AI RESEARCH
Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations
arXiv CS.LG
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ArXi:2605.07460v1 Announce Type: new Accurate Monte Carlo (MC) modelling in high-energy physics is challenging, particularly in complex scenarios where simulations fail to reproduce observed data. In practice, experimental information is often limited to one-dimensional (1D) distributions, while mismodelling arises in a multidimensional feature space. This restricts traditional correction methods, as one-dimensional reweighting ignores correlations and fully multidimensional approaches require large target datasets.