IJS-FMF high-energy physics seminars

Manuel Szewc: Modeling Hadronization with Machine Learning

Europe/Ljubljana
https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09 (F1 tea room)

https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09

F1 tea room

Description

A fundamental part of event generation, hadronization is currently simulated with the help of fine-tuned empirical models. Motivated by the difficulties of these models, in this talk I'll present MLHAD: a proposed alternative where the empirical model is replaced by a surrogate Machine Learning-based model to be ultimately data-trainable. I'll detail the current stage of development and discuss challenges and possible ways forward.