4 citations · 9 across the 5 of their papers we have counts for
5 papers
Hunting the Unseen: Deep Learning Analysis for Semi-Visible Jet Tagging
Miguel A. Avendaño-Bernal, Srinandan Dasmahapatra, Ahmed Hammad +4
Semi-Visible Jets (SVJs) constitute a distinctive collider signature of strongly interacting dark sectors, embedding Dark Matter candidates, wherein jets contain both visible Stand…
hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology
Mauricio A. Diaz, Srinandan Dasmahapatra, Stefano Moretti
This paper presents hep-aid, a modular Python library conceived for utilising, implementing, and developing parameter scan algorithms. Originally devised for sample-efficient, mult…
Bayesian Active Search on Parameter Space: a 95 GeV Spin-0 Resonance in the ()SSM
Mauricio A. Diaz, Giorgio Cerro, Srinandan Dasmahapatra +1
In the attempt to explain possible data anomalies from collider experiments in terms of New Physics (NP) models, computationally expensive scans over their parameter spaces are typ…
JetLOV: Enhancing Jet Tree Tagging through Neural Network Learning of Optimal LundNet Variables
Mauricio A. Diaz, Giorgio Cerro, Jacan Chaplais +2
Machine learning has played a pivotal role in advancing physics, with deep learning notably contributing to solving complex classification problems such as jet tagging in the field…
Fat -Jet Analyses Using Old and New Clustering Algorithms in New Higgs Boson Searches at the LHC
Amit Chakraborty, Srinandan Dasmahapatra, Henry Day-Hall +3
We compare different jet-clustering algorithms in establishing fully hadronic final states stemming from the chain decay of a heavy Higgs state into a pair of the 125 GeV Higgs bos…