Transport Phenomena In Dissipative Heavy Ion Collisions PDF Download

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Energy Research Abstracts

Energy Research Abstracts
Author:
Publisher:
Total Pages: 872
Release: 1988
Genre: Power resources
ISBN:

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Energy Research Abstracts

Energy Research Abstracts
Author:
Publisher:
Total Pages: 890
Release: 1988
Genre: Power resources
ISBN:

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Treatise on Heavy Ion Science

Treatise on Heavy Ion Science
Author: D.A. Bromley
Publisher: Springer Science & Business Media
Total Pages: 748
Release: 2012-12-06
Genre: Science
ISBN: 1461580943

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Chiral Magnetic and Vortical Effects in High-energy Nuclear Collisions--A Status Report

Chiral Magnetic and Vortical Effects in High-energy Nuclear Collisions--A Status Report
Author:
Publisher:
Total Pages: 28
Release: 2016
Genre:
ISBN:

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Here, the interplay of quantum anomalies with magnetic field and vorticity results in a variety of novel non-dissipative transport phenomena in systems with chiral fermions, including the quark-gluon plasma. Among them is the Chiral Magnetic Effect (CME)--the generation of electric current along an external magnetic field induced by chirality imbalance. Because the chirality imbalance is related to the global topology of gauge fields, the CME current is topologically protected and hence non-dissipative even in the presence of strong interactions. As a result, the CME and related quantum phenomena affect the hydrodynamical and transport behavior of strongly coupled quark-gluon plasma, and can be studied in relativistic heavy ion collisions where strong magnetic fields are created by the colliding ions. Evidence for the CME and related phenomena has been reported by the STAR Collaboration at Relativistic Heavy Ion Collider at BNL, and by the ALICE Collaboration at the Large Hadron Collider at CERN. The goal of the present review is to provide an elementary introduction into the physics of anomalous chiral effects, to describe the current status of experimental studies in heavy ion physics, and to outline the future work, both in experiment and theory, needed to eliminate the existing uncertainties in the interpretation of the data.