Boosted decision tree reweighting of simulated neutrino interactions for $O(1)$ GeV neutrino cross section measurements
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2025
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| author | Lin, Z. Akhter, S. Dar, Z. Ahmad Alex, N. S. Betancourt, M. Boyd, S. Budd, H. Caceres, G. Díaz, G. A. Felix, J. Fields, L. Gago, A. M. Gaur, P. K. Gilligan, S. M. Gran, R. Harris, D. A. Hart, A. L. Kleykamp, J. Klustová, A. Last, D. Lozano, A. Lu, X. -G. Manly, S. Mann, W. A. McFarland, K. S. Moreno, O. Nelson, J. K. Paolone, V. Perdue, G. N. Pernas, C. Ramírez, M. A. Roy, N. Ruterbories, D. Schellman, H. Salinas, C. J. Solano Correia, D. S. Sultana, M. Vaughan, N. H. Waldron, A. V. Yaeggy, B. Zazueta, L. |
| author_facet | Lin, Z. Akhter, S. Dar, Z. Ahmad Alex, N. S. Betancourt, M. Boyd, S. Budd, H. Caceres, G. Díaz, G. A. Felix, J. Fields, L. Gago, A. M. Gaur, P. K. Gilligan, S. M. Gran, R. Harris, D. A. Hart, A. L. Kleykamp, J. Klustová, A. Last, D. Lozano, A. Lu, X. -G. Manly, S. Mann, W. A. McFarland, K. S. Moreno, O. Nelson, J. K. Paolone, V. Perdue, G. N. Pernas, C. Ramírez, M. A. Roy, N. Ruterbories, D. Schellman, H. Salinas, C. J. Solano Correia, D. S. Sultana, M. Vaughan, N. H. Waldron, A. V. Yaeggy, B. Zazueta, L. |
| contents | This paper illustrates a generic method for multi-dimensional reweighting of $O(1)$ GeV neutrino interaction Monte Carlo samples. The reweighting is based on a Boosted Decision Tree algorithm trained on high-dimensional space in detector final-state observables. This enables one generator's events to be reweighted so that its reconstructed particle content and kinematics distributions, as well as detector efficiency, match those of a target model. The approach establishes an efficient way to reuse legacy Monte Carlo data, avoiding re-generation. As an example, we test its use in a measurement of transverse kinematic imbalance of the $μ^-$ and proton in charged-current quasielastic like $ν_μ$ events from the MINERvA experiment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07463 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Boosted decision tree reweighting of simulated neutrino interactions for $O(1)$ GeV neutrino cross section measurements Lin, Z. Akhter, S. Dar, Z. Ahmad Alex, N. S. Betancourt, M. Boyd, S. Budd, H. Caceres, G. Díaz, G. A. Felix, J. Fields, L. Gago, A. M. Gaur, P. K. Gilligan, S. M. Gran, R. Harris, D. A. Hart, A. L. Kleykamp, J. Klustová, A. Last, D. Lozano, A. Lu, X. -G. Manly, S. Mann, W. A. McFarland, K. S. Moreno, O. Nelson, J. K. Paolone, V. Perdue, G. N. Pernas, C. Ramírez, M. A. Roy, N. Ruterbories, D. Schellman, H. Salinas, C. J. Solano Correia, D. S. Sultana, M. Vaughan, N. H. Waldron, A. V. Yaeggy, B. Zazueta, L. High Energy Physics - Experiment This paper illustrates a generic method for multi-dimensional reweighting of $O(1)$ GeV neutrino interaction Monte Carlo samples. The reweighting is based on a Boosted Decision Tree algorithm trained on high-dimensional space in detector final-state observables. This enables one generator's events to be reweighted so that its reconstructed particle content and kinematics distributions, as well as detector efficiency, match those of a target model. The approach establishes an efficient way to reuse legacy Monte Carlo data, avoiding re-generation. As an example, we test its use in a measurement of transverse kinematic imbalance of the $μ^-$ and proton in charged-current quasielastic like $ν_μ$ events from the MINERvA experiment. |
| title | Boosted decision tree reweighting of simulated neutrino interactions for $O(1)$ GeV neutrino cross section measurements |
| topic | High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2510.07463 |