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UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2026-06-11 23:58 |
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Conference: Bucharest University Faculty of Physics 2026 Meeting
Section: High-Energy Physics
Title:
Cut-Based and Machine-Learning Methods for W/Z Mass Reconstruction in Diboson Production
Authors:
Victoria-Adriana VARGA (1), Călin ALEXA (2), Daniel COSTACHE (1, 2), Anca DINU (1,2), Ioana DUMINICĂ (1, 2), Roxana ZUS (1)
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Affiliation:
1) Faculty of Physics, University of Bucharest, Atomiștilor 405, RO - 077125, Măgurele, România
2) IFIN-HH, Atomiștilor 409, RO - 077125, Măgurele, România
E-mail
victoria-adriana.varga@s.unibuc.ro
Keywords:
W and Z bosons, Signal to Background Separation, Cut-Based, Machine Learning Algorithms, ATLAS Open Data
Abstract:
This study analyzes how to accurately reconstruct the mass of W and Z bosons in Triple Gauge Coupling processes. This is an important, yet challenging task in high-energy physics, due to the detector's limits and missing transverse energy. The missing energy comes primarily from the invisible neutrinos produced during W boson decays, making it impossible to measure the final state of all particles. Without the momentum of these missing neutrinos, we cannot calculate the exact mass, making it more difficult to separate the signal from background. To solve this problem, we compare two different strategies for mass reconstruction.
On the one hand, the study evaluates a traditional method based on kinematic cuts. This approach uses sequential limits on variables like transverse momentum and mass to find the best signal.
On the other hand, we explore a modern Machine Learning strategy using Boosted Decision Trees (BDT). This algorithm learns patterns from the data to separate the signal from the background much more effectively.
To conclude, by comparing mass distributions, background rejection, and overall efficiency, this research shows the performance of Machine Learning algorithms compared to the traditional approach. This highlights the best computational tools to help us better understand the Standard Model and its technological applications.
References:
[1] Francis Halzen and Alan D. Martin. Quarks and Leptons: An Introductory Course in Modern Particle Physics. John Wiley & Sons, 1984.
[2] ATLAS Collaboration. Measurement of the W ±Z boson pair-production cross section in pp collisions at √s = 13 TeV with the ATLAS detector.
[3] Olaf Behnke, Kevin Kroninger, Gregory Schott, and Thomas Schorner-Sadenius. Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods. John Wiley & Sons, 2013.
[4] L. L. Carter and E. D. Cashwell. Particle-Transport Simulation with the Monte Carlo Method. Technical Information Center, Energy Research and Development Adminis-tration, 1975.
Acknowledgement:
I would like to thank to my supervisors for their mentorship and for making my participation in this conference possible.
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