Deeply learning deep inelastic scattering kinematics
نویسندگان
چکیده
We study the use of deep learning techniques to reconstruct kinematics neutral current inelastic scattering (DIS) process in electron-proton collisions. In particular, we simulated data from ZEUS experiment at HERA accelerator facility, and train neural networks kinematic variables $Q^2$ $x$. Our approach is based on information used classical construction methods, measurements scattered lepton, hadronic final state detector, but enhanced through correlations patterns revealed with sets. show that, appropriate selection a training set, sufficiently surpass all reconstruction methods most range considered. Rapid access large samples ability effectively extract sets, both suggest that DIS can serve as rigorous method combine outperform methods.
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ژورنال
عنوان ژورنال: European Physical Journal C
سال: 2022
ISSN: ['1434-6044', '1434-6052']
DOI: https://doi.org/10.1140/epjc/s10052-022-10964-z