. Shimizu and U. Shrestha and K. Slifer and K. Smith and Daria Sokhan and Ron A. Soltz and Walter Sondheim and J. Song and Igor I. Strakovsky and P. Steinberg and P. Stepanov and J. Stevens and Jan Strube and P. Sun and X. Sun and Vardan Tadevosyan and W. Tang and S. Tapia Araya and S. Tarafdar and Liliana Teodorescu and Anthony Robert Timmins and Lukas Tomasek and Nikita Trotta and Richard Trotta and Trine Spedstad Tveter and Ejiro Naomi Umaka and A. Usman and H. W. van Hecke and Charlotte Barbara Van Hulse and Julia Velkovska and Eric Voutier and P. K. Wang and Q. Wang and Y. Wang and D P Watts and N. Wickramaarachchi and Lawrence B. Weinstein and Mark Williams and C. P. Wong and L. Wood and Martin Wood and Craig Woody and Boleslaw Wyslouch and Ziwei Xiao and Y. Yamazaki and Y. Yang and Z H Ye and H. D. Yoo and M. Yurov and N. Zachariou and William A. Zajc and Wangmei Zha and J. Zhang and Y. X. Zhang and Y. X. Zhao and X. Zheng and P. Zhuang},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.09185}
}
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… 
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References

SHOWING 1-10 OF 32 REFERENCES

AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case

TLDR
This work proposes a general approach to detector R&D based on Bayesian optimization and machine learning that encodes detector requirements and shows that the detector design obtained with this automated and highly parallelized framework outperforms the baseline dRICH design within the assumptions of the current model.

Design of the ECCE Detector for the Electron Ion Collider

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National

Design of detectors at the electron ion collider with artificial intelligence

  • C. Fanelli
  • Physics, Computer Science
    Journal of Instrumentation
  • 2022
TLDR
Future high energy nuclear physics experiments can leverage AI-based strategies to design more efficient detectors by optimizing their performance driven by physics criteria and minimizing costs for their realization.

ALICE ITS 3: the first truly cylindrical inner tracker

The high integration density of MAPS, with silicon sensor and readout electronics implemented in the same device, allows very thin structures with a greatly reduced material budget. Thicknesses of O

Geant4 - A simulation toolkit

First demonstration of in-beam performance of bent Monolithic Active Pixel Sensors

  • A. I. P. G. A. RinellaM. Agnello Seoul.
  • Materials Science
    Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
  • 2022

Search for resonances in diphoton events at root s=13TeV with the ATLAS detector

Searches for new resonances decaying into two photons in the ATLAS experiment at the CERN Large Hadron Collider are described. The analysis is based on proton–proton collision data corresponding to

AtlFast3: The Next Generation of Fast Simulation in ATLAS

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger

Search for resonances in diphoton events at s=13$$ \sqrt{s}=13 $$ TeV with the ATLAS detector

A bstractSearches for new resonances decaying into two photons in the ATLAS experiment at the CERN Large Hadron Collider are described. The analysis is based on proton-proton collision data

TeV with the ATLAS Detector

A measurement of correlations between event-plane angles Φn is presented as a function of centrality for PbPb collisions at sNN = 2.76 TeV. These correlations are estimated from observed event-plane