论文标题
具有电阻读取的硅传感器：最终空间分辨率的机器学习技术
Silicon sensors with resistive read-out: Machine Learning techniques for ultimate spatial resolution
论文作者
论文摘要
电阻性交流耦合硅探测器（RSD）基于低增益雪崩二极管（LGAD）技术，其特征在于连续增益层，并且是通过创新的电阻读数引入的。得益于旨在最大化信号共享的新型电极设计，RSD2是Fondazione Bruno Kessler（FBK）的第二个RSD生产，因此在整个像素表面上达到了位置分辨率，约8 $ $ $ $ $ $ $ $ $ $ $ $μm$。 RSD2阵列已使用配备了16通道数字化器的瞬态电流技术进行了测试，并通过机器学习算法获得了空间分辨率的结果。
Resistive AC-coupled Silicon Detectors (RSDs) are based on the Low Gain Avalanche Diode (LGAD) technology, characterized by a continuous gain layer, and by the innovative introduction of resistive read-out. Thanks to a novel electrode design aimed at maximizing signal sharing, RSD2, the second RSD production by Fondazione Bruno Kessler (FBK), achieves a position resolution on the whole pixel surface of about 8 $μm$ for 200-$μm$ pitch. RSD2 arrays have been tested using a Transient Current Technique setup equipped with a 16-channel digitizer, and results on spatial resolution have been obtained with machine learning algorithms.
