Identifying tools for comparing simulations and observations of spectral-line data cubes
Identifying tools for comparing simulations and observations of spectral-line data cubes
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DOI：
10.1093/mnras/stx1671
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发表时间：
2017-07
影响因子：
4.8
通讯作者：
E. Koch;Caleb G. Ward;S. Offner;Jason L. Loeppky;E. Rosolowsky
中科院分区：
文献类型：
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作者：
E. Koch;Caleb G. Ward;S. Offner;Jason L. Loeppky;E. Rosolowsky
我们提出了一个统计框架来比较分子云的谱线数据立方体，并使用该框架来执行从文献中提出的方法开发的各种统计工具的分析。我们测试我们的方法是否对云的基本物理特性的变化敏感，或者它们的行为是否受随机波动的影响。我们进行了一组32个自引力磁流体动力学模拟，测试五个物理参数的所有组合-马赫数，等离子体参数，维里参数，驱动尺度和螺线管驱动分数-其中每一个都可以设置为一个低或高的值。我们从每个模拟中创建了${\rm ^{13}CO}$（1-0）排放的模拟观测数据集。我们将这些模拟数据与使用伪距离度量的一组基线模拟生成的数据进行比较，这些伪距离度量基于先前用于研究分子云的18种不同统计技术。我们使用实验设计统计领域的方法分析了这些结果，发现一些统计数据可以可靠地跟踪基础物理的变化。我们的分析表明，参数之间的相互作用往往是最显着的影响。一小部分统计数据对磁场特性的变化也很敏感。我们使用这个框架来比较一组模拟附近的三个恒星形成区域的观测：NGC 1333，Oph A和IC 348。我们发现，没有一个模拟同意显着更好的观察，虽然有证据表明，高马赫数的模拟与观察更一致。
We present a statistical framework to compare spectral-line data cubes of molecular clouds and use the framework to perform an analysis of various statistical tools developed from methods proposed in the literature. We test whether our methods are sensitive to changes in the underlying physical properties of the clouds or whether their behaviour is governed by random fluctuations. We perform a set of 32 self-gravitating magnetohydrodynamic simulations that test all combinations of five physical parameters -- Mach number, plasma parameter, virial parameter, driving scales, and solenoidal driving fraction -- each of which can be set to a low or high value. We create mock observational data sets of ${\rm ^{13}CO}$(1-0) emission from each simulation. We compare these mock data to a those generated from a set of baseline simulations using pseudo-distance metrics based on 18 different statistical techniques that have previously been used to study molecular clouds. We analyze these results using methods from the statistical field of experimental design and find that several of the statistics can reliably track changes in the underlying physics. Our analysis shows that the interactions between parameters are often among the most significant effects. A small fraction of statistics are also sensitive to changes in magnetic field properties. We use this framework to compare the set of simulations to observations of three nearby star-forming regions: NGC 1333, Oph A, and IC 348. We find that no one simulation agrees significantly better with the observations, although there is evidence that the high Mach number simulations are more consistent with the observations.