Subrata Pal (Tata Institute of Fundamental Research, Mumbai, India)
We present a new method for analyzing anisotropic flow, $v_n$, from the eigenmodes and eigenvalues of the two-particle correlation matrix $\langle\cos n\Delta\phi\rangle$, where $\Delta\phi$ is the azimuthal separation between two particles (in general from different pseudorapidity bins), and angular brackets denote an average over pairs of particles. Methods currently used to analyze anisotropic flow (event plane method, cumulant method) were devised before the importance of flow fluctuations was recognized. Our new method uses more detailed information on how the azimuthal correlation depends on the pseudorapidity (and/or transverse momentum) of both particles. This information can be used to extract flow fluctuations directly from experiment. When correlations are due to flow, all the eigenvalues are positive. The eigenmode analysis allows to write the correlation matrix as a sum, where each term in the sum corresponds to a different component of flow fluctuations. The largest eigenvalue corresponds to the usual rms $v_n$, which depends little on the pseudorapidity $\eta$, while the next-to-largest eigenvalues yield modes which typically oscillate as a function of $\eta$, and which correspond to flow fluctuations. We study the effect of nonflow correlations, and statistical errors. We test the applicability of this new method with Monte-Carlo simulations using the transport model AMPT.
|On behalf of collaboration:||None|
Derek Teaney (Stony Brook University) Prof. Rajeev Bhalerao (TIFR) Subrata Pal (Tata Institute of Fundamental Research, Mumbai, India)