Speaker
Subrata Pal
(Tata Institute of Fundamental Research, Mumbai, India)
Description
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 |
|---|
Primary authors
Derek Teaney
(Stony Brook University)
Prof.
Rajeev Bhalerao
(TIFR)
Subrata Pal
(Tata Institute of Fundamental Research, Mumbai, India)
