Hyperfine Group Ratio (HFGR): A Recipe for Deriving Kinetic Temperature from Ammonia Inversion Lines. (arXiv:2007.05229v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Wang_S/0/1/0/all/0/1">Shen Wang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ren_Z/0/1/0/all/0/1">Zhiyuan Ren</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Li_D/0/1/0/all/0/1">Di Li</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Kauffmann_J/0/1/0/all/0/1">Jens Kauffmann</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Zhang_Q/0/1/0/all/0/1">Qizhou Zhang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Shi_H/0/1/0/all/0/1">Hui Shi</a>
Ammonia is a classic interstellar thermometer. The estimation of the
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 to
the two conventional methods, hyperfine fitting and line intensity ratio, based
on both real data and simulated spectra. The 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 $Delta
T_{rm rot}$ as a function of the signal-to-noise ratio (SNR) are also
provided. HFGR can keep an internal error of $Delta T_{rm rot}leq0.5$ K over
a broad parameter space of temperature (10 to 70 K), line width (0.3 to 4
kms), and optical depth (0 to 5). When applied to the noisy spectra, HFGR can
keep an uncertainty of $Delta T_{rm rot}leq 1.0$ K (1 $sigma$) when
SNR$>4$.
Ammonia is a classic interstellar thermometer. The estimation of the
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 to
the two conventional methods, hyperfine fitting and line intensity ratio, based
on both real data and simulated spectra. The 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 $Delta
T_{rm rot}$ as a function of the signal-to-noise ratio (SNR) are also
provided. HFGR can keep an internal error of $Delta T_{rm rot}leq0.5$ K over
a broad parameter space of temperature (10 to 70 K), line width (0.3 to 4
kms), and optical depth (0 to 5). When applied to the noisy spectra, HFGR can
keep an uncertainty of $Delta T_{rm rot}leq 1.0$ K (1 $sigma$) when
SNR$>4$.
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