Related papers: A unified machine learning approach for reconstruc…
A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which…
In this work we demonstrate that significant gains in performance and data efficiency can be achieved in High Energy Physics (HEP) by moving beyond the standard paradigm of sequential optimization or reconstruction and analysis components.…
In searches for new physics in the energy regime of the LHC, it is becoming increasingly important to distinguish single-jet objects that originate from the merging of the decay products of W bosons produced with high transverse momenta…
Tau-lepton decays with up to two $\pi^0$'s in the final state, $\tau^+ \to \pi^+ \bar{\nu}_\tau$, $\rho^+ (\pi^+\pi^0) \bar{\nu}_\tau$, $a^+_1 (\pi^+\pi^0\pi^0) \bar{\nu}_\tau$, are used to study the performance of the barrel part of the…
Top quark pair decay events resulting in final states containing {\tau} leptons present interesting channels in the search for physics beyond the Standard Model. This document describes the in-progress analyses of two channels, {\tau}+jets…
This PhD thesis studies some hadronic and radiative decays of the tau lepton using a Chiral Lagrangian including resonance fields. After a theoretical introduction, the decays to the $(\pi \pi \pi)^-$, $(KK\pi)^-$ and $\eta^{(\prime)} \pi^-…
Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer…
In the particle-flow approach information from all available sub-detector systems is combined to reconstruct all stable particles. The global event reconstruction has been shown to improve, in particular, the resolution of jet energy and…
Selected results on hadronic decays of the tau lepton from the TAU98 Workshop are reviewed. A comprehensive picture emerges for strange particle branching fractions, and exploration of resonant substructure of both strange and non-strange…
Reconstructing the trajectories of charged particles in high-energy collisions requires high precision to ensure reliable event reconstruction and accurate downstream physics analyses. In particular, both precise hit selection and…
Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models…
A method is introduced for distinguishing top jets (boosted, hadronically decaying top quarks) from light quark and gluon jets using jet substructure. The procedure involves parsing the jet cluster to resolve its subjets, and then imposing…
Jet classification in high-energy particle physics is important for understanding fundamental interactions and probing phenomena beyond the Standard Model. Jets originate from the fragmentation and hadronization of quarks and gluons, and…
A search for a pair of low-mass pseudoscalars $a$ that promptly decay into $\tau$-leptons is presented using 140 fb$^{-1}$ of proton-proton collision data at $13$ TeV centre-of-mass energy recorded with the ATLAS detector at the Large…
A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods…
Status of tau lepton decay Monte Carlo generator TAUOLA is reviewed. Recent efforts on development of new hadronic currents are presented. Multitude new channels for anomalous tau decay modes and parametrization based on defaults used by…
Using deep neural networks for identifying physics objects at the Large Hadron Collider (LHC) has become a powerful alternative approach in recent years. After successful training of deep neural networks, examining the trained networks not…
The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found…
We apply both cut-based and machine learning techniques using the same inputs to the challenge of hadronic jet substructure recognition, utilizing classical subjettiness variables within the Delphes parameterized detector simulation…
Top tagging is a recent approach to identifying boosted hadronic top quarks. It avoids reconstructing individual top decay products and instead uses a jet algorithm to reconstruct the entire top decay. Quite generally, geometrically large…