VLQBounds is a modular Python tool that compares VLQ parameter points to LHC pair and single production limits via grid interpolation and returns 95% CL exclusion verdicts.
Aadet al.(ATLAS), JHEP11, 168, arXiv:2308.02595 [hep-ex]
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XGBoost multivariate analysis extends the 5-sigma discovery reach for singly produced vector-like bottom quarks decaying via heavy neutral Higgs bosons to 1.6 TeV at the HL-LHC with 3 ab^{-1}.
ATLAS Inner Detector track and vertex reconstruction maintains high efficiency, good resolution, and low fake rates for up to 80 simultaneous proton-proton interactions in Run 2 and Run 3 data and simulations.
citing papers explorer
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VLQBounds: Confronting Vector-Like Quark Models with LHC Searches
VLQBounds is a modular Python tool that compares VLQ parameter points to LHC pair and single production limits via grid interpolation and returns 95% CL exclusion verdicts.
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Probing Heavy Neutral Higgs Bosons via Single Vector-Like Bottom Quark Production at the HL-LHC
XGBoost multivariate analysis extends the 5-sigma discovery reach for singly produced vector-like bottom quarks decaying via heavy neutral Higgs bosons to 1.6 TeV at the HL-LHC with 3 ab^{-1}.
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Track and Vertex Reconstruction with the ATLAS Inner Detector
ATLAS Inner Detector track and vertex reconstruction maintains high efficiency, good resolution, and low fake rates for up to 80 simultaneous proton-proton interactions in Run 2 and Run 3 data and simulations.