scholarly journals Phenomenology of vector-like leptons with Deep Learning at the Large Hadron Collider

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Felipe F. Freitas ◽  
João Gonçalves ◽  
António P. Morais ◽  
Roman Pasechnik

Abstract In this paper, a model inspired by Grand Unification principles featuring three generations of vector-like fermions, new Higgs doublets and a rich neutrino sector at the low scale is presented. Using the state-of-the-art Deep Learning techniques we perform the first phenomenological analysis of this model focusing on the study of new charged vector-like leptons (VLLs) and their possible signatures at CERN’s Large Hadron Collider (LHC). In our numerical analysis we consider signal events for vector-boson fusion and VLL pair production topologies, both involving a final state containing a pair of charged leptons of different flavor and two sterile neutrinos that provide a missing energy. We also consider the case of VLL single production where, in addition to a pair of sterile neutrinos, the final state contains only one charged lepton. We propose a novel method to identify missing transverse energy vectors by comparing the detector response with Monte-Carlo simulated data. All calculated observables are provided as data sets for Deep Learning analysis, where a neural network is constructed, based on results obtained via an evolutive algorithm, whose objective is to maximise either the accuracy metric or the Asimov significance for different masses of the VLL. Taking into account the effect of the three analysed topologies, we have found that the combined significance for the observation of new VLLs at the high-luminosity LHC can range from 5.7σ, for a mass of 1.25 TeV, all the way up to 28σ if the VLL mass is 200 GeV. We have also shown that by the end of the LHC Run-III a 200 GeV VLL can be excluded with a confidence of 8.8 standard deviations. The results obtained show that our model can be probed well before the end of the LHC operations and, in particular, providing important phenomenological information to constrain the energy scale at which new gauge symmetries emergent from the considered Grand Unification picture can be manifest.

2021 ◽  
Vol 2021 (5) ◽  
Author(s):  
Ulrich Haisch ◽  
Giacomo Polesello

Abstract Given the hints of lepton-flavour non-universality in B-meson decays, leptoquarks (LQs) are enjoying a renaissance. We propose novel Large Hadron Collider (LHC) searches for such hypothetical states that do not rely on strong production only, but can also receive important contributions from quark-lepton annihilation. For the cases of a resonant signal involving a bottom quark and a tau lepton (b + τ), a top quark and missing transverse energy ($$ {E}_T^{\mathrm{miss}} $$ E T miss ) and light-flavour jets plus $$ {E}_T^{\mathrm{miss}} $$ E T miss , we develop realistic analysis strategies and provide detailed evaluations of the achievable sensitivities for the corresponding LQ signatures at future LHC runs. Our analyses allow us to derive a series of stringent constraints on the masses and couplings of third-generation singlet vector LQs, showing that at LHC Run III and the high-luminosity LHC the proposed search channels can probe interesting parts of the LQ parameter space addressing the B-physics anomalies. In view of the reach of the proposed b + τ signature, we recommend that dedicated resonance searches for this final state should be added to the exotics search canon of both ATLAS and CMS.


Universe ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Carla Sbarra ◽  

LUCID (LUminosity Cerenkov Integrating Detector) is the main luminosity monitor of the ATLAS (A Toroidal LHC Apparatus) experiment at the Large Hadron Collider (LHC) and in particular is the only one capable of providing bunch-by-bunch luminosity information, both online and offline, for all beam conditions and luminosity ranges. LUCID-2 refers to the detector upgrade designed to cope with the running conditions to be met in Run-2 (2015–2018): a center of mass energy of 13 TeV, with 50 pp interactions per bunch-crossing on average and a 25 ns bunch-spacing. This report summarizes all changes with respect to the detector deployed in Run-1 (2010–2012), including smaller sensors for higher granularity, new readout electronics for early signal digitization, and a completely new calibration concept guaranteeing long-term stability of the detector response. In addition, the overall detector performance in Run-2 and preliminary results on luminosity measurements are presented.


2005 ◽  
Vol 20 (15) ◽  
pp. 3400-3402
Author(s):  
◽  
SATYAKI BHATTACHARYA

The Large Hadron Collider(LHC) is a proton proton collider being built at CERN, Geneva which will collide two 7 TeV proton beams giving a center of mass energy of 14 TeV. The Compact Muon Solenoid (CMS) is a multi-purpose detector at the LHC which is designed to discover the Higgs boson over the mass range of 90 to 1000 GeV. Since LEP searches have put a 95% C.L. lower bound on (standard model) Higgs mass of 114.4 GeV and theory excludes mass above about 1 TeV, CMS should discover the Higgs if it exists. In this paper, we will review CMS's Higgs-discovery potential both in the Standard Model and the Minimal Supersymmetric Standard Model for Higgs bosons produced in gluon-gluon fusion and in vector boson fusion mechanisms. Particular emphasis will be placed on discovery in the early years of running with luminosity of about 2 × 1033cm-2/s.


2019 ◽  
Vol 214 ◽  
pp. 06031 ◽  
Author(s):  
Michael Andrews ◽  
Manfred Paulini ◽  
Sergei Gleyzer ◽  
Barnabas Poczos

An essential part of new physics searches at the Large Hadron Collider (LHC) at CERN involves event classification, or distinguishing potential signal events from those coming from background processes. Current machine learning techniques accomplish this using traditional hand-engineered features like particle 4-momenta, motivated by our understanding of particle decay phenomenology. While such techniques have proven useful for simple decays, they are highly dependent on our ability to model all aspects of the phenomenology and detector response. Meanwhile, powerful deep learning algorithms are capable of not only training on high-level features, but of performing feature extraction. In computer vision, convolutional neural networks have become the state-of-the-art for many applications. Motivated by their success, we apply deep learning algorithms to low-level detector data from the 2012 CMS Simulated Open Data to directly learn useful features, in what we call, end-to-end event classification. We demonstrate the power of this approach in the context of a physics search and offer solutions to some of the inherent challenges, such as image construction, image sparsity, combining multiple sub-detectors, and de-correlating the classifier from the search observable, among others.


Physics ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 84-91 ◽  
Author(s):  
Miguel-Angel Sanchis-Lozano ◽  
Edward K. Sarkisyan-Grinbaum

In this paper, we consider the possibility that a new stage of matter stemming from hidden/dark sectors beyond the Standard Model, to be formed in p p collisions at the LHC (Large Hadron Collider), can significantly modify the correlations among final-state particles. In particular, two-particle azimuthal correlations are studied by means of a Fourier series sensitive to the near-side ridge effect while assuming that hidden/dark particles decay on top of the conventional parton shower. Then, new (fractional) harmonic terms should be included in the Fourier analysis of the azimuthal anisotropies, encoding the hypothetical new physics contribution and enabling its detection in a complementary way to other signatures.


2021 ◽  
Vol 2021 (5) ◽  
Author(s):  
Andreas Papaefstathiou ◽  
Tania Robens ◽  
Gilberto Tetlalmatzi-Xolocotzi

Abstract We investigate the production of three Higgs bosons in the Two Real Singlet extension of the Standard Model, where the scalar sector is augmented by two additional real scalar fields which are singlets under the Standard Model gauge group. The model contains three neutral CP-even scalars, allowing for resonant production and asymmetric decay chains. We focus on the signature pp → h3→ h1h2→ h1h1h1, where we identify h3 as the heaviest scalar state, h2 as the second heaviest and the lightest, h1, as the Standard Model-like Higgs boson discovered by the Large Hadron Collider experiments. The dominant final state occurs when all three Higgs bosons decay to bottom-anti-bottom quark pairs, h1→$$ b\overline{b} $$ b b ¯ , leading to 6 b-jets. Taking into account all current theoretical and experimental constraints, we determine the discovery prospects for this channel in future runs of the Large Hadron Collider, as well as in the high-luminosity phase.


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