40 citations · 119 across the 13 of their papers we have counts for
13 papers
Tagging fully hadronic exotic decays of the vectorlike quark using a graph neural network
Jai Bardhan, Tanumoy Mandal, Subhadip Mitra +2
Following up on our earlier study in [J. Bardhan et al., Machine learning-enhanced search for a vectorlike singlet B quark decaying to a singlet scalar or pseudoscalar, Phys. Rev.…
HEP-JEPA: A foundation model for collider physics using joint embedding predictive architecture
Jai Bardhan, Radhikesh Agrawal, Abhiram Tilak +2
We present a transformer architecture-based foundation model for tasks at high-energy particle colliders such as the Large Hadron Collider. We train the model to classify jets usin…
Constructing sensible baselines for Integrated Gradients
Jai Bardhan, Cyrin Neeraj, Mihir Rawat +1
Machine learning methods have seen a meteoric rise in their applications in the scientific community. However, little effort has been put into understanding these "black box" model…
Loss function to optimise signal significance in particle physics
Jai Bardhan, Cyrin Neeraj, Subhadip Mitra +1
We construct a surrogate loss to directly optimise the significance metric used in particle physics. We evaluate our loss function for a simple event classification task using a li…
TooLQit: Leptoquark Models and Limits
Arvind Bhaskar, Yash Chaurasia, Arijit Das +5
We introduce the leptoquark (LQ) toolkit, TooLQit, which includes leading-order FeynRules models for all types of LQs and a Python-based calculator, named CaLQ, to test if a set of…
Unsupervised and lightly supervised learning in particle physics
Jai Bardhan, Tanumoy Mandal, Subhadip Mitra +2
We review the main applications of machine learning models that are not fully supervised in particle physics, i.e., clustering, anomaly detection, detector simulation, and unfoldin…
Pinning down the leptophobic in leptonic final states with Deep Learning
Tanumoy Mandal, Aniket Masaye, Subhadip Mitra +3
A leptophobic that does not couple with the Standard Model leptons can evade the stringent bounds from the dilepton-resonance searches. In our earlier paper [T. Arun et…
Machine learning-enhanced search for a vectorlike singlet quark decaying to a singlet scalar or pseudoscalar
Jai Bardhan, Tanumoy Mandal, Subhadip Mitra +1
The presence of a new decay mode relaxes the current mass exclusion limits on vectorlike quarks considerably. We consider the case of a weak-singlet vectorlike quark that can d…
Discovery prospects of a vectorlike top partner decaying to a singlet boson
Akanksha Bhardwaj, Kartik Bhide, Tanumoy Mandal +2
The possibility of a vectorlike top partner decaying to a new colourless weak-singlet scalar or pseudoscalar has attracted some attention in the literature. We investigate the prod…
Roadmap to explore vectorlike quarks decaying to a new scalar or pseudoscalar
Akanksha Bhardwaj, Tanumoy Mandal, Subhadip Mitra +1
The current experimental data allow for a sub-TeV colourless weak-singlet scalar or pseudoscalar. If such a singlet field is present together with TeV-range vectorlike top and bott…
Precise LHC limits on the leptoquark parameter space
Arvind Bhaskar, Diganta Das, Tanumoy Mandal +2
A TeV scale leptoquark (LQ) is one of the promising explanations of the recent anomalies in the semileptonic decays of mesons. Among the various LQs, the vector is c…
LHC Bounds on motivated Leptoquark Models
Arvind Bhaskar, Tanumoy Mandal, Subhadip Mitra +2
Most of the popular explanations of the observed anomalies in the semileptonic -meson decays involve TeV scale Leptoquarks (LQs). Among the various possible LQ models, two parti…
Precise limits on the charge- vector leptoquark
Arvind Bhaskar, Diganta Das, Tanumoy Mandal +2
The leptoquark is known to be a suitable candidate for explaining the semileptonic -decay anomalies. We derive precise limits on its parameter space relevant for the anoma…