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Elastic Neural Net for standalone RICH ring finding

KIP. Elastic Neural Net for standalone RICH ring finding. Sergey Gorbunov Ivan Kisel DESY, Zeuthen KIP , Uni-Heidelberg. ACAT 2005, DESY, Zeuthen May 22-27, 2005. EN – Traveling Salesman Problem. Discrete EN. (*) Pentium IV/2.4 GHz.

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Elastic Neural Net for standalone RICH ring finding

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  1. KIP Elastic Neural Net for standalone RICH ring finding Sergey Gorbunov Ivan Kisel DESY, Zeuthen KIP, Uni-Heidelberg ACAT 2005, DESY, Zeuthen May 22-27, 2005

  2. EN – Traveling Salesman Problem Discrete EN (*) Pentium IV/2.4 GHz Nature, 326 (1987) 689 S. Gorbunov, I. Kisel

  3. EN – Ring Search : Idea • Features: • External forces - minimizing distances • Internal forces - constraint on Fourier coefficients CHEP’01, Beijing (2001) 162 S. Gorbunov, I. Kisel

  4. EN – Ring Search : Implementation • Scheme: • Loop over hits • Finding a ring in a local area around the hit • Sorting of the found rings • Details: • No internal forces - fixed ring shape (circle) • External forces - minimize distances • Discrete ring evolution - direct finding of the minimum in 2-3 iterations • Time ~ total number of hits S. Gorbunov, I. Kisel

  5. RICH Detector in the CBM Experiment at GSI mirror R = 450 cm 3.3 m gaseous radiator 40%He + 60%CH4N2 beam 4.7 m 2 m 38 rings/event 33 electrons 5 pions 12.6 e from primary vertex 5 p from primary vertex 1 central Au+Au collision, 25 AGeV (UrQMD) S. Gorbunov, I. Kisel

  6. EN – Performance All set: N hits ≥ 5 Ref set: N hits ≥ 15 Extra set: 5 ≤ N hits < 15 Reconstructed: ≥ 70% hits from the same MC Clone: MC reconstructed few times Ghost: < 70% hits from the same MC S. Gorbunov, I. Kisel

  7. Conclusion • Efficient ring finder based on the elastic net • Standalone – no track guidance necessary • Simple – suitable for hardware implementation • Fast – can be used for triggering S. Gorbunov, I. Kisel

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