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Related Experiment Videos

Cronin effect in hadron production off nuclei.

B Z Kopeliovich1, J Nemchik, A Schäfer

  • 1Max-Planck Institut für Kernphysik, Postfach 103980, 69029 Heidelberg, Germany.

Physical Review Letters
|June 13, 2002
PubMed
Summary

This study explains the Cronin effect, a nuclear enhancement of high-energy hadrons, using a novel light-cone QCD-dipole model. The new approach predicts particle behavior without fitting data, revealing energy-dependent mechanisms.

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Area of Science:

  • High Energy Physics
  • Nuclear Physics
  • Quantum Chromodynamics

Background:

  • The Cronin effect describes the nuclear enhancement of high-transverse momentum (pT) hadrons observed in particle collisions.
  • Existing models for the Cronin effect often require fitting to experimental data, limiting their predictive power.
  • Recent data from the Relativistic Heavy Ion Collider (RHIC) has renewed interest in quantitatively understanding this phenomenon.

Purpose of the Study:

  • To develop a new phenomenological description of the Cronin effect.
  • To explain experimental data without relying on data fitting.
  • To provide predictions for particle production in proton-a (pA) collisions at RHIC and the Large Hadron Collider (LHC).

Main Methods:

  • Utilizing a light-cone Quantum Chromodynamics (QCD)-dipole approach.

Related Experiment Videos

  • Developing a phenomenological model based on established theoretical frameworks.
  • Analyzing the energy dependence of hadron production mechanisms.

    • Main Results:

    • The developed model successfully explains existing experimental data for the Cronin effect without fitting.
    • The model provides predictions for future experiments at RHIC and LHC.
    • A significant shift in the underlying production mechanism from incoherent to coherent processes at high energies was identified.

    Conclusions:

    • The light-cone QCD-dipole approach offers a robust framework for understanding the Cronin effect.
    • The energy-dependent nature of the underlying mechanism is crucial for accurate predictions.
    • This work provides a data-driven, predictive tool for high-energy nuclear physics research.