Comment on “A new implementation of the Humlicek algorithm for the calculation of the Voigt profile function” by M. Kuntz [JQSRT 57(6) (1997) 819–824]

Ruyten, Wim

doi:10.1016/j.jqsrt.2003.12.027

Cited by 34 publications

(12 citation statements)

References 3 publications

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“…One of the most widely used algorithms for efficient and moderately accurate computation is by Humlíček [22] providing four significant digits (further variants and optimizations by, e.g., Kuntz [31], Ruyten [32], Imai et al [33].) Because this w4 code uses four different rational approximations for small and/or large x and y, it can be difficult to implement efficiently in, e.g., Numeric Python.…”

Section: Discussionmentioning

confidence: 99%

Comments on the Voigt function implementation in the Astropy and SpectraPlot.com packages

Schreier

2018

Journal of Quantitative Spectroscopy and Radiative Transfer

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The Voigt profile is important for spectroscopy, astrophysics, and many other fields of physics, but is notoriously difficult to compute. McLean et al. [J. Electron Spectrosc. & Relat. Phenom., 1994] have proposed an approximation using a sum of Lorentzians. Our assessment indicates that this algorithm has significant errors for small arguments. After a brief survey of the requirements for spectroscopy we give a short list of both efficient and accurate codes and recommend implementations based on rational approximations.

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Section: Discussionmentioning

confidence: 99%

Comments on the Voigt function implementation in the Astropy and SpectraPlot.com packages

Schreier

2018

Journal of Quantitative Spectroscopy and Radiative Transfer

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“…To verify the accuracy of our approach, we compared cross sections calculated using the techniques described above with the results obtained using the existing opacity calculators. One is the cross section made for the study of exoplanet spectra (Kawashima & Ikoma 2018), which uses a polynomial expansion of the Voigt profile by Kuntz (1997) (see also Ruyten 2004). The other is a fast GPU-based opacity calculator, HELIOS-K 2.0 (Grimm et al 2021).…”

Section: Comparison With Other Opacity Calculatorsmentioning

confidence: 99%

Auto-Differentiable Spectrum Model for High-Dispersion Characterization of Exoplanets and Brown Dwarfs

Kawahara,

Kawashima,

Masuda

et al. 2021

Preprint

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We present an auto-differentiable spectral modeling of exoplanets and brown dwarfs. This model enables a fully Bayesian inference of the high-dispersion data to fit the ab initio line-by-line spectral computation to the observed spectrum by combining it with the Hamiltonian Monte Carlo in recent probabilistic programming languages. An open source code, exojax , developed in this study, was written in Python using the GPU/TPU compatible package for automatic differentiation and accelerated linear algebra, JAX (Bradbury et al. 2018). We validated the model by comparing it with existing opacity calculators and a radiative transfer code and found reasonable agreements of the output. As a demonstration, we analyzed the high-dispersion spectrum of a nearby brown dwarf, Luhman 16 A and found that a model including water, carbon monoxide, and H 2 /He collision induced absorption was well fitted to the observed spectrum (R = 10 5 and 2.28-2.30 µm). As a result, we found that T 0 = 1295 ± 14 K at 1 bar and C/O = 0.62 ± 0.01, which is slightly higher than the solar value. This work demonstrates the potential of full Bayesian analysis of brown dwarfs and exoplanets as observed by high-dispersion spectrographs and also directly-imaged exoplanets as observed by high-dispersion coronagraphy.

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“…the review of Armstrong (1967) or the comparisons by Twitty et al (1980), Klim (1981), Schreier (1992), and Thompson (1993)]. Further optimizations of the Hui et al and Humliček algorithms have been presented by Schreier (1992), Shippony andRead (1993, 2003), Kuntz (1997), Ruyten (2004), Wells (1999), and Schreier and Kohlert (2008). Further optimizations of the Hui et al and Humliček algorithms have been presented by Schreier (1992), Shippony andRead (1993, 2003), Kuntz (1997), Ruyten (2004), Wells (1999), and Schreier and Kohlert (2008).…”

Section: Numericsmentioning

confidence: 99%

Comments on “A Common Misunderstanding about the Voigt Line Profile”

Schreier

2009

Journal of the Atmospheric Sciences

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In a recent paper, it was argued that some of the illustrations in popular textbooks comparing the Lorentz and Gaussian profiles with the ''corresponding'' Voigt profile are incorrect. These ''misunderstandings'' are shown to be a result of ambiguous specifications of the Voigt profile (i.e., there is no unique corresponding Voigt profile). Additionally, some comments on half-widths, numerics, and visualization are given.

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Comment on “A new implementation of the Humlicek algorithm for the calculation of the Voigt profile function” by M. Kuntz [JQSRT 57(6) (1997) 819–824]

Cited by 34 publications

References 3 publications

Comments on the Voigt function implementation in the Astropy and SpectraPlot.com packages

Comments on the Voigt function implementation in the Astropy and SpectraPlot.com packages

Auto-Differentiable Spectrum Model for High-Dispersion Characterization of Exoplanets and Brown Dwarfs

Comments on “A Common Misunderstanding about the Voigt Line Profile”

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