Related papers: A unified machine learning approach for reconstruc…
We study weak isosinglet vectorlike leptons that decay through a small mixing with the tau lepton, for which the discovery and exclusion reaches of the Large Hadron Collider and future proposed hadron colliders are limited. We show how an…
This Letter presents a study of the reconstruction and identification of $H\to WW^*$ with high transverse momentum, where both $W^{(*)}$ bosons decay hadronically. We show that the boosted $H\to WW^*$ can be effectively reconstructed as a…
We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC). Collision events produced at the LHC and represented as…
We study the possibility of utilising the constrained mass variable, $M_{2Cons}$, in reconstructing the semi-invisible events originated from a resonant production at the LHC. While this proposal is effective for any similar antler type…
Rapidly applying the effects of detector response to physics objects (e.g. electrons, muons, showers of particles) is essential in high energy physics. Currently available tools for the transformation from truth-level physics objects to…
We briefly review common tools and methods to identify boosted, hadronically decaying top quarks at the LHC experiments. This includes generic jet substructure variables, specific top identification algorithms, and recent developments in…
Analytic expressions are given for the $\tau$ decays into three charged leptons, $\tau\rta \ell\ell\overline \ell\nu_\tau\overline \nu_\ell$, where the $\ell$ are combinations of electrons and muons, and for the radiative decays $\tau\rta…
In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics.…
We show that machine learning methods produce superior particle position reconstruction accuracy in scintillation-based detectors.
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many…
Interest in deep learning in collider physics has been growing in recent years, specifically in applying these methods in jet classification, anomaly detection, particle identification etc. Among those, jet classification using neural…
A new algorithm for the identification of boosted, hadronically decaying, heavy particles at the LHC is presented. The algorithm is based on the known procedure of jet clustering with variable distance parameter $R$ and adapts the jet size…
The reconstruction of top-quark pair-production ($t\bar{t}$) events is a prerequisite for many top-quark measurements. We use a deep neural network, trained with Monte-Carlo simulated events, to reconstruct $t\bar{t}$ decays in the…
This paper presents direct searches for lepton flavour violation in Higgs boson decays, $H\rightarrow e\tau$ and $H\rightarrow\mu\tau$, performed using data collected with the ATLAS detector at the LHC. The searches are based on a data…
Model independent tests for symmetry violations in tau decays are important for determining whether the tau lepton is elementary or, instead, macroscopic. Such tests are also significant steps towards resolving the outstanding "e - mu -…
Motivated by the recent investigation of neutrinoless $\tau$-lepton decays by the CLEO collaboration, we perform a systematic analysis of such decays in a possible new-physics scenario with heavy Dirac/Majorana neutrinos, including…
We study the impact of machine-learning algorithms on LHC searches for leptoquarks in final states with hadronically decaying tau leptons, multiple $b$-jets, and large missing transverse momentum. Pair production of scalar leptoquarks with…
A search for a new high-mass resonance decaying to a tau lepton and a neutrino is reported. The analysis uses proton-proton collision data collected by the CMS experiment at the LHC at $\sqrt{s} =$ 13 TeV, corresponding to an integrated…
The precise reconstruction of the mass peak of long-lived heavy neutral leptons (HNLs) helps to improve the sensitivity for sterile neutrino searches in both fixed-target and collider environments (e.g., SHiP and the LHC). We present an…
Identifying the origin of high-energy hadronic jets ('jet tagging') has been a critical benchmark problem for machine learning in particle physics. Jets are ubiquitous at colliders and are complex objects that serve as prototypical examples…