Factorization in the model of unstable particles with continuous masses

Kuksa, V.; Volchanskiy, N.

doi:10.48550/arxiv.1109.1541

Cited by 1 publication

(1 citation statement)

References 58 publications

(113 reference statements)

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“…In fact, within the context of Quantum Field Theory, a large value for the width implies that the particle is highly non-local and the narrow-width approximation is no longer valid calling for a more robust framework to describe it (see e.g. [25][26][27]). Such a scenario is not relevant for the charged VLL as the mixing element U MIX must be small due to EW constraints involving Higgs and Z boson decays.…”

Section: The Modelsmentioning

confidence: 99%

Deep learning searches for vector-like leptons at the LHC and electron/muon colliders

et al. 2023

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The discovery potential of both singlet and doublet vector-like leptons (VLLs) at the Large Hadron Collider (LHC) as well as at the not-so-far future muon and electron machines is explored. The focus is on a single production channel for LHC direct searches while double production signatures are proposed for the leptonic colliders. A Deep Learning algorithm to determine the discovery (or exclusion) statistical significance at the LHC is employed. While doublet VLLs can be probed up to masses of 1 TeV, their singlet counterparts have very low cross sections and can hardly be tested beyond a few hundreds of GeV at the LHC. This motivates a physics-case analysis in the context of leptonic colliders where one obtains larger cross sections in VLL double production channels, allowing to probe higher mass regimes otherwise inaccessible even to the LHC high-luminosity upgrade.

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Section: The Modelsmentioning

confidence: 99%