论文标题
贝叶斯 - 洛斯维德：用于非参数提取星系线速度分布的贝叶斯框架
BAYES-LOSVD: a bayesian framework for non-parametric extraction of the line-of-sight velocity distribution of galaxies
论文作者
论文摘要
我们介绍了贝叶斯 - 洛斯维德（Bayes-Losvd），这是对星系中视线速度分布（LOSVD）非参数提取的新实现。我们采用贝叶斯推断来获得强大的LOSVD和相关的不确定性。我们的方法依赖于主成分分析来降低提取所需的模板基础的维度，从而提高代码的性能。此外，我们实施了多种选择来正规化输出解决方案。我们在模拟光谱上进行的测试证实了我们的方法对广泛的LOSVD形状建模的能力，克服了最广泛使用的参数方法的局限性（例如Gauss-Hermite扩展）。我们使用Muse和Sauron Integral-Field Field单元（IFU）数据介绍了具有已知奇特LOSVD形状的真实星系LOSVD提取物的示例。我们的实施还可以处理来自其他流行的IFU调查的数据（例如Atlas3d，Califa，漫画，Sami）。代码和相关文档的详细信息可供专用存储库中的社区免费获得。
We introduce BAYES-LOSVD, a novel implementation of the non-parametric extraction of line-of-sight velocity distributions (LOSVDs) in galaxies. We employ bayesian inference to obtain robust LOSVDs and associated uncertainties. Our method relies on principal component analysis to reduce the dimensionality of the base of templates required for the extraction and thus increase the performance of the code. In addition, we implement several options to regularise the output solutions. Our tests, conducted on mock spectra, confirm the ability of our approach to model a wide range of LOSVD shapes, overcoming limitations of the most widely used parametric methods (e.g. Gauss-Hermite expansion). We present examples of LOSVD extractions for real galaxies with known peculiar LOSVD shapes, i.e. NGC4371, IC0719 and NGC4550, using MUSE and SAURON integral-field unit (IFU) data. Our implementation can also handle data from other popular IFU surveys (e.g. ATLAS3D, CALIFA, MaNGA, SAMI). Details of the code and relevant documentation are freely available to the community in the dedicated repositories.
