Speaker
Description
Event classifiers based on the charged-particle multiplicity have been extensively used in pp collisions at the LHC. However, one drawback of the multiplicity-based event classifiers is that requiring a high charged-particle multiplicity biases the sample towards hard processes. These biases blur the effects of multi-parton interactions (MPI) and make it difficult to pinpoint the origins of fluid-like effects in small systems.
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 identified and unidentified charged particles 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. All the results are compared with predictions from QCD-inspired Monte Carlo event generators.
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