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- heavy ion collisions (7) (remove)
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Azimuthal correlations of pions in relativistic heavy ion collisions at 1 GeV/nucl.
(1995)
- Triple differential cross sections of pions in heavy ion collisions at 1 GeV/nucl. are studied with the IQMD model. After discussing general properties of resonance and pion production we focus on azimuthal correlations: At projectile- and target-rapidities we observe an anticorrelation in the in-plane transverse momentum between pions and protons. At c.m.-rapidity, however, we find that high pt pions are being preferentially emitted perpendicular to the event-plane. We investigate the causes of those correlations and their sensitivity on the density and momentum dependence of the real and imaginary part of the nucleon and pion optical potential.
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Nucleus-nucleus collisions at highest energies
(1996)
- The microscopic phasespace approach URQMD is used to investigate the stopping power and particle production in heavy systems at SPS and RHIC energies. We find no gap in the baryon rapidity distribution even at RHIC. For CERN energies URQMD shows a pile up of baryons and a supression of multi-nucleon clusters at midrapidity.
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Intermediate mass dileptons from secondary Drell-Yan processes
(1998)
- Recent reports on enhancements of intermediate and hight mass muon pairs producedin heavy ion collisions have attracted much attention.
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Excitation function of energy density and partonic degrees of freedom in relativistic heavy ion collisions
(1998)
- We estimate the energy density epsilon pile-up at mid-rapidity in central Pb+Pb collisions from 2 200 GeV/nucleon. epsilon is decomposed into hadronic and partonic contributions. A detailed analysis of the collision dynamics in the framework of a microscopic transport model shows the importance of partonic degrees of freedom and rescattering of leading (di)quarks in the early phase of the reaction for Elab 30 GeV/nucleon. In Pb+Pb collisions at 160 GeV/nucleon the energy density reaches up to 4 GeV/fm3, 95% of which are contained in partonic degrees of freedom.
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Dissociation of expanding c anti-c states in heavy ion collisions
(1999)
- We study J/psi suppression in AB collisions assuming that the charmonium states evolve from small, color transparent configurations. Their interaction with nucleons and nonequilibrated, secondary hadrons is simulated using the microscopic model UrQMD. The Drell-Yan lepton pair yield and the J/psi Drell-Yan ratio are calculated as a function of the neutral transverse energy in Pb+Pb collisions at 160 GeV and found to be in reasonable agreement with existing data.
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Modeling J /Psi production and absorption in a microscopic nonequilibrium approach
(1999)
- Charmonium production and absorption in heavy ion collisions is studied with the Ultrarelativisitic Quantum Molecular Dynamics model. We compare the scenario of universal and time independent color-octet dissociation cross sections with one of distinct color-singlet J/psi, psi 2 and CHIc states, evolving from small, color transparent configurations to their asymptotic sizes. The measured J/psi production cross sections in pA and AB collisions at SPS energies are consistent with both purely hadronic scenarios. The predicted rapidity dependence of J/psi suppression can be used to discriminate between the two experimentally. The importance of interactions with secondary hadrons and the applicability of thermal reaction kinetics to J/psi absorption are in- vestigated. We discuss the e ect of nuclear stopping and the role of leading hadrons. The dependence of the 2/J/psi ratio on the model assumptions and the possible influence of refeeding processes is also studied.
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Neural networks for impact parameter determination
(1996)
- Abstract: An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input generation for the network is proposed, namely the transverse and longitudinal momentum distribution of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of two as compared to classical techniques. To achieve this improvement simple network architectures and a 5 × 5 input grid in (pt, pz) space are suffcient.
