GReFC-Net:测量螺旋星系结构特征的自动方法

IF 2.7 3区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS
Gengqi Lin, Liangping Tu, Jianxi Li, Jiawei Miao
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引用次数: 0

摘要

螺旋结构是星系内的一种重要形态,它提供了有关螺旋星系形成、演化和环境的信息。旋臂数是描述旋涡星系形态的重要参数之一。在本项目中,我们研究基于深度学习算法的旋臂数量对螺旋星系进行分类。本项目的数据集包括来自 Galaxy Zoo 2 和 Galaxy Zoo DECaLS 的合格样本。为了更好地识别旋臂的纹理特征,我们设计了一个包含 Gabor 滤波器的卷积神经网络模型(Gabor Residual Filtering Convolutional Net,GReFC-Net),并使用其他网络进行 3 向和 4 向分类。在 3 向分类中,GReFC-Net 算法的精确度、召回率、F1 分数和 AUC 值最高,分别为 96.25%、96.23%、96.21% 和 0.9937。在 4 路情况下,GReFC-Net 算法的召回率、F1-分数和 AUC 值最高,分别为 95.57%、95.42% 和 0.9957。利用 SHAP 方法分析了 GReFC-Net 的可解释性,结果表明该网络能很好地识别旋涡星系的旋臂结构。可见,GReFC-Net 算法可以有效地应用于大量旋涡星系旋臂结构的自动测量任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GReFC-Net: an automated method for measuring structural features of spiral galaxies

GReFC-Net: an automated method for measuring structural features of spiral galaxies

The spiral structure is an important morphology within galaxies, providing information on the formation, evolution, and environment of spiral galaxies. The number of spiral arms is one of the important parameters to describe the morphology of spiral galaxies. In this project, we study the classification of spiral galaxies by the number of spiral arms based on deep learning algorithms. The data set for this project consists of eligible samples from Galaxy Zoo 2 and Galaxy Zoo DECaLS. To better identify the texture features of the spiral arms, we designed a convolutional neural network model incorporating Gabor filter (Gabor Residual Filtering Convolutional Net, GReFC-Net), and used other networks for 3 and 4-way classifications. In the 3-way case, the GReFC-Net algorithm achieves the highest precision, recall, F1-score, and AUC value, which are 96.25%, 96.23%, 96.21%, and 0.9937. In the 4-way case, the GReFC-Net algorithm has the highest recall, F1-score and AUC value, which are 95.57%, 95.42% and 0.9957. The interpretability of GReFC-Net is analyzed by the SHAP method, and the results show that the network can identify the spiral arm structure of spiral galaxies well. It can be seen that the GReFC-Net algorithm can be effectively applied to the automatic measurement task of spiral arm structure in a large number of spiral galaxies.

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来源期刊
Experimental Astronomy
Experimental Astronomy 地学天文-天文与天体物理
CiteScore
5.30
自引率
3.30%
发文量
57
审稿时长
6-12 weeks
期刊介绍: Many new instruments for observing astronomical objects at a variety of wavelengths have been and are continually being developed. Furthermore, a vast amount of effort is being put into the development of new techniques for data analysis in order to cope with great streams of data collected by these instruments. Experimental Astronomy acts as a medium for the publication of papers of contemporary scientific interest on astrophysical instrumentation and methods necessary for the conduct of astronomy at all wavelength fields. Experimental Astronomy publishes full-length articles, research letters and reviews on developments in detection techniques, instruments, and data analysis and image processing techniques. Occasional special issues are published, giving an in-depth presentation of the instrumentation and/or analysis connected with specific projects, such as satellite experiments or ground-based telescopes, or of specialized techniques.
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