Related papers: A unified machine learning approach for reconstruc…
The task of reconstructing particles from low-level detector response data to predict the set of final state particles in collision events represents a set-to-set prediction task requiring the use of multiple features and their correlations…
Status of tau lepton decay Monte Carlo generator TAUOLA, and its main recent applications are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the…
Reconstructing unstable heavy particles requires sophisticated techniques to sift through the large number of possible permutations for assignment of detector objects to the underlying partons. Anapproach based on a generalized attention…
Machine Learning (ML) techniques are rapidly finding a place among the methods of High Energy Physics data analysis. Different approaches are explored concerning how much effort should be put into building high-level variables based on…
The quality of the invariant mass reconstruction of the di-{\tau} system is crucial for searches and analyses of di-{\tau} resonances. Due to the presence of neutrinos in the final state, the {\tau} {\tau} invariant mass cannot be…
The identification of hadronic tau lepton decays is an important requirement for the LHC physics program, both in terms of standard model measurements and the search for beyond-the-standard-model physics. The ATLAS and CMS algorithms for…
Precise measurements of the lepton properties provide stringent tests of the Standard Model and accurate determinations of its parameters. We overview the present status of tau physics, highlighting the most recent developments, and discuss…
For a resonance decaying to $\tau^+\tau^-$, it is difficult to reconstruct its mass accurately because of the presence of neutrinos in the decay products of the $\tau$ leptons. If the resonance is heavy enough, we show that its mass can be…
Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented particle multiplicities expected at the High-Luminosity Large Hadron Collider (HL-LHC) pose significant challenges for track…
Particle identification is one of the core tasks in the data analysis pipeline at the Large Hadron Collider (LHC). Statistically, this entails the identification of rare signal events buried in immense backgrounds that mimic the properties…
Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review…
The trigger system of the CMS detector is pivotal in the acquisition of data for physics measurements and searches. Studies of final states characterized by hadronic decays of tau leptons require the reconstruction and the identification of…
In high energy physics, the ability to reconstruct particles based on their detector signatures is essential for downstream data analyses. A particle reconstruction algorithm based on learning hypergraphs (HGPflow) has previously been…
Machine learning (ML) plays an increasingly important role in both online and offline event reconstruction and identification at CMS experiment. A variety of ML techniques are used to improve the identification of physics objects. Dedicated…
At the LHC, tagging boosted heavy particle resonances which decay hadronically, such as top quarks and Higgs bosons, can play an essential role in new physics searches. In events with high multiplicity, however, the standard approach to tag…
We train several neural networks and boosted decision trees to discriminate fully-hadronic boosted di-$\tau$ topologies against background QCD jets, using calorimeter and tracking information. Boosted di-$\tau$ topologies consisting of a…
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require…
Quantum Tomography of tau lepton pairs produced at a Higgs Factory collider will enable measurements of their spin correlations arising from quantum entanglement. Such measurements rely on the ability to measure the components of and…
The tau-lepton plays an important role in the physics program at the Large Hadron Collider (LHC). It offers a probe in searches for New Physics and to measure parameters of the Standard Model. Spin of tau lepton is an interesting…
Top taggers are established analysis tools to reconstruct boosted hadronically decaying top quarks for example in searches for heavy resonances. We first present a dedicated study of signal efficiency versus background rejection, allowing…