A pitfall of piecewise-polytropic equation of state inference
A pitfall of piecewise-polytropic equation of state inference
复制标题
分段多变状态方程推理的一个陷阱
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
A. L. Watts
中科院分区：
文献类型：
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作者：
Geert Raaijmakers;T. E. Riley;A. L. Watts
宇宙中唯一可以用来统计探测冷致密物质的状态方程（EOS）的信使辐射是源自致密恒星近场的辐射。限制旋转致密星的引力质量和赤道半径是当前和未来望远镜任务的主要目标，其主要目的是限制EOS。从贝叶斯的角度来看，有必要仔细讨论先验定义；在这种情况下，一个复杂的问题是，在实践中，局部（内部源物质）和全局（外部时空）参数空间之间的广义相对论映射存在病态。在一篇配套论文中，这些问题是在理论基础上提出的。在本研究中，我们重现了文献中的概率变换过程，以便将 Schwarzschild 引力质量和半径的联合后验分布映射为 EOS 参数的联合后验分布。我们通过计算证明，EOS 参数推断对于在这些质量和半径的联合空间上定义先验的选择敏感，而不是在联合空间内部源物质参数上。我们重点关注分段多变 EOS 模型，该模型目前是天体物理致密物质研究领域的标准。我们讨论这个问题对该领域的影响。
The only messenger radiation in the Universe that one can use to statistically probe the Equation of State (EOS) of cold dense matter is that originating from the near-field vicinities of compact stars. Constraining gravitational masses and equatorial radii of rotating compact stars is a major goal for current and future telescope missions, with a primary purpose of constraining the EOS. From a Bayesian perspective, it is necessary to carefully discuss prior definition; in this context a complicating issue is that in practice there exist pathologies in the general relativistic mapping between spaces of local (interior source matter) and global (exterior space–time) parameters. In a companion paper, these issues were raised on a theoretical basis. In this study we reproduce a probability transformation procedure from the literature in order to map a joint posterior distribution of Schwarzschild gravitational masses and radii into a joint posterior distribution of EOS parameters. We demonstrate computationally that EOS parameter inferences are sensitive to the choice to define a prior on a joint space of these masses and radii, instead of on a joint space interior source matter parameters. We focus on the piecewise-polytropic EOS model, which is currently standard in the field of astrophysical dense matter study. We discuss the implications of this issue for the field.
影响因子：
8.6
作者：
M. Alford;A. Sedrakian
通讯作者：
M. Alford;A. Sedrakian