English(EN) Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training

自监督ViT框架增强中微子探测器分析

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-13 04:00

研究人员开发了一种新的自监督预训练框架，使用稀疏Vision Transformer（ViT）为异构中微子探测器创建可重用表示。该方法在大型强子对撞机上FASERCal概念的模拟数据上进行了评估，与从头开始训练相比，显著提高了中微子味识别和动量回归等任务的性能。该方法展示了强大的数据效率，在标记数据量大大减少的情况下取得了可比的性能，并显示出对其他探测器技术和能量尺度的有效迁移能力。 AI

影响这种方法可以通过实现对复杂实验数据的更有效分析来加速科学发现。

排序理由详细介绍科学数据分析新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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arXiv cs.CV TIER_1 English(EN) · Sa\'ul Alonso-Monsalve, Fabio Cufino, Umut Kose, Anna Mascellani, Andr\'e Rubbia · 2026-08-13 04:00

通过自监督预训练，迈向能源前沿异构中微子探测器的基础模型

arXiv:2604.07037v2 Announce Type: replace-cross Abstract: Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally dense, overlapping detector signatures. In this regime, event interpretation beco…

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通过自监督预训练，迈向能源前沿异构中微子探测器的基础模型

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