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Dr Vishal Ngairangbam's Outputs (3)

Foundations of automatic feature extraction at LHC–point clouds and graphs (2024)
Journal Article
Bhardwaj, A., Konar, P., & Ngairangbam, V. (2024). Foundations of automatic feature extraction at LHC–point clouds and graphs. European Physical Journal - Special Topics, 233(15-16), 2619-2640. https://doi.org/10.1140/epjs/s11734-024-01306-z

Deep learning algorithms will play a key role in the upcoming runs of the Large Hadron Collider (LHC), helping bolster various fronts ranging from fast and accurate detector simulations to physics analysis probing possible deviations from the Standar... Read More about Foundations of automatic feature extraction at LHC–point clouds and graphs.

Equivariant, safe and sensitive — graph networks for new physics (2024)
Journal Article
Bhardwaj, A., Englert, C., Naskar, W., Ngairangbam, V. S., & Spannowsky, M. (2024). Equivariant, safe and sensitive — graph networks for new physics. Journal of High Energy Physics, 2024(7), Article 245. https://doi.org/10.1007/jhep07%282024%29245

This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integrating equivar... Read More about Equivariant, safe and sensitive — graph networks for new physics.

Interpretable deep learning models for the inference and classification of LHC data (2024)
Journal Article
Ngairangbam, V. S., & Spannowsky, M. (2024). Interpretable deep learning models for the inference and classification of LHC data. Journal of High Energy Physics, 2024(5), Article 4. https://doi.org/10.1007/jhep05%282024%29004

The Shower Deconstruction methodology is pivotal in distinguishing signal and background jets, leveraging the detailed information from perturbative parton showers. Rooted in the Neyman-Pearson lemma, this method is theoretically designed to differen... Read More about Interpretable deep learning models for the inference and classification of LHC data.