Research on the X-ray polarization deconstruction method based on hexagonal convolutional neural network  

作　　者：Ya-Nan Li Jia-Huan Zhu Huai-Zhong Gao Hong Li Ji-Rong Cang Zhi Zeng Hua Feng Ming Zeng 

机构地区：[1]Key Laboratory of Particle&Radiation Imaging,Tsinghua University,Ministry of Education,Beijing 100084,China [2]Department of Engineering Physics,Tsinghua University,Beijing 100084,China [3]Department of Astronomy,Tsinghua University,Beijing 100084,China [4]StarDetect Co.,Ltd,Beijing 100084,China

出　　处：《Nuclear Science and Techniques》2025年第2期49-61,共13页核技术(英文)

基　　金：supported by the National Natural Science Foundation of China(No.12025301);the Tsinghua University Initiative Scientific Research Program.

摘　　要：Track reconstruction algorithms are critical for polarization measurements.Convolutional neural networks(CNNs)are a promising alternative to traditional moment-based track reconstruction approaches.However,the hexagonal grid track images obtained using gas pixel detectors(GPDs)for better anisotropy do not match the classical rectangle-based CNN,and converting the track images from hexagonal to square results in a loss of information.We developed a new hexagonal CNN algorithm for track reconstruction and polarization estimation in X-ray polarimeters,which was used to extract the emission angles and absorption points from photoelectron track images and predict the uncer-tainty of the predicted emission angles.The simulated data from the PolarLight test were used to train and test the hexagonal CNN models.For individual energies,the hexagonal CNN algorithm produced 15%-30%improvements in the modulation factor compared to the moment analysis method for 100%polarized data,and its performance was comparable to that of the rectangle-based CNN algorithm that was recently developed by the Imaging X-ray Polarimetry Explorer team,but at a lower computational and storage cost for preprocessing.

关 键 词：X-ray polarization Track reconstruction Deep learning Hexagonal conventional neural network 

分 类 号：O436.3[机械工程—光学工程] TP183[理学—光学] TP391.41[理学—物理]