6 papers · 1 filter
Anomaly detection for multijet scenarios
Gregor Kasieczka, Sung Hak Lim, Louis Moureaux +3
Signals of physics beyond the Standard Model continue to resist discovery at the LHC. Recent years have seen the proliferation of new anomaly detection techniques, promising discov…
Jet Classification Using High-Level Features from Anatomy of Top Jets
Amon Furuichi, Sung Hak Lim, Mihoko M. Nojiri
Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to…
Neural Network-based Top Tagger with Two-Point Energy Correlations and Geometry of Soft Emissions
Amit Chakraborty, Sung Hak Lim, Mihoko M. Nojiri +1
Deep neural networks trained on jet images have been successful in classifying different kinds of jets. In this paper, we identify the crucial physics features that could reproduce…
Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra
Amit Chakraborty, Sung Hak Lim, Mihoko M. Nojiri
Classification of jets with deep learning has gained significant attention in recent times. However, the performance of deep neural networks is often achieved at the cost of interp…
Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case
Sung Hak Lim, Mihoko M. Nojiri
Jets from boosted heavy particles have a typical angular scale which can be used to distinguish them from QCD jets. We introduce a machine learning strategy for jet substructure an…
Monojet Signatures from Heavy Colored Particles: Future Collider Sensitivities and Theoretical Uncertainties
Amit Chakraborty, Silvan Kuttimalai, Sung Hak Lim +2
In models with colored particle that can decay into a dark matter candidate , the relevant collider process $pp\to \mathcal{Q}\bar{\mathcal{Q}}\rightarrow X\bar{X}…