19–21 mai 2025
IPHC
Fuseau horaire Europe/Paris

How to Unfold Top Decays

20 mai 2025, 16:20
15m
Amphi Grünewald (IPHC)

Amphi Grünewald

IPHC

Institut Pluridisciplinaire Hubert Curien 23 rue du Loess 67200 Strasbourg
Methods and Tools Methods and Tools

Orateur

Sofia Palacios Schweitzer (ITP, Heidelberg University)

Description

Many physics analyses at the LHC rely on algorithms to remove detector effect, commonly known as unfolding. Whereas classical methods only work with binned, one-dimensional data, Machine Learning promises to overcome both problems. Using a generative unfolding pipeline, we show how it can be build into an existing LHC analysis, designed to measure the top mass. We discuss the model-dependence of our algorithm, i.e. the bias of our measurement towards the top mass used in simulation and propose a method to reliably achieve unbiased results.

Authors

Alexander Paasch (Hamburg University) Dennis Schwarz (Austrian Academy of Sciences) Luigi Favaro Roman Kogler (University of Hamburg) Sofia Palacios Schweitzer (ITP, Heidelberg University) Tilman Plehn (Heidelberg University)

Documents de présentation