34 citations · 296 across the 31 of their papers we have counts for
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Event topology and global observables in heavy-ion collisions at the Large Hadron Collider
Suraj Prasad, Neelkamal Mallick, Debadatta Behera +2
Particle production and event topology are very strongly correlated in high-energy hadronic and nuclear collisions. Event topology is decided by the underlying particle production…
A new logistic growth model applied to COVID-19 fatality data
S. Triambak, D. P. Mahapatra, N. Mallick +1
Background: Recent work showed that the temporal growth of the novel coronavirus disease (COVID-19) follows a sub-exponential power-law scaling whenever effective control intervent…
Transverse spherocity dependence of azimuthal anisotropy in heavy-ion collisions at the LHC using a multi-phase transport model
Neelkamal Mallick, Raghunath Sahoo, Sushanta Tripathy +1
One of the event shape observables, the transverse spherocity (), has been studied successfully in small collision systems such as proton-proton collisions at the LHC as a too…
Implementation of machine learning techniques to predict impact parameter and transverse spherocity in heavy-ion collisions at the LHC
Aditya Nath Mishra, Neelkamal Mallick, Sushanta Tripathy +2
Machine learning techniques have been quite popular recently in the high-energy physics community and have led to numerous developments in this field. In heavy-ion collisions, one…
Predictions on global properties in O+O collisions at the Large Hadron Collider using a multi-phase transport model
Debadatta Behera, Neelkamal Mallick, Sushanta Tripathy +3
Oxygen (O) ions are planned to be injected at the Large Hadron Collider (LHC) in its next runs, and a day of physics run is anticipated for O+O collisions at $\sqrt{s_{\rm{N…
Event topology and constituent-quark scaling of elliptic flow in heavy-ion collisions at the Large Hadron Collider using a multiphase transport model
Neelkamal Mallick, Sushanta Tripathy, Raghunath Sahoo
Transverse spherocity is an event shape observable, which separates the events based on their geometrical shapes. In this work, we use transverse spherocity to study the identified…
Estimation of Impact Parameter and Transverse Spherocity in heavy-ion collisions at the LHC energies using Machine Learning
Neelkamal Mallick, Sushanta Tripathy, Aditya Nath Mishra +2
Recently, machine learning (ML) techniques have led to a range of numerous developments in the field of nuclear and high-energy physics. In heavy-ion collisions, the impact paramet…