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SUMMARY:Principal Component Analysis of Correlation Data without Nonflow E
 ffects
DTSTART;VALUE=DATE-TIME:20160524T160000Z
DTEND;VALUE=DATE-TIME:20160524T162000Z
DTSTAMP;VALUE=DATE-TIME:20190325T155634Z
UID:indico-contribution-1978306@indico.cern.ch
DESCRIPTION:Speakers: Rajeev Bhalerao (TIFR)\nWe extend the recently prese
 nted Principal Component Analysis (PCA)\nmethod to reduce the nonflow effe
 cts present in the two-particle\ncorrelation data. We illustrate this tech
 nique by applying it to\nsimulated pseudorapidity correlation data obtaine
 d with A Multi-Phase\nTransport (AMPT) model for Pb-Pb collisions at the L
 HC energy 2.76 TeV. \nMeasurable subleading modes are seen in the\nellipti
 c and triangular flows as a function of pseudorapidity.\nAlthough we show 
 here only two-particle correlation results\, the technique is\napplicable 
 to also multi-particle correlations.\n\nhttps://indico.cern.ch/event/46985
 7/contributions/1978306/
LOCATION:Centro de Congressos\, Instituto Superior Técnico\, Alameda Camp
 us Room 02.2
URL:https://indico.cern.ch/event/469857/contributions/1978306/
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