Investigating the Seebeck effect of the QGP medium using a novel relaxation time approximation model
Abstract: The highly energetic particle medium formed in the ultrarelativistic heavy ion collision displays a notable difference in the temperatures between its central and peripheral regions. This temperature gradient can generate an electric field within the medium, a phenomenon referred to as the Seebeck effect. We have estimated the Seebeck coefficient for a dense quark-gluon plasma medium by using the relativistic Boltzmann transport equation in the recently developed novel relaxation time approximation (RTA) model within the kinetic theory framework. This study explores the Seebeck coefficient of individual quark flavors as well as the entire partonic medium. Our observation indicates that, for given current quark masses, the magnitude of the Seebeck coefficient for each quark flavor as well as for the partonic medium decreases as the temperature rises and increases as the chemical potential increases. Furthermore, we have investigated the Seebeck effect by considering the partonic interactions within the quasiparticle model. In addition, we have presented a comparison between our findings and the results of the standard RTA model. We have observed that the Seebeck coefficient of the QGP medium gets conspicuously decreased in the novel RTA model as compared to that in the standard RTA model. A decreased Seebeck coefficient in the novel RTA model describes a smaller magnitude of induced electric field in the medium than that estimated by the standard RTA model. However, the rate of decline gets gradually smaller as the medium gets hotter for both the current quark mass scenario and the quasiparticle mass scenario. It is also found that, in the noninteracting case, the Seebeck coefficient possesses a slightly negative value in the high temperature region, unlike the quasiparticle description, where the Seebeck coefficient remains positive for the entire temperature range.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.