Dynamical modelling of dwarf spheroidal galaxies using Gaussian-process emulation
Dynamical modelling of dwarf spheroidal galaxies using Gaussian-process emulation
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DOI：
10.1093/mnras/stz605
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发表时间：
2018-06
影响因子：
4.8
通讯作者：
A. Gration;M. Wilkinson
中科院分区：
文献类型：
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作者：
A. Gration;M. Wilkinson
提出了一种新的有效的方法来拟合矮球状星系（dSph）中恒星运动学数据的动力学模型。我们的方法基于高斯过程仿真（GPE），这是一种复杂的曲线拟合形式，比其他方法需要更少的训练数据。我们使用一组验证测试和诊断标准来评估仿真过程的性能。我们已经实现了一种算法，其中GPE过程及其验证都是完全自动化的。将此方法应用于合成数据，用不到100个模型评估，我们能够恢复dSph的相空间分布函数的玩具模型的三维参数向量的鲁棒置信区域。虽然本文提出的动态模型是低维和静态的，我们强调，该算法适用于任何计划，涉及计算昂贵的模型的评估。因此，它有可能使易于处理的以前棘手的问题，例如，使用高维，时间依赖的N体模拟的个人dSphs的建模。
We present a novel and efficient method for fitting dynamical models of stellar kinematic data in dwarf spheroidal galaxies (dSph). Our approach is based on Gaussian-process emulation (GPE), which is a sophisticated form of curve fitting that requires fewer training data than alternative methods. We use a set of validation tests and diagnostic criteria to assess the performance of the emulation procedure. We have implemented an algorithm in which both the GPE procedure and its validation are fully automated. Applying this method to synthetic data, with fewer than 100 model evaluations we are able to recover a robust confidence region for the three-dimensional parameter vector of a toy model of the phase-space distribution function of a dSph. Although the dynamical model presented in this paper is low-dimensional and static, we emphasize that the algorithm is applicable to any scheme that involves the evaluation of computationally expensive models. It therefore has the potential to render tractable previously intractable problems, for example, the modelling of individual dSphs using high-dimensional, time-dependent N-body simulations.