The Davis–Chandrasekhar–Fermi method revisited
The Davis–Chandrasekhar–Fermi method revisited
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重新审视戴维斯·钱德拉塞卡·费米方法
DOI：
10.1093/mnras/stac1417
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发表时间：
2022
影响因子：
4.8
通讯作者：
Li, Pak Shing
中科院分区：
文献类型：
--
作者：
Chen, Che-Yu;Li, Zhi-Yun;Mazzei, Renato R;Park, Jinsoo;Fissel, Laura M;Chen, Michael C-Y;Klein, Richard I;Li, Pak Shing
尽管对恒星形成区域的星际磁场有丰富的观测结果，但仍然不清楚这些磁场在不同的物理尺度上有多大的动力学意义，因为直接测量磁场强度在观测上是困难的。Davis-Chandrasekhar-Fermi(DCF)方法是从极化数据估算磁场强度的最常用方法。它基于气体湍流运动是通过线性Alfvén波产生场失真的驱动力的假设。在这项工作中，使用恒星形成云的MHD模拟，我们通过检查DCF方法在真实3D空间中的精度来测试DCF方法所依据的假设的有效性。我们的结果表明，湍流动能和磁能涨落之间的DCF关系应该被视为统计结果，而不是局部性质。然后，我们利用合成观测对原始的DCF方法进行了一些改进，并提出了新的配方来提高DCF导出的磁场强度的精度。我们进一步指出，DCF分析中最大的不确定性可能来自线宽测量，而不是偏振观测，特别是因为视线气体速度可以用来估计DCF方法中的另一个关键参数-气体体积密度。
Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.