Skip to Content.
Sympa Menu

fizinfo - [Fizinfo] Wigner FK RMI Elméleti Osztály Szemináriuma

fizinfo AT


List archive

[Fizinfo] Wigner FK RMI Elméleti Osztály Szemináriuma

Chronological Thread 
  • From: Balog Janos <balog.janos AT>
  • To: fizinfo AT, rmkiusers AT
  • Subject: [Fizinfo] Wigner FK RMI Elméleti Osztály Szemináriuma
  • Date: Mon, 18 Oct 2021 15:09:09 +0200
  • Authentication-results: (amavisd-new); dkim=pass (1024-bit key) reason="pass (just generated, assumed good)"

Wigner FK RMI Elméleti Osztály Szemináriuma
Tisztelettel meghívjuk

Neelkamal Mallick

"Event shape dependence of azimuthal anisotropy and application of machine learning tools in heavy-ion collisions at the LHC using a multi-phase transport model"

címmel tartandó szemináriumára.


Recently, event shape observables such as transverse
spherocity, has been studied successfully in small collision systems at
the LHC as a tool to separate jetty and isotropic events. In this work,
we have performed an extensive study of charged particles' azimuthal
anisotropy in heavy-ion collisions as a function of spherocity for the
first time using a multi-phase transport (AMPT) model. We have used the
two-particle correlation (2PC) method to estimate the elliptic flow for
different centrality classes in Pb-Pb collisions at sNN−−−√=5.02 TeV for high spherocity, spherocity-integrated and low
spherocity events. It is found that transverse spherocity successfully
differentiates heavy-ion collisions’ event topology based on their
geometrical shapes i.e. high and low values of spherocity. The high-
spherocity events are found to have nearly zero elliptic flow while the
low spherocity events contribute significantly to elliptic flow of
spherocity-integrated events. In the absence of experimental
explorations in this direction, we have implemented the ML-based
regression technique via Gradient Boosting Decision Trees (GBDTs) to
estimate spherocity distributions in Pb-Pb collisions at 5.02 TeV c.m.
energy by training the model with experimentally available event
properties. This ML-model also estimates the impact parameter in heavy-
ion collisions. Throughout this work, we have used final state
observables as the input to the ML-model, which could be easily made
available from collision data. Our method seems to work quite well as
we see a good agreement between the simulated true values and the
predicted values from the ML-model.

(1) Neelkamal Mallick, Raghunath Sahoo, Sushanta Tripathy,
and Antonio Ortiz, J.Phys.G 48 (2021) 4, 045104

(2) Neelkamal Mallick, Sushanta Tripathy, Aditya Nath Mishra,
Suman Deb, and Raghunath Sahoo, Phys.Rev.D 103 (2021) 9, 094031

A szeminárium
Helye: Wigner FK RMI III. ép. Tanácsterem
Ideje: 2021 október 22 péntek d.u. 2 óra

Szívesen látunk minden érdeklődőt.

Balog János

Archive powered by MHonArc 2.6.19+.

Top of Page