A. Gianelle

collaborators

3 papers

hep-ex2026

Machine learning techniques for jet reconstruction at LHCb and application to the search for $H \to b b ˉ$ and $H \to c c ˉ$ in $s = 13$ TeV $pp$ collisions

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1210

Two machine learning techniques for jet measurements at the LHCb experiment are presented: a regression-based method for jet-energy calibration and a deep neural network algorithm…

hep-ex2025

Evidence for CP violation in $B^{+} \to p p ˉ K^{+}$ decays

LHCb collaboration, R. Aaij, B. Adeva +698

Three-body $B^{+} \to p p K^{+}$ and $B^{+} \to p p I ¨ ^{+}$ decays are studied using a data sample corresponding to an integrated luminosity of 3.0 $f b^{- 1}$ collected by…

physics.acc-ph2025

Interim report for the International Muon Collider Collaboration (IMCC)

C. Accettura, S. Adrian, R. Agarwal +383

The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implemen…

Machine learning techniques for jet reconstruction at LHCb and application to the search for H→bbˉ and H→ccˉ in s​=13 TeV pp collisions

Evidence for CP violation in B+→ppˉ​K+ decays

Interim report for the International Muon Collider Collaboration (IMCC)

Machine learning techniques for jet reconstruction at LHCb and application to the search for $H \to b b ˉ$ and $H \to c c ˉ$ in $s = 13$ TeV $pp$ collisions

Evidence for CP violation in $B^{+} \to p p ˉ K^{+}$ decays