Signature of Granular Structures by Single-Event Intensity Interferometry
arXiv:nucl-th/0411044 · doi:10.1103/PhysRevC.70.064904
Abstract
The observation of a granular structure in high-energy heavy-ion collisions can be used as a signature for the quark-gluon plasma phase transition, if the phase transition is first order in nature. We propose methods to detect a granular structure by the single-event intensity interferometry. We find that the correlation function from a chaotic source of granular droplets exhibits large fluctuations, with maxima and minima at relative momenta which depend on the relative coordinates of the droplet centers. The presence of this type of maxima and minima of a single-event correlation function at many relative momenta is a signature for a granular structure and a first-order QCD phase transition. We further observe that the Fourier transform of the correlation function of a granular structure exhibits maxima at the relative spatial coordinates of the droplet centers, which can provide another signature of the granular structure.
22 pages, 5 figures, in LaTex, to be published in Physical Review C
References in corpus (1)
Cited by in corpus (11)
- Analysis of pion elliptic flows and HBT interferometry in a granular quark-gluon plasma droplet model
- Chaoticity Parameter Lambda in Hanbury-Brown Twiss Interferometry
- The Wigner Function of Produced Particles in String Fragmentation
- Signals in Single-Event Pion Interferometry for Granular Sources of Quark-Gluon Plasma Droplets
- Imaging of granular sources in high energy heavy ion collisions
- Detection of source inhomogeneity through event-by-event two-pion Bose-Einstein correlations
- Explanation of the RHIC HBT Puzzle by a Granular Source of Quark-Gluon Plasma Droplets
- Two-pion interferometry for the granular sources in ultrarelativistic heavy ion collisions
- Fluctuations of pion flow harmonics and HBT correlation functions in ultrarelativistic heavy ion collisions
- Single-Event Handbury-Brown-Twiss Interferometry
- Mini-jet Clustering Algorithm Using Transverse-momentum Seeds in High-energy Nuclear Collisions