论文标题
模糊集群分析：应用非常金属贫困星的金属性
Fuzzy Cluster Analysis: Application to Determining Metallicities for Very Metal-poor Stars
论文作者
论文摘要
这项工作首次尝试将模糊群集分析（FCA）用于分析恒星光谱。 FCA被采用以分类从LAMOST低分辨率光谱测量的线指数，并自动删除对金属性最低敏感的指数。然后将FCA处理的指数转移到人工神经网络（ANN）中，以获得147个非常金属贫困（VMP）恒星的金属性，这些金属已通过高分辨率光谱进行了分析。与高分辨率分析相比，FCA-ANN方法可以得出VMP恒星的鲁棒金属度，精度为0.2 DEX。建议的FCA阈值值λ为此测试在0.9965至0.9975之间。在通过FCA降低线指数的尺寸后，派生的金属度仍然很强，没有准确性损失，并且FCA -ANN方法的性能稳定，从[Fe/H]下降到-1.8，从-1.8降至-3.5。与传统的分类方法相比，FCA考虑了分组的歧义和数据的非连续性，因此更适合观察数据分析。尽管该早期测试使用FCA来分析低分辨率光谱，并将输入ANN方法推导金属性的输入，但FCA应该能够在大数据时代分析无slitss slitseprosproscopicy和多型光度法，并准备不限于ANN的方法的输入，以供其他研究中的ANN进行其他研究，例如其他研究，例如其他PECEFIFIAT，例如，例如Pec。文献收集的高分辨率样品可以帮助改善管道以获得恒星金属性，并讨论了三个已发表的Lamost目录的VMP恒星的金属恒星的系统偏移。
This work presents a first attempt to apply fuzzy cluster analysis (FCA) to analyzing stellar spectra. FCA is adopted to categorize line indices measured from LAMOST low-resolution spectra, and automatically remove the least metallicity-sensitive indices. The FCA-processed indices are then transferred to the artificial neural network (ANN) to derive metallicities for 147 very metal-poor (VMP) stars that have been analyzed by high-resolution spectroscopy. The FCA-ANN method could derive robust metallicities for VMP stars, with a precision of 0.2 dex compared with high-resolution analysis. The recommended FCA threshold value λfor this test is between 0.9965 and 0.9975. After reducing the dimension of the line indices through FCA, the derived metallicities are still robust, with no loss of accuracy, and the FCA-ANN method performs stably for different spectral quality from [Fe/H] from -1.8 down to -3.5. Compared with traditional classification methods, FCA considers ambiguity in groupings and noncontinuity of data, and is thus more suitable for observational data analysis. Though this early test uses FCA to analyze low-resolution spectra, and feeds the input to the ANN method to derive metallicities, FCA should be able to, in the large data era, also analyze slitless spectroscopy and multiband photometry, and prepare the input for methods not limited to ANN, in the field of stellar physics for other studies, e.g., stellar classification, identification of peculiar objects. The literature-collected high-resolution sample can help improve pipelines to derive stellar metallicities, and systematic offsets in metallicities for VMP stars for three published LAMOST catalogs have been discussed.
