New KAN method anatomizes Pythia-Herwig differences in physics event generation

Researchers have developed a new method using additive Kolmogorov-Arnold Networks (KANs) to analyze the differences between high-energy physics event generators like Pythia and Herwig. This approach allows for a staged functional analysis, breaking down discrepancies at various simulation levels, from hard scattering to hadronization. The study found that differences in multiplicity are prominent at the shower level, while jet mass and shape become more significant after hadronization, with a mixed structure emerging in the full generator configuration. This KAN-based framework offers a detailed functional anatomy of generator-model dependence, revealing persistent structures and support failures. AI

IMPACT Introduces a novel KAN-based framework for dissecting discrepancies in complex simulation models, potentially applicable to other scientific domains.

RANK_REASON The cluster contains an academic paper detailing a new methodology for analyzing differences in physics event generators. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

• Arghya Chattopadhyay
• arXiv
• Herwig
• high energy physics
• Kolmogorov-Arnold Networks
• Pythia

• paper
• other

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