2017/01/26 by T. A. Trainor, Trainor, Thomas A.
Physics and Astronomy · #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #High-Energy Particle Collisions Research #Particle physics theoretical and experimental studies #Quantum Chromodynamics and Particle Interactions
paper · pdf · doi:10.48550/arxiv.1701.07866
openalex publication_date 2017/01/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Dijets observed near midrapidity in high-energy nuclear collisions result from large-angle scattering of low-x partons (gluons) within projectile hadrons as a signature manifestation of QCD. Within the same collisions it has been claimed that hydrodynamic flows (radial, elliptic and "higher harmonic" flows) carried by a dense QCD medium or quark-gluon plasma (QGP) dominate the observed hadronic final state. The flow-QGP narrative is imposed \em a priori on primary particle data, and of all possible analysis methods a subset A that seems to support that narrative is preferred. The present study explores an alternative minimum-bias (MB) jet narrative -- quantitative correspondence of MB dijet manifestations in the hadronic final state with measured \em isolated jet properties. The latter incorporates a different set of methods B that emerge from inductive study of primary particle data without \em a priori assumptions. The resulting system of methods and data manifestations is represented by a two-component (soft + hard) model (TCM) of hadron production. A survey of methods reveals that type A tends to discard substantial information carried by primary particle data whereas type B retains almost all information in both primary particle data from nuclear collisions and from isolated jets. The main goal of the present study is a review of MB dijet contributions to high-energy collisions in small and large systems relative to measured isolated-jet properties. Representative analysis methods from types A and B are compared in the context of MB jet manifestations. This study suggests that at least some data features commonly attributed to flows actually result from MB dijets and thereby challenges the flow-QGP narrative.