105 citations · 798 across the 35 of their papers we have counts for
35 papers
Complementary probes of Bilinear RPV SUSY models with a wino-like LSP via Neutrino Oscillation and LHC
Arghya Choudhury, Arpita Mondal
In this work, we explore the bilinear R-parity violating Supersymmetry model's parameter space by performing a Markov Chain Monte Carlo scan with neutrino oscillation data, Higgs m…
Revisiting the Electroweakino Sector of the Baryon Number Violating MSSM at the HL-LHC with Deep Neural Networks
Rahool Kumar Barman, Arghya Choudhury, Subhadeep Sarkar
We study the projected sensitivity of direct electroweakino production at the HL-LHC in a simplified framework with wino-like, mass degenerate…
Generalized Quantum Hadamard Test for Machine Learning
Vivek Mehta, Arghya Choudhury, Utpal Roy
Quantum machine learning models are designed for performing learning tasks. Some quantum classifier models are proposed to assign classes of inputs based on fidelity measurements.…
Reconstructing Sparticle masses at the LHC using Generative Machine Learning
Rahool Kumar Barman, Arghya Choudhury, Subhadeep Sarkar
We explore a generative model framework to infer the masses of heavy particles from detector-level data over a broad parameter space. Our model combines a transformer-based detecto…
Exploring the BSM parameter space with Neural Network aided Simulation-Based Inference
Atrideb Chatterjee, Arghya Choudhury, Sourav Mitra +2
Some of the issues that make sampling parameter spaces of various beyond the Standard Model (BSM) scenarios computationally expensive are the high dimensionality of the input param…
Probing sub-TeV Higgsinos aided by a ML-based top tagger in the context of Trilinear RPV SUSY
Rajneil Baruah, Arghya Choudhury, Kirtiman Ghosh +2
Probing higgsinos remains a challenge at the LHC owing to their small production cross-sections and the complexity of the decay modes of the nearly mass degenerate higgsino states.…