Fluctuating hydrodynamics confronts rapidity dependence of p T -correlations Rajendra Pokharel 1, Sean Gavin 1 and George Moschelli 2 1 Wayne State University.

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Presentation transcript:

Fluctuating hydrodynamics confronts rapidity dependence of p T -correlations Rajendra Pokharel 1, Sean Gavin 1 and George Moschelli 2 1 Wayne State University 2 Frankfurt Institute of Advanced Studies Hot Quark 2012 Oct 14-20Copamarina, Puerto Rico

Outlines o Motivation o Viscosity and Hydrodynamics of Fluctuations o Diffusion of p t correlations o Results and STAR measurements o Summary

o Modification of transverse momentum fluctuations by viscosity o Transverse momentum fluctuations have been used as an alternative measure of viscosity o Estimate the impact of viscosity on fluctuations using best information on EOS, transport coefficients, and fluctuating hydrodynamics Motivation Sean Gavin & Mohamed Abdel-Aziz, Phys. Rev. Lett. 97 (2006) STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467

o Small variations of initial transverse flow in each event o Viscosity arises as the fluid elements shear past each other o Shear viscosity drives the flow toward the average o damping of radial flow fluctuations  viscosity Sean Gavin & Mohamed Abdel-Aziz, Phys. Rev. Lett. 97 (2006) Fluctuations of transverse flow

Helmholtz decomposition: Momentum density current Transverse momentum fluctuations First, from non-relativistic hydro: Linearized Navier-Stokes  viscous diffusion Transverse modes: sound waves (damped by viscosity) Longitudinal modes: It is the transverse modes that we are interested in.

Dissipative relativistic hydrodynamics Conservation of energy-momentum: ideal dissipative  Equations of relativistic viscous hydrodynamics First order (Navier-Stokes) hydro: Second order (Israel-Stewart) hydro: A. Muronga, Phys.Rev. C69, (2004)

Linearized hydro and diffusion of flow fluctuations Linearized Navier-Stokes for transverse flow fluctuations:  g transverse component Linearized Israel-Stewart for transverse flow fluctuations:  First order diffusion violates causality! This saves causality!

Two-particle transverse momentum correlations and first order diffusion satisfies the diffusion equation  r satisfies  Two-particle momentum correlation first order Sean Gavin & Mohamed Abdel-Aziz, Phys. Rev. Lett. 97 (2006)

is temp. dependent T. Hirano and M. Gyulassy, Nucl. Phys. A769, 71(2006), nucl-th/ EOS I -> Lattice s95p-v1 EOS II -> Hirano & Gyulassy T. Hirano and M. Gyulassy, Nucl. Phys. A769, 71(2006), nucl-th/ P. Huovinen and P. Petreczky, Nucl.Phys. A837, 26(2010), Second order diffusion of transverse momentum correlations Entropy density s(T) depends on equation of state (EOS)

Entropy density and EOS EOS I and EOS II T. Hirano and M. Gyulassy, Nucl. Phys. A769, 71(2006), nucl-th/ Entropy production ideal: first order: second order: We have used used both in our numerical solutions. A. Muronga, Phys.Rev. C69, (2004) Lattice: P. Huovinen and P. Petreczky, Nucl.Phys. A837, 26(2010),

Diffusion vs Waves Diffusion fills the gap in between the propagating Wave Rapidity separation of the fronts saturates

Choosing different initial widths Smaller initial widths resolves better R. Pokharel, S. Gavin, G. Moschelli in preparation Initial correlation is a normalized Gaussian Constant diffusion coefficient used in these examples plots

STAR measured these correlations Sean Gavin & Mohamed Abdel-Aziz, Phys. Rev. Lett. 97 (2006) STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467

STAR measured these correlations STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467 Measured: rapidity width of near side peak – the ridge Fit peak + constant offset Offset is ridge, i.e., long range rapidity correlations Report rms width of the peak Central vs. peripheral increase consistent with

NeXSPheRIO: Sharma et al., Phys.Rev. C84 (2011) STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467 NeXSPheRIO Fluctuating ideal hydro, NeXSPheRIO vs Ideal hydro NeXSPheRIO calculations of width fails match the STAR data

Results R. Pokharel, S. Gavin, G. Moschelli in preparation Numerical results vs STAR Relaxation time: τ π = 5-6, AMY, Phys. Rev. D79, (2009), τ π = 6.3, J. Hong, D. Teaney, and P. M. Chesler (2011), STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467

Results R. Pokharel, S. Gavin, G. Moschelli in preparation C : second order vs STAR STAR: H. Agakishiev et al, Phys.Lett. B704 (2011) 467 STAR unpublished data: M. Sharma and C. Pruneau, private communications. Bumps in central to mid-central case in data and second order diffusion calculations No such bumps in the first order case means bumps are second order diffusion phenomena First and second order entropy production equations give virtually the same results (plots not shown here).

Results 10-20% Evolution of C for 10-20% Second order vs first order R. Pokharel, S. Gavin, G. Moschelli in preparation

Results

Summary  First order hydro calculations do poor job in fitting the experimental (STAR) data.  NeXSPheRIO calculations (ideal hydro + fluctuations) of width show opposite trend in the variation of width with centralities compared to the data.  Widths given by second order diffusion agrees with STAR data.  Second order diffusion calculations show bumps in C for central to mid-central cases and this is also indicated by data.  Theory the bumps is clear: pronounced effect of wave part of the causal diffusion equation.

Thank You

Notations & conventions: Backups R. Baier, P. Romatschke, and U. A. Wiedemann, Phys.Rev. C73, (2006), U. W. Heinz, H. Song, and A. K. Chaudhuri, Phys.Rev. C73, (2006)