Profil bibliographique

Erik Butz

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

3Publications signalées
0Citations signalées
0Affiliations récentes

Les domaines associés

Particle physics theoretical and experimental studiesHigh-Energy Particle Collisions ResearchComputational Physics and Python ApplicationsQuantum Chromodynamics and Particle InteractionsParticle Detector Development and Performance

Les publications récentes

Accès ouvert 2025 article OpenAlex

Characterization of the quantum state of top quark pairs produced in proton-proton collisions at $\sqrt{s}$ = 13 TeV using the beam and helicity bases

Aram Hayrapetyan, Vladimir Makarenko, A. Tumasyan, Wolfgang Adam et autres

Measurements of the spin correlation coefficients in the beam basis are presented for top quark-antiquark ($\mathrm{t\bar{t}}$) systems produced in proton-proton collisions at $\sqrt{s}$ = 13 TeV collected by the CMS experiment in 2016$-$2018, and corresponding to an integrated luminosity of 138 fb$^{-1}$. …

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0 citations Desy publication database (The Deutsches Elektronen-Synchrotron)
Accès ouvert 2025 article OpenAlex

Search for charged Higgs bosons decaying into top and bottom quarks in lepton+jets final states in proton-proton collisions at $\sqrt{s}$ = 13 TeV

Aram Hayrapetyan, Vladimir Makarenko, A. Tumasyan, Wolfgang Adam et autres

A search is presented for charged Higgs bosons (H$^\pm$) in proton-proton (pp) collision events via the pp $\to$ (b)H$^\pm$ processes, with H$^\pm$ decaying into top (t) and bottom (b) quarks. The search targets final states with one lepton, missing transverse momentum, and …

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0 citations Desy Publications Database (Deutsches Elektronen-Synchrotron DESY)
Accès ouvert 2025 article OpenAlex

Machine-learning techniques for model-independent searches in dijet final states

Aram Hayrapetyan, Vladimir Makarenko, A. Tumasyan, Wolfgang Adam et autres

Anomaly detection methods used in a recent search for new phenomena by CMS at the CERN LHC are presented. The methods use machine learning to detect anomalous jets produced in the decay of new massive particles. The effectiveness of these approaches in …

de (code pays fourni par la source)

0 citations Desy Publications Database (Deutsches Elektronen-Synchrotron DESY)
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