Orateur
Description
Event classifiers based either on the charged-particle multiplicity or on event topologies, such as spherocity and underlying event activity, have been extensively used in proton-proton (pp) collisions by the ALICE Collaboration at the LHC. These event classifiers became important tools since the observation of fluid-like behavior in high multiplicity pp collisions as for example radial and anisotropic flow. Furthermore, the study as a function of the charged-particle multiplicity allowed for the discovery of strangeness enhancement in high-multiplicity pp collisions. However, one drawback of the multiplicity-based event classifiers is that requiring a high charged-particle multiplicity biases the sample towards hard processes like multijet final states. These biases blur the effects of multi-parton interactions (MPI) and make it difficult to pinpoint the origins of fluid-like effects.
This contribution exploits a new event classifier, the charged-particle flattenicity, defined in ALICE using the charged-particle multiplicity estimated in 2.8 < $\eta$ < 5.1 and −3.7 < $\eta$ < −1.7 intervals. New final results on the production of pions, kaons, protons, and unidentified charged particles at midrapidity (|$\eta$| < 0.8) as a function of flattenicity in pp collisions at $\sqrt{s}$ = 13 TeV will be discussed. It will be shown how flattenicity can be used to select events more sensitive to MPI and less sensitive to final-state hard processes. All the results are compared with predictions from QCD-inspired Monte Carlo event generators such as PYTHIA and EPOS. Finally, an outlook on using the flattenicity estimator using Run3 data will be shown.
