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Negative Sidewards Flow in Nucleus-Nucleus Collisions and the Equation of State

  • Jean Péter
Part of the NATO ASI Series book series (NSSB, volume 321)

Abstract

The multidetector array Mur + Tonneau has been used to perform a 4π detection of charged particles and fragments emitted in reactions at energies ranging from 36 to 95 MeV/u. The collective transverse momentum in the reaction plane (sidewards flow parameter) is observed to strongly vary as a function of impact parameter and incident energy. The measured values have to be corrected for the effects due to the error on the reaction plane determination and to the detector limitations. Those limitations caused by the method itself are more important than those caused by the detector. The flow parameter changes from negative values (negative scattering) at low energies to slightly positive values (compression), at the highest energies. For the system 40Ar+27A1, the inversion (or balance) energy is in the range 80-100 MeV/u, depending on the impact parameter value. Theoretical studies (BUU, Landau-Vlasov, QMD) show that the flow, and especially the inversion energy, is sensitive to the nucleon-nucleon cross section 6NN in medium. A comparison to the data indicates that a momentum dependent effective interaction should be used. Then, the flow value is not much sensitive to the incompressibility modulus K, but possibly in peripheral collisions. Additionnal observables should be used. The azimuthal distribution of mid-rapidity particles indicates a rotation-like behaviour of the participants which is reproduced by BUU calculations.

Keywords

Transverse Momentum Impact Parameter Flow Parameter Flow Angle Reaction Plane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Jean Péter
    • 1
  1. 1.L.P.C. - ISMRA, CNRS-IN2P3Boulevard du Maréchal JuinCaen CedexFrance

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