Analytic Bjorken flow in one-dimensional relativistic magnetohydrodynamics

In the initial stage of relativistic heavy-ion collisions, strong magnetic fields appear due to the large velocity of the colliding charges. The evolution of these fields appears as a novel and intriguing feature in the fluid-dynamical description of heavy-ion collisions. In this work, we study analytically the one-dimensional, longitudinally boost-invariant motion of an ideal fluid in the presence of a transverse magnetic field. Interestingly, we find that, in the limit of ideal magnetohydrodynamics, i.e., for infinite conductivity, and irrespective of the strength of the initial magnetization, the decay of the fluid energy density $e$ with proper time $\tau$ is the same as for the time-honored "Bjorken flow" without magnetic field. Furthermore, when the magnetic field is assumed to decay $\sim \tau^{-a}$, where $a$ is an arbitrary number, two classes of analytic solutions can be found depending on whether $a$ is larger or smaller than one. In summary, the analytic solutions presented here highlight that the Bjorken flow is far more general than formerly thought. These solutions can serve both to gain insight on the dynamics of heavy-ion collisions in the presence of strong magnetic fields and as testbeds for numerical codes.Comment: 9 pages, 4 figures, corrected typos and symbols, accepted for publication in Phys.Lett.

Effect of intense magnetic fields on reduced-MHD evolution in sNN\sqrt{s_{\rm NN}} = 200 GeV Au+Au collisions

We investigate the effect of large magnetic fields on the $2+1$ dimensional reduced-magnetohydrodynamical expansion of hot and dense nuclear matter produced in $\sqrt{s_{\rm NN}}$ = 200 GeV Au+Au collisions. For the sake of simplicity, we consider the case where the magnetic field points in the direction perpendicular to the reaction plane. We also consider this field to be external, with energy density parametrized as a two-dimensional Gaussian. The width of the Gaussian along the directions orthogonal to the beam axis varies with the centrality of the collision. The dependence of the magnetic field on proper time ($\tau$) for the case of zero electrical conductivity of the QGP is parametrized following [Deng 2012], and for finite electrical conductivity following [Tuchin 2013]. We solve the equations of motion of ideal hydrodynamics for such an external magnetic field. For collisions with non-zero impact parameter we observe considerable changes in the evolution of the momentum eccentricities of the fireball when comparing the case when the magnetic field decays in a conducting QGP medium and when no magnetic field is present. The elliptic-flow coefficient $v_2$ of $\pi^{-}$ is shown to increase in the presence of an external magnetic field and the increment in $v_2$ is found to depend on the evolution and the initial magnitude of the magnetic field.Comment: 12 pages, 6 figures, new discussion added, published in Phys.Rev.

A New Correlator to Detect and Characterize the Chiral Magnetic Effect

A charge-sensitive in-event correlator is proposed and tested for its efficacy to detect and characterize charge separation associated with the Chiral Magnetic Effect (CME) in heavy ion collisions. Tests, performed with the aid of two reaction models, indicate discernible responses for background- and CME-driven charge separation, relative to the second- ($\Psi_{2}$) and third-order ($\Psi_{3}$) event planes, which could serve to identify the CME. The tests also indicate a degree of sensitivity which would enable robust characterization of the CME via Anomalous Viscous Fluid Dynamics (AVFD) model comparisons.Comment: 5 pages, 5 Figs.; Published versio

Inclusive Artificial Intelligence

Prevailing methods for assessing and comparing generative AIs incentivize responses that serve a hypothetical representative individual. Evaluating models in these terms presumes homogeneous preferences across the population and engenders selection of agglomerative AIs, which fail to represent the diverse range of interests across individuals. We propose an alternative evaluation method that instead prioritizes inclusive AIs, which provably retain the requisite knowledge not only for subsequent response customization to particular segments of the population but also for utility-maximizing decisions