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We make predictions for the kaon interferometry measurements in Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC). A first order phase transition from a thermalized Quark-Gluon-Plasma (QGP) to a gas of hadrons is assumed for the transport calculations. The fraction of kaons that are directly emitted from the phase boundary is considerably enhanced at large transverse momenta K T ~ 1 GeV/c. In this kinematic region, the sensitivity of the R out/R side ratio to the QGP-properties is enlarged. Here, the results of the 1-dimensional correlation analysis are presented. The extracted interferometry radii, depending on K-Theta, are not unusually large and are strongly affected by momentum resolution effects.
We calculate the kaon HBT radius parameters for high energy heavy ion collisions, assuming a first order phase transition from a thermalized Quark-Gluon-Plasma to a gas of hadrons. At high transverse momenta K_T ~ 1 GeV/c direct emission from the phase boundary becomes important, the emission duration signal, i.e., the R_out/R_side ratio, and its sensitivity to T_c (and thus to the latent heat of the phase transition) are enlarged. Moreover, the QGP+hadronic rescattering transport model calculations do not yield unusual large radii (R_i<9fm). Finite momentum resolution effects have a strong impact on the extracted HBT parameters (R_i and lambda) as well as on the ratio R_out/R_side.
We present calculations of two-pion and two-kaon correlation functions in relativistic heavy ion collisions from a relativistic transport model that includes explicitly a first-order phase transition from a thermalized quark-gluon plasma to a hadron gas. We compare the obtained correlation radii with recent data from RHIC. The predicted R_side radii agree with data while the R_out and R_long radii are overestimated. We also address the impact of in-medium modifications, for example, a broadening of the rho-meson, on the correlation radii. In particular, the longitudinal correlation radius R_long is reduced, improving the comparison to data.