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arXiv · 2603.22407

MadNIS at NLO

Giovanni De Crescenzo·Javier Mariño Villadamigo·Nina Elmer·Theo Heimel·Tilman Plehn·Ramon Winterhalder·Marco Zaro
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Abstract

We combine fast amplitude surrogates with neural importance sampling to accelerate NLO calculations. For virtual corrections, a learned ratio to the Born matrix element with calibrated uncertainties guarantees reliable precision across phase space. For real emission, we stick to the standard FKS subtraction and train sector-conditioned surrogates of the regularized integrands away from divergences. MadNIS then uses multi-channel mappings and FKS sectors as conditions. We validate our approach for electron-positron scattering to three and four jets and find significant speed-ups and variance reduction in the integration.

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Giovanni De Crescenzo, Javier Mariño Villadamigo, Nina Elmer, Theo Heimel, Tilman Plehn, Ramon Winterhalder, Marco Zaro. 2026-03-23. MadNIS at NLO. https://arxiv.org/abs/2603.22407

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