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Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning

A Gavrikov, A Serafini, D Dolzhikov… - arXiv preprint arXiv …, 2025 - arxiv.org
Physics paper physics.data-an Suggest

… We propose a solution using neural likelihood estimation within the simulation-based inference framework. We develop two complementary neural density estimators …

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BibTeX

@misc{gavrikov2025simulationbasedinferenceprecisionneutrino,
      title={Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning}, 
      author={A. Gavrikov and A. Serafini and D. Dolzhikov and A. Garfagnini and M. Gonchar and M. Grassi and R. Brugnera and V. Cerrone and L. V. D'Auria and R. M. Guizzetti and L. Lastrucci and G. Andronico and V. Antonelli and A. Barresi and D. Basilico and M. Beretta and A. Bergnoli and M. Borghesi and A. Brigatti and R. Bruno and A. Budano and B. Caccianiga and A. Cammi and R. Caruso and D. Chiesa and C. Clementi and C. Coletta and S. Dusini and A. Fabbri and G. Felici and G. Ferrante and M. G. Giammarchi and N. Giudice and N. Guardone and F. Houria and C. Landini and I. Lippi and L. Loi and P. Lombardi and F. Mantovani and S. M. Mari and A. Martini and L. Miramonti and M. Montuschi and M. Nastasi and D. Orestano and F. Ortica and A. Paoloni and L. Pelicci and E. Percalli and F. Petrucci and E. Previtali and G. Ranucci and A. C. Re and B. Ricci and A. Romani and C. Sirignano and M. Sisti and L. Stanco and E. Stanescu Farilla and V. Strati and M. D. C Torri and C. Tuvè and C. Venettacci and G. Verde and L. Votano},
      year={2025},
      eprint={2507.23297},
      archivePrefix={arXiv},
      primaryClass={physics.data-an},
      url={https//arxiv.org/abs/2507.23297}, 
}

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