We perform a principal component analysis (PCA) of $v_n(p_T)$ in event-by-event hydrodynamic simulations of Pb+Pb collisions at the Large Hadron Collider. PCA is a statistical technique for extracting the dominant components in fluctuating data. It was suggested to apply it to relativistic collisions  in order to extract the information from event-by-event fluctuations from the two-particle correlation matrix. A generalization was proposed in . Its connection to initial geometry was studied in [3,4]. Here we make a comparison with the data recently presented by the CMS collaboration  for elliptic and triangular flows as well as multiplicity fluctuations.
 Rajeev S. Bhalerao, Jean-Yves Ollitrault, Subrata Pal, Derek Teaney, Phys. Rev. Lett. 114, 152301 (2015), arXiv:1410.7739
 P. Bozek, arXiv:1711.07773
 Aleksas Mazeliauskas and Derek Teaney, Phys. Rev. C 91, 044902 (2015)
 Aleksas Mazeliauskas and Derek Teaney, Phys. Rev. C 93, 024913 (2016)
 CMS Collaboration, arXiv:1708.07133
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