Measurement of light-by-light scattering with the ATLAS detector using RUN3 data

Ghizlane Ez-Zobayr,
University Mohammed VI Polytechnic (Institute of Applied Physics)

IAP Physics Seminar Series will occur on Tuesday 23 September, at 11:15 at the UM6P campus (Ryad 8, 1st floor).

Abstract:

The study presents a new measurement of light-by-light scattering in Pb+Pb collisions at a center-of-mass energy per nucleon pair of √sNN = 5.36 TeV, using data collected in 2023. The analysis utilizes a data set with an integrated luminosity of 1.7 nb⁻¹, recorded by the ATLAS experiment at the Large Hadron Collider (LHC). Light-by-light scattering candidates are identified in events featuring the exclusive production of two photons, with the following selection criteria: diphoton invariant mass (mγγ) greater than 4 GeV, diphoton transverse momentum (ptγγ) exceeding 2 GeV, diphoton acoplanarity (Aco) less than 0.01, and photon absolute pseudorapidity |η| within 2.37. Our contribution focuses on measuring the fiducial cross-section and four differential distributions, employing both bin-by-bin unfolding and iterative Bayesian unfolding techniques for the analysis

Biography:

Ghizlane EZ-ZOBAYR : Ghizlane Ez-Zobayr, currently pursuing a PhD in high energy physics at the Institute of Applied Physics, Mohammed VI Polytechnic University, in collaboration with CERN- ATLAS experiment and under the supervision of Professor Yahya Tayalati and Professor Abdelouahed Elfatimy. I earned my bachelor’s degree in physics from Mohammed I University in 2021 and completed a master’s degree in physics of matter and radiation at Mohammed I University in 2023. For my master’s graduation project, I completed an internship at the Institute of Applied Physics, where I worked on the measurement of the W boson mass with the ATLAS detector, graduating as the valedictorian of my class.

Localization: Ryad 8, 1st Floor.

Teams Link:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_NjkxYTFkOTEtMTA2NC00YjE2LWJkYzktMmI2NWE0ZDRmOTRh%40thread.v2/0?context=%7b%22Tid%22%3a%2239626157-a047-4689-87a2-6fa645cb5cb7%22%2c%22Oid%22%3a%22d3bbb26e-fd14-45df-84fa-adbf01366dcc%22%7d