From the 1 of 22 linked papers with an AI index.
22 papers
Evolution of the underlying event and non-extensive thermodynamics in pp collisions from RHIC to LHC energies
Suraj Prasad, Aditya Nath Mishra, Guy Paić +1
We investigate the geometrical and thermodynamical aspects of particle production in pp collisions over a broad center-of-mass energy, ranging from GeV to 13 TeV us…
Constraining -cluster compactness in and at TeV energies using azimuthal anisotropy
Aswathy Menon Kavumpadikkal Radhakrishnan, Suraj Prasad, Neelkamal Mallick +2
The study uses simulations of ultra‑relativistic O‑O and Ne‑Ne collisions to see if elliptic flow measurements can constrain the alpha‑cluster compactness in O and Ne…
Machine learning driven identification of heavy flavor decay leptons in proton-proton collisions at the Large Hadron Collider
Raghunath Sahoo, Kangkan Goswami, Suraj Prasad
The study of heavy-flavor hadrons is topical in the era of precision measurements, which is useful to test theories based on pQCD. The heavy-flavor hadrons are produced initially d…
MAGE-HEP: Monte Carlo Analysis and Graphical Environment for High-Energy Physics
Rishabh Gupta, Kangkan Goswami, Suraj Prasad +1
Monte Carlo event generators are central to high-energy physics analysis. However, workflows based on handwritten scripts can be difficult to reuse, modify, and reproduce when mult…
Inferring identified hadron production in collisions with physics-informed machine learning at the LHC
Rishabh Gupta, Kangkan Goswami, Suraj Prasad +1
Machine learning has become a powerful tool in high-energy collider experiments, which enables the studies based on data-driven approaches to complex reconstruction and regression…
Nuclear geometry driven symmetry plane correlations in OO and Ne--Ne collisions at the Large Hadron Collider
Suraj Prasad, Raghunath Sahoo
Symmetry-plane correlations (SPCs) are key observables sensitive to the medium's transport properties and are driven by participant-plane correlations (PPCs) in the nuclear overlap…