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physics.ins-det2020
ML-assisted versatile approach to Calorimeter R&D
Alexey Boldyrev, Denis Derkach, Fedor Ratnikov +1
Advanced detector R&D for both new and ongoing experiments in HEP requires performing computationally intensive and detailed simulations as part of the detector-design optimisation…
physics.ins-det2020
Using machine learning to speed up new and upgrade detector studies: a calorimeter case
F. Ratnikov, D. Derkach, A. Boldyrev +3
In this paper, we discuss the way advanced machine learning techniques allow physicists to perform in-depth studies of the realistic operating modes of the detectors during the sta…