以光为动力的端到端中子检测和成像,采用边部署的光学AI芯片
Shanny Lin1,2, Hanqing Zhu2, Steven Clayton1
1Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Scientific reports
|November 27, 2025
概括
我们使用光学神经网络 (ONN) 开发了一种自动化的中子检测工作流程,以提高辐射硬度. 该系统实现了超过96%的精度和中子成像应用的子像素分辨率.
科学领域:
- 核物理与工程 核物理与工程
- 先进的传感器技术技术的传感器技术.
- 科学仪器仪表中的人工智能
背景情况:
- 中子探测在核物理,能源,技术和保障方面至关重要.
- 目前的检测方法可能受到辐射损伤和处理速度的限制.
- 需要自动化工作流程来实现高效可靠的中子探测和成像.
研究的目的:
- 实现自动化,端到端的中子检测和成像工作流.
- 为了提高中子探测仪器的辐射硬度和运行寿命.
- 使用基于边缘的光学神经网络,实现高精度的中子检测,具有子像素分辨率.
主要方法:
- 使用固态图像传感器开发了用于中子检测的自动化工作流.
- 在基于边缘的光学神经网络 (ONN) 上部署工作流.
- 实施了两阶段的神经网络框架:一个区域提案网络,然后是一个完全连接的网络,用于分像素定位.
主要成果:
- 实现了超过96%的中子检测准确度.
- 获得了中子碰撞的子像素和子微米位置分辨率.
- 展示了ONN硬件的优点:辐射硬度,低功耗和高计算速度.
结论:
- 开发的自动化工作流程和双阶段神经网络框架使得有效和准确的中子检测成为可能.
- 基于边缘的ONN部署显著改善了仪器的辐射硬度和寿命.
- 这种方法为集成中子探测系统的电子对应提供了一个有希望的替代方案.
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