论文标题
智能传感器使用人工智能进行探测器电子和ASIC
Smart sensors using artificial intelligence for on-detector electronics and ASICs
论文作者
论文摘要
尖端探测器通过进一步改善空间和时间分辨率，增加检测器面积和体积以及通常减少背景和噪声来推动传感技术。这导致了下一代实验中越来越多的数据爆炸。因此，在数据源上需要近传感器，使用更强大的算法处理对于更有效地捕获正确的实验数据，降低下游系统的复杂性并启用更快，更低的功能反馈回路变得越来越重要。在本文中，我们讨论了探索器AI的动机和潜在应用。此外，粒子物理的独特要求可以唯一推动新型AI硬件和设计工具的开发。我们描述了该领域粒子物理的现有现代作品。最后，我们概述了许多机会领域，可以推进机器学习技术，代码工作流以及未来的微电子技术，这些技术将加速下一代实验的设计，性能和实现。
Cutting edge detectors push sensing technology by further improving spatial and temporal resolution, increasing detector area and volume, and generally reducing backgrounds and noise. This has led to a explosion of more and more data being generated in next-generation experiments. Therefore, the need for near-sensor, at the data source, processing with more powerful algorithms is becoming increasingly important to more efficiently capture the right experimental data, reduce downstream system complexity, and enable faster and lower-power feedback loops. In this paper, we discuss the motivations and potential applications for on-detector AI. Furthermore, the unique requirements of particle physics can uniquely drive the development of novel AI hardware and design tools. We describe existing modern work for particle physics in this area. Finally, we outline a number of areas of opportunity where we can advance machine learning techniques, codesign workflows, and future microelectronics technologies which will accelerate design, performance, and implementations for next generation experiments.
