论文标题
超细群比率：从氨反转线得出动力学温度的食谱
Hyperfine Group Ratio: A Recipe for Deriving Kinetic Temperature from Ammonia Inversion Lines
论文作者
论文摘要
尽管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高精细分量（HFC）的影响。我们开发了一种新的食谱，称为Hyperfine组比率（HFGR），该配方仅利用直接观察物，即组分组的HFC之间的强度比。如在模型光谱上测试的，HFGR中的经验公式可以以明确的方式从HFC组比例得出旋转温度（$ t _ {\ rm rot} $）。我们基于模拟光谱和真实数据将HFGR与另外两种经典方法，强度比和超精细拟合进行了比较。 HFGR有三个重大改进。首先，HFGR不需要对HFC进行建模或拟合线轮廓，因此在HFC混合的效果方面更强大。其次，启用了仿真的经验公式要比拟合光谱符合参数空间要快得多，因此计算机时间和人类时间都可以在很大程度上保存。第三，温度$ΔT_ {\ rm rot} $的统计不确定性作为信噪比（SNR）的函数是HFGR配方的天然产物。 HFGR的内部误差为$δT_ {\ rm rot} \ leq0.5 $ k在旋转温度的广泛参数（10至60 K），线宽度（0.3至4 km/s）和光学深度（0至5）上（0至5）。当存在频谱噪声时，HFGR还可以将合理的不确定性水平保持在$ΔT_ {\ rm rot} \ leq 1.0 $ k（1 $σ$）时，当SNR> 4时。
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.
