most citedPhysics-informed neural network (PINN) modeling of charged particle multiplicity using the two-component framework in heavy-ion collisions: A comparison with data-driven neural networks

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Physics-informed neural network (PINN) modeling of charged particle multiplicity using the two-component framework in heavy-ion collisions: A comparison with data-driven neural networks

Akash Das, Satya Ranjan Nayak, B. K. Singh

In this study, we employ a conventional deep neural network (NN) framework integrated with physics-based constraints to predict charged hadron multiplicity () in hea…

hep-ph2025

Two-particle cumulant distribution: a simulation study of higher moments

Satya Ranjan Nayak, Akash Das, B. K. Singh

In this work, we have shown the two-particle correlations of charged hadrons in d-Au collisions at 200 GeV in PYTHIA8/Angantyr simulations. These correlations were studied at diffe…