7 citations · 7 across the 6 of their papers we have counts for
9 papers
Probing the microscopic origin of prompt and non-prompt production through event-shape engineering in proton-proton collisions at the LHC
Aswathy Menon Kavumpadikkal Radhakrishnan, Suraj Prasad, Purnima Srivastava +1
Heavy-flavour hadrons are produced in the early stages of ultra-relativistic collisions at the LHC via hard partonic interactions and experience the whole system evolution. The stu…
Mean free path of photons in relativistic heavy ion collisions
Jajati K. Nayak, Rupa Chatterjee
Electromagnetic probes, such as photons and dileptons, play a key role in diagnosing the initial temperature of the hot and dense quark-gluon plasma (QGP) matter created in relativ…
Probing the sensitivity of anisotropic flow coefficients to the initial nuclear structure in pO and OO collisions at the LHC
Aswathy Menon Kavumpadikkal Radhakrishnan, Suraj Prasad, Neelkamal Mallick +2
RHIC and LHC have injected nuclei in their accelerator complexes with a focus on investigating collectivity and the origin of quark-gluon plasma signatures in small co…
Higher order flow coefficients -- A Messenger of QCD medium formed in heavy-ion collisions at the Large Hadron Collider
Suraj Prasad, Aswathy Menon K R, Raghunath Sahoo +1
Anisotropic flow and fluctuations are sensitive observables of the initial state effects in heavy ion collisions and are characterized by the medium properties and final state inte…
Exploring the effects of -clustered structure of nuclei in anisotropic flow fluctuations in - collisions at the LHC within a CGC+Hydro framework
Suraj Prasad, Neelkamal Mallick, Raghunath Sahoo +1
In this paper, we explore the effects of the presence of clustered nuclear structure of in the final state elliptic flow fluctuations through - collisions…
Prompt and non-prompt production of charm hadrons in proton-proton collisions at the Large Hadron Collider using machine learning
Raghunath Sahoo, Suraj Prasad, Neelkamal Mallick +2
In this contribution, we use machine learning (ML) based models to separate the prompt and non-prompt production of heavy flavour hadrons, such as and J/, in proton-proton…