arxiv
PublishedOctober 16, 2026 at 4:00 AM
Machine-learning-based neutrino-event generation constrained by experimental measurements
Publisher summary· verbatim
arXiv:2610.20870v1 Announce Type: cross Abstract: We present a generative surrogate for charged-current \(\nu_\mu\)-nucleus scattering that can be calibrated to measured differential cross sections without event-level experimental samples. Starting from a theoretical interaction model, we fine-tune
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response7harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making7harxivRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents7harxivIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD7hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗