358 citations · 362 across the 7 of their papers we have counts for
8 papers
Sample-Size Scalability and Representation Sensitivity of Quantum Machine Learning Models for Higgs Boson Event Classification
Shiksha Bhardwaj, Ankhi Roy
Quantum machine learning offers new approaches to multivariate event classification in high-energy physics, but its performance relative to optimized classical methods remains unce…
Centrality Dependence of the Balance Functions for Identified Particles in Pb--Pb Collisions Using Pythia + Angantyr
Rashi Gupta, Ankhi Roy
In this paper, we study the balance functions for pions, kaons, and protons in Pb--Pb collisions at TeV using the PYTHIA 8.3 + Angantyr model. The b…
An Impact of Parton Distribution Functions on Open Heavy Flavor Azimuthal Angular Correlations in Pb-Pb Collisions at = 5.5 TeV
Swapnesh Khade, Ravindra Singh, Yoshini Bailung +1
In this paper, we investigate the impact of modern free parton distribution functions and nuclear parton distribution functions on the azimuthal angular correlation of open heavy f…
Probing coalescence of light nuclei via femtoscopy and azimuthal anisotropies
Yoshini Bailung, Sudhir Pandurang Rode, Neha Shah +1
The production mechanism of light nuclei in heavy-ion collisions is vital to understanding the intricate details of nucleon-nucleon interactions. The coalescence of nucleons is a w…
Searching for enhancement in coalescence of in-jet (anti-)deuterons in proton-proton collisions
Yoshini Bailung, Neha Shah, Ankhi Roy
Recent measurements from ALICE report that in-jet'' nucleons carry a higher probability of forming a deuteron via coalescence than the nucleons from the underlying event (UE).…
Exploring light nuclei production at RHIC and LHC energies with A Multi-Phase Transport model and a coalescence afterburner
Yoshini Bailung, Neha Shah, Ankhi Roy
In heavy-ion collisions, understanding how light nuclei species are produced can provide insight into the nature of hadronic interactions in extreme conditions. It can also shed li…
Separation of electrons from pions in GEM TRD using deep learning
Nilay Kushawaha, Yulia Furletova, Ankhi Roy +1
Machine learning (ML) is no new concept in the high-energy physics community, in fact, many ML techniques have been employed since the early 80s to deal with a broad spectrum of ph…
Challenges in QCD matter physics - The Compressed Baryonic Matter experiment at FAIR
CBM Collaboration, T. Ablyazimov, A. Abuhoza +585
Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is stud…