相关论文: Invariant mass reconstruction of heavy gauge boson…
The reconstruction of the invariant mass of $\tau$ lepton pairs is important for analyses containing Higgs and Z bosons decaying to $\tau^{+}\tau^{-}$, but highly challenging due to the neutrinos from the $\tau$ lepton decays, which cannot…
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…
Various theories beyond the Standard Model predict the existence of heavy resonances decaying to Higgs (H) boson pairs. In order to maximize the sensitivity of searches for such resonances, it is important that experimental analyses cover a…
The invariant mass of tau lepton pairs turns out to be smaller than the resonant mass of their mother particle and the invariant mass distribution is stretched wider than the width of the resonant mass as significant fraction of tau lepton…
Tau leptons serve as an important tool for studying the production of Higgs and electroweak bosons, both within and beyond the Standard Model of particle physics. Accurate reconstruction and identification of hadronically decaying tau…
Accurate reconstruction of the mass of a resonance decaying to a pair of $\tau$ leptons is challenging because of the presence of multiple neutrinos from $\tau$ decays. The existing methods rely on either a partially reconstructed mass,…
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…
We present an algorithm for the reconstruction of the Higgs mass in events with Higgs bosons decaying into a pair of tau leptons. The algorithm is based on matrix element (ME) techniques and achieves a relative resolution on the Higgs boson…
We explore the potential to use machine learning methods to search for heavy neutrinos, from their hadronic final states including a fat-jet signal, via the processes $pp \rightarrow W^{\pm *}\rightarrow \mu^{\pm} N \rightarrow \mu^{\pm}…
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…
Tau leptons play an important role in the physics program at the LHC. They are used in searches for new phenomena like the Higgs boson or Supersymmetry and in electroweak measurements. Identifying hadronically decaying tau leptons with good…
We propose a method for reconstructing the mass of a particle, such as the Higgs boson, decaying into a pair of tau leptons, of which one subsequently undergoes a 3-prong decay. The kinematics is solved using information from the visible…
The Higgs boson is thought to provide the interaction that imparts mass to the fundamental fermions, but while measurements at the Large Hadron Collider (LHC) are consistent with this hypothesis, current analysis techniques lack the…
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…
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…
We conduct a detailed exploration of charged Higgs boson masses $M_{H^{\pm}}$ within the range of $100-190~GeV$. This investigation is grounded in the benchmark points that comply with experimental constraints, allowing us to systematically…
Tau leptons play a crucial role in studies of the Higgs boson and searches for Beyond the Standard Model physics at the present LHC and in its high luminosity upgrade. This talk presents the latest advancements in the reconstruction and…
The performance of tau-lepton reconstruction and identification algorithms is studied using a data sample of proton-proton collisions at sqrt(s)=7 TeV, corresponding to an integrated luminosity of 36 inverse picobarns collected with the CMS…
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…
A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) that originate from genuine tau leptons in the CMS detector against $\tau_\mathrm{h}$ candidates that originate from quark or…