16 citations · 23 across the 18 of their papers we have counts for
9 papers · 1 filter
Branching fraction measurement of the decay at high dihadron mass
LHCb collaboration, R. Aaij, M. Abdelfatah +1103
This Letter presents the first measurement of the differential branching fraction in the region of the dihadron mass, , $1000< m_{…
Branching fraction measurements of and anomalous decays
LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1187
Branching fractions of and anomalous decays are measured using collision data at a center-of-mass energy of collected by the LHCb exper…
Search for meson decays to multimuon final states
LHCb collaboration, R. Aaij, M. Abdelfatah +1109
A search for decays of mesons to final states with four or six muons using collision data recorded by the LHCb experiment corresponding to an integrated luminosity of $5.4…
Observation of several sources of violation in decays
LHCb collaboration, R. Aaij, M. Abdelfatah +1116
An amplitude analysis of decays is presented in which six -violating phenomena are judged to be of significance for the first time. This analysis is b…
Resolution of outstanding puzzles in decays
LHCb collaboration, R. Aaij, M. Abdelfatah +1116
An amplitude analysis of decays is presented, based on collision data recorded with the LHCb detector in 2011--2012, corresponding to an integrated lum…
Amplitude analysis of decays
LHCb collaboration, R. Aaij, M. Abdelfatah +1116
The branching fractions and quasi-two-body -violating asymmetries of intermediate states obtained through an amplitude analysis of the charmless three-body decay $B^+ \!\to K…
Observation of the charmless purely baryonic decay
LHCb collaboration, R. Aaij, M. Abdelfatah +1103
A search for the charmless purely baryonic decay is performed using proton-proton collision data recorded by the LHCb experi…
Measurement of using and decays with and
LHCb collaboration, R. Aaij, M. Abdelfatah +1105
A measurement of the CKM angle using the decay channels and , where the meson decays to $D\rightarrow K_{\rm S}^{…
Machine learning techniques for jet reconstruction at LHCb and application to the search for and in TeV collisions
LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1194
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…