From the 1 of 22 linked papers with an AI index.
22 papers
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…
Why Do Light Nuclei Survive at the Large Hadron Collider?
Sushanta Tripathy, Raghunath Sahoo
Light nuclei and antinuclei, such as deuterons, are produced abundantly at the Large Hadron Collider (LHC) in hadronic and nuclear collisions. Even though their binding energies ar…
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…