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arXiv 2007.05229astro-ph.GAastro-ph.SR
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超精细基团比:从氨反转线推导动力学温度的方法

Hyperfine Group Ratio: A Recipe for Deriving Kinetic Temperature from Ammonia Inversion Lines

Shen Wang, Zhiyuan Ren, Di Li, Jens Kauffmann, Qizhou Zhang, Hui Shi

摘要:

虽然氨是一种广泛使用的星际温度计,但其旋转和动力学温度的估计可能会受到混合超精细组分(HFCs)的影响。我们开发了一种新的配方,称为超精细组比(HFGR),它只利用直接观测值,即分组HFC之间的强度比。通过对模型谱的测试,HFGR中的经验公式可以以明确的方式从HFC基团比率导出旋转温度($T_{\rm rot}$)。我们比较了HFGR与其他两个经典的方法,强度比和超精细拟合,基于模拟光谱和实际数据。HFGR有三大改进。首先,HFGR不需要对HFC进行建模或拟合线轮廓,因此对HFC混合的影响更鲁棒。第二,模拟启用的经验公式比在参数空间上拟合光谱快得多,因此可以大大节省计算机时间和人力时间。第三,作为信噪比(SNR)的函数的温度$ΔT_{\rm rot}$的统计不确定性是HFGR配方的自然产物。HFGR的内部误差是$ΔT_{\rm rot}\leq0.5$ K在一个广泛的参数空间的旋转温度(10至60 K),线宽(0.3至4公里/秒),和光学厚度(0至5)。当存在频谱噪声时,当SNR > 4时,HFGR还可以将合理的不确定性水平维持在$ΔT_{\rm rot}\leq 1.0$ K(1 $σ$)。

英文摘要:

Although ammonia is a widely used interstellar thermometer, the estimation of its rotational and kinetic temperatures can be affected by the blended Hyperfine Components (HFCs). We developed a new recipe, referred to as the HyperFine Group Ratio (HFGR), which utilizes only direct observables, namely the intensity ratios between the grouped HFCs. As tested on the model spectra, the empirical formulae in HFGR can derive the rotational temperature ($T_{\rm rot}$) from the HFC group ratios in an unambiguous manner. We compared HFGR with two other classical methods, intensity ratio and hyperfine fitting, based on both simulated spectra and real data. HFGR has three major improvements. First, HFGR does not require modeling the HFC or fitting the line profiles, thus is more robust against the effect of HFC blending. Second, the simulation-enabled empirical formulae are much faster than fitting the spectra over the parameter space, so the computer time and human time can be both largely saved. Third, the statistical uncertainty of the temperature $ΔT_{\rm rot}$ as a function of the signal-to-noise ratio (SNR) is a natural product of the HFGR recipe. The internal error of HFGR is $ΔT_{\rm rot}\leq0.5$ K over a broad parameter space of rotational temperature (10 to 60 K), line width (0.3 to 4 km/s), and optical depth (0 to 5). When there is a spectral noise, HFGR can also maintain a reasonable uncertainty level at $ΔT_{\rm rot}\leq 1.0$ K (1 $σ$) when SNR > 4.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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