Fluctuating Glasma initial conditions and flow in heavy ion collisions

TL;DR

Initial conditions in heavy ion collisions within the color glass condensate framework are computed by combining the impact parameter dependent saturation model with the classical Yang-Mills description of initial Glasma fields.

Abstract

We compute initial conditions in heavy-ion collisions within the Color Glass Condensate (CGC) framework by combining the impact parameter dependent saturation model (IP-Sat) with the classical Yang-Mills description of initial Glasma fields. In addition to fluctuations of nucleon positions, this IP-Glasma description includes quantum fluctuations of color charges on the length-scale determined by the inverse nuclear saturation scale Q_s. The model naturally produces initial energy fluctuations that are described by a negative binomial distribution. The ratio of triangularity to eccentricity is close to that in a model tuned to reproduce experimental flow data. We compare transverse momentum spectra and v_(2,3,4)(p_T) of pions from different models of initial conditions using relativistic viscous hydrodynamic evolution.

Figures (4)

• Figure 1: The IP-Glasma event-by-event distribution in energy for $b=9$ fm on the lattice compared to different functional forms. The negative binomial distribution (NBD) gives the best fit.
• Figure 2: (Color online) Initial energy density (arbitrary units) in the transverse plane in three different heavy-ion collision events: from top to bottom, IP-Glasma, MC-KLN and MC-Glauber Schenke:2011bn models.
• Figure 3: (Color online) Average participant ellipticity (upper panel) and triangularity (lower panel) of the initial state. This calculation (circles), MC-KLN (squares), Glauber implementation with participant and binary collision scaling (triangles).
• Figure 4: (Color online) Thermal $\pi^+$ transverse momentum spectra (upper) and anisotropic flow coefficients $v_2$, $v_3$, and $v_4$ as functions of $p_T$ (lower) from IP-Glasma initial conditions (solid), MC-KLN (dashed), MC-Glauber using participant scaling (dotted) and binary collision scaling (dash-dotted).