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This content will become publicly available on February 17, 2026

Title: Describing hadronization via histories and observables for Monte-Carlo event reweighting
We introduce a novel method for extracting a fragmentation model directly from experimental data without requiring an explicit parametric form, called Histories and Observables for Monte-Carlo Event Reweighting (HOMER), consisting of three steps: the training of a classifier between simulation and data, the inference of single fragmentation weights, and the calculation of the weight for the full hadronization chain. We illustrate the use of HOMER on a simplified hadronization problem, aq\bar{q} q q string fragmenting into pions, and extract a modified Lund string fragmentation functionf(z) f ( z ) . We then demonstrate the use of HOMER on three types of experimental data: (i) binned distributions of high-level observables, (ii) unbinned event-by-event distributions of these observables, and (iii) full particle cloud information. After demonstrating thatf(z) f ( z ) can be extracted from data (the inverse of hadronization), we also show that, at least in this limited setup, the fidelity of the extractedf(z) f ( z ) suffers only limited loss when moving from (i) to (ii) to (iii). Public code is available at https://gitlab.com/uchep/mlhad.  more » « less
Award ID(s):
2411215 2417682 2103889
PAR ID:
10615029
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
SciPost
Date Published:
Journal Name:
SciPost Physics
Volume:
18
Issue:
2
ISSN:
2542-4653
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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