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

Abstract

Advanced detector R&D requires performing computationally intensive and detailed simulations as part of the detector-design optimization process. Here, we propose a general approach to this process based on Bayesian optimization and machine learning that encodes detector requirements. As a case study, we focus on the design of the dual-radiator Ring Imaging Cherenkov (dRICH) detector under development as a potential component of the particle-identification system at the future Electron-Ion Collider (EIC). The EIC is a US-led frontier accelerator project for nuclear physics, which has been proposed to further explore the structure and interactions of nuclear matter at the scale of sea quarks and gluons. We show that the detector design obtained with our automated and highly parallelized framework outperforms the baseline dRICH design within the assumptions of the current model. Our technique can be applied to any detector R&D, provided that realistic simulations are available.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [7];  [11];  [12];  [13];  [14];  [6];  [14];  [12];  [6];  [15] more »;  [16];  [17];  [18];  [19];  [6];  [8];  [17];  [15];  [8];  [11];  [20];  [19];  [6];  [9];  [21];  [8];  [6];  [18];  [19];  [22];  [18];  [18];  [23];  [24];  [25];  [6];  [6] « less
  1. National Inst. of Nuclear Physics (INFN), Rome (Italy); Istituto Superiore di Sanità (ISS), Rome (Italy)
  2. National Inst. of Nuclear Physics (INFN), Frascati (Italy). National Lab. of Frascati (INFN-LNF)
  3. Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  4. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  5. Howard Univ., Washington, DC (United States)
  6. Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)
  7. National Inst. of Nuclear Physics (INFN), Ferrara (Italy)
  8. The Catholic Univ. of America, Washington, DC (United States)
  9. Federico Santa María Technical Univ., Valparaíso (Chile)
  10. Univ. of New Hampshire, Durham, NH (United States)
  11. North Carolina A & T State Univ., Greensboro, NC (United States)
  12. Univ. of New Mexico, Albuquerque, NM (United States)
  13. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  14. Inst. for High Energy Physics, Protvino (Russia)
  15. Univ. of South Carolina, Columbia, SC (United States)
  16. Univ. of Illinois at Urbana-Champaign, IL (United States)
  17. Old Dominion Univ., Norfolk, VA (United States)
  18. Georgia State Univ., Atlanta, GA (United States)
  19. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  20. City College of New York, NY (United States)
  21. Stony Brook Univ., NY (United States)
  22. College of William and Mary, Williamsburg, VA (United States)
  23. Abilene Christian Univ., TX (United States)
  24. Argonne National Lab. (ANL), Argonne, IL (United States)
  25. Duke Univ., Durham, NC (United States)
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Nuclear Physics (NP)
OSTI Identifier:
1623319
Alternate Identifier(s):
OSTI ID: 1633037; OSTI ID: 1768759
Report Number(s):
JLAB-PHY-20-3207; DOE/OR/23177-4986; arXiv:1911.05797
Journal ID: ISSN 1748-0221
Grant/Contract Number:  
SC0019999; AC05-06OR23177; FG02-94ER40818; AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Instrumentation
Additional Journal Information:
Journal Volume: 15; Journal Issue: 05; Journal ID: ISSN 1748-0221
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; Detector design and construction technologies and materials; Cherenkov detectors

Citation Formats

Cisbani, E., Dotto, A. Del, Fanelli, C., Williams, M., Alfred, M., Barbosa, F., Barion, L., Berdnikov, V., Brooks, W., Cao, T., Contalbrigo, M., Danagoulian, S., Datta, A., Demarteau, M., Denisov, A., Diefenthaler, M., Durum, A., Fields, D., Furletova, Y., Gleason, C., Grosse-Perdekamp, M., Hattawy, M., He, X., Hecke, H. van, Higinbotham, D., Horn, T., Hyde, C., Ilieva, Y., Kalicy, G., Kebede, A., Kim, B., Liu, M., McKisson, J., Mendez, R., Nadel-Turonski, P., Pegg, I., Romanov, D., Sarsour, M., Silva, C. L. da, Stevens, J., Sun, X., Syed, S., Towell, R., Xie, J., Zhao, Z. W., Zihlmann, B., and Zorn, C. AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case. United States: N. p., 2020. Web. https://doi.org/10.1088/1748-0221/15/05/P05009.
Cisbani, E., Dotto, A. Del, Fanelli, C., Williams, M., Alfred, M., Barbosa, F., Barion, L., Berdnikov, V., Brooks, W., Cao, T., Contalbrigo, M., Danagoulian, S., Datta, A., Demarteau, M., Denisov, A., Diefenthaler, M., Durum, A., Fields, D., Furletova, Y., Gleason, C., Grosse-Perdekamp, M., Hattawy, M., He, X., Hecke, H. van, Higinbotham, D., Horn, T., Hyde, C., Ilieva, Y., Kalicy, G., Kebede, A., Kim, B., Liu, M., McKisson, J., Mendez, R., Nadel-Turonski, P., Pegg, I., Romanov, D., Sarsour, M., Silva, C. L. da, Stevens, J., Sun, X., Syed, S., Towell, R., Xie, J., Zhao, Z. W., Zihlmann, B., & Zorn, C. AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case. United States. https://doi.org/10.1088/1748-0221/15/05/P05009
Cisbani, E., Dotto, A. Del, Fanelli, C., Williams, M., Alfred, M., Barbosa, F., Barion, L., Berdnikov, V., Brooks, W., Cao, T., Contalbrigo, M., Danagoulian, S., Datta, A., Demarteau, M., Denisov, A., Diefenthaler, M., Durum, A., Fields, D., Furletova, Y., Gleason, C., Grosse-Perdekamp, M., Hattawy, M., He, X., Hecke, H. van, Higinbotham, D., Horn, T., Hyde, C., Ilieva, Y., Kalicy, G., Kebede, A., Kim, B., Liu, M., McKisson, J., Mendez, R., Nadel-Turonski, P., Pegg, I., Romanov, D., Sarsour, M., Silva, C. L. da, Stevens, J., Sun, X., Syed, S., Towell, R., Xie, J., Zhao, Z. W., Zihlmann, B., and Zorn, C. Tue . "AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case". United States. https://doi.org/10.1088/1748-0221/15/05/P05009. https://www.osti.gov/servlets/purl/1623319.
@article{osti_1623319,
title = {AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case},
author = {Cisbani, E. and Dotto, A. Del and Fanelli, C. and Williams, M. and Alfred, M. and Barbosa, F. and Barion, L. and Berdnikov, V. and Brooks, W. and Cao, T. and Contalbrigo, M. and Danagoulian, S. and Datta, A. and Demarteau, M. and Denisov, A. and Diefenthaler, M. and Durum, A. and Fields, D. and Furletova, Y. and Gleason, C. and Grosse-Perdekamp, M. and Hattawy, M. and He, X. and Hecke, H. van and Higinbotham, D. and Horn, T. and Hyde, C. and Ilieva, Y. and Kalicy, G. and Kebede, A. and Kim, B. and Liu, M. and McKisson, J. and Mendez, R. and Nadel-Turonski, P. and Pegg, I. and Romanov, D. and Sarsour, M. and Silva, C. L. da and Stevens, J. and Sun, X. and Syed, S. and Towell, R. and Xie, J. and Zhao, Z. W. and Zihlmann, B. and Zorn, C.},
abstractNote = {Advanced detector R&D requires performing computationally intensive and detailed simulations as part of the detector-design optimization process. Here, we propose a general approach to this process based on Bayesian optimization and machine learning that encodes detector requirements. As a case study, we focus on the design of the dual-radiator Ring Imaging Cherenkov (dRICH) detector under development as a potential component of the particle-identification system at the future Electron-Ion Collider (EIC). The EIC is a US-led frontier accelerator project for nuclear physics, which has been proposed to further explore the structure and interactions of nuclear matter at the scale of sea quarks and gluons. We show that the detector design obtained with our automated and highly parallelized framework outperforms the baseline dRICH design within the assumptions of the current model. Our technique can be applied to any detector R&D, provided that realistic simulations are available.},
doi = {10.1088/1748-0221/15/05/P05009},
journal = {Journal of Instrumentation},
number = 05,
volume = 15,
place = {United States},
year = {2020},
month = {5}
}

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