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Studying Capabilities of a Fast Monitor for Beam Collisions by Monte Carlo Simulations and Machine Learning Methods

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Abstract

A system for fast monitoring of intense beam collisions in experiments at the NICA collider, based on segmented ring detectors on microchannel plates, is considered. Simulation of the monitoring system has been carried out using a DQGSM event generator. It is shown that in each collision event, the monitoring system and machine learning algorithms can ensure the accuracy of finding the position of the interaction point with the standard deviation σ ≤ 12 mm.

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Funding

The work was supported by the Russian Foundation for Basic Research (project no. 18-02-40097/19).

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Authors and Affiliations

  1. St. Petersburg State University, 198504, St. Petersburg, Russia

    V. S. Sandul, G. A. Feofilov & F. F. Valiev

Authors
  1. V. S. Sandul
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  2. G. A. Feofilov
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  3. F. F. Valiev
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Corresponding author

Correspondence to V. S. Sandul.

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The authors declare that they have no conflicts of interest.

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Translated by G. Dedkov

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Sandul, V.S., Feofilov, G.A. & Valiev, F.F. Studying Capabilities of a Fast Monitor for Beam Collisions by Monte Carlo Simulations and Machine Learning Methods. Phys. Part. Nuclei 54, 712–716 (2023). https://doi.org/10.1134/S1063779623040275

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  • DOI: https://doi.org/10.1134/S1063779623040275

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