Abstract

The NOvA far detector is well suited for finding exotic particles due to its technical features (see [1]). One type of those exotic particles is a "slow" magnetic monopole. It is assumed that the energy deposition of such monopoles should be enough to be registered (see [2]). Measurement of the expected signals was performed on the NOvA test bench at JINR (see [3]). Result of this measurement allows us to perform slow monopole's research using NOvA software and hardware with high efficiency. As a whole, the research can lead to a discovery, or it can limit the existence of monopoles in a wide range of parameters, previously unreachable in other experiments (MACRO, SLIM, RICE, IceCube). Several special software tools have been developed. Slow Monopole Trigger has been created and implemented in the NOvA Data-Driven-Trigger system. Also, an online reconstruction algorithm has been developed and tested on 5% of the data. A technical description of these tools and current results of the analysis are presented in this work.

Highlights

  • NOvA is a long-baseline neutrino experiment that is studying various parameters of neutrinos

  • Light from the scintillator is captured by the fibers and is transmitted to an Avalanche Photodiode (APD)

  • Fibers from 32 cells are grouped on one APD board

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Summary

Slow magnetic monopoles search in NOvA

Alexander Antoshkin,1∗ Martin Frank Dzhelepov Laboratory of Nuclear Problems, JINR. The NOvA far detector is well suited for finding exotic particles due to its technical features (see [1]). One type of those exotic particles is a ”slow” magnetic monopole. Measurement of the expected signals was performed on the NOvA test bench at JINR (see [3]). Each cell in the far detector measures 3.9 cm wide, 6.0 cm deep and 15.5 meters long. Quantum mechanical formulation of the magnetic monopoles was made by Paul Dirac in 1931 Searches for these particles are very important for several reasons:

SEARCHING STRATEGIES IN NOVA
Highly ionizing particle
Data Samples
Linear Regression coefficient
Time Gap Fraction
Findings
CONCLUSION
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