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Minimum-bias angular and trigger-associated correlations from 200 GeV p-p collisions: jets, flows, centrality and the underlying event

Published 19 Jun 2014 in hep-ex and hep-ph | (1406.5225v1)

Abstract: The mechanisms leading to the hadronic final state of high-energy proton-proton collisions remain an unresolved issue at the RHIC and LHC. A substantial contribution to the hadronic final state from minimum-bias (MB) jets is dominated by non-perturbative processes and may provide the common base for any high-energy dijet. Observation of a same-side (on azimuth)"ridge" in LHC p-p collisions suggests to some that hydrodynamic flows may play a role in that small system at higher energies. The issue of p-p centrality vs triggered jets has emerged in the context of gluon transverse distributions in the proton inferred from DIS data. Attempts have been made to isolate and study the underlying event (UE) complementary to triggered dijets, and it is suggested that multiple parton interactions may contribute to the UE. Reference [1] considered theoretical and experimental results for UE systematics and p-p centrality in the context of a two-component (soft+hard) model derived from single-particle $p_t$ spectrum $n_{ch}$ systematics. The study concluded that there may be a substantial contribution to the UE from the triggered dijet and that p-p centrality is not controlled significantly by a jet trigger condition (if p-p centrality is relevant at all). Further study of two-particle correlations in p-p collisions was called for, particularly the $n_{ch}$ dependence of MB correlations. We report a comprehensive study of MB (no $p_t$ cuts) angular correlations and trigger-associated (TA) $y_t$ correlations (transverse rapidity $y_t = \ln[(m_t + p_t)/m_\pi])$ from 200 GeV p-p collisions. Angular correlations are characterized by 2D model fits that accurately distinguish among proton dissociation structure (soft), jet-related structure (hard) and a nonjet azimuth quadrupole. All angular correlations are simply represented by a (2+1)-component model...

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