An Algorithm to Compress Line-transition Data for Radiative-transfer Calculations

• Published in: The Astrophysical journal Vol. 850; no. 1; pp. 32 - 35
• Main Author: Cubillos, Patricio E.
• Format: Journal Article
• Language: English
• Published: Philadelphia The American Astronomical Society 20.11.2017; IOP Publishing
• Subjects: Algorithms; Astrophysics; atomic data; Mathematical analysis; methods: numerical; Population density; radiative transfer; Temperature dependence
• ISSN: 0004-637X; 1538-4357
• DOI: 10.3847/1538-4357/aa9228

Molecular line-transition lists are an essential ingredient for radiative-transfer calculations. With recent databases now surpassing the billion-line mark, handling them has become computationally prohibitive, due to both the required processing power and memory. Here I present a temperature-dependent algorithm to separate strong from weak line transitions, reformatting the large majority of the weaker lines into a cross-section data file, and retaining the detailed line-by-line information of the fewer strong lines. For any given molecule over the 0.3-30 m range, this algorithm reduces the number of lines to a few million, enabling faster radiative-transfer computations without a significant loss of information. The final compression rate depends on how densely populated the spectrum is. I validate this algorithm by comparing Exomol's HCN extinction-coefficient spectra between the complete (65 million line transitions) and compressed (7.7 million) line lists. Over the 0.6-33 m range, the average difference between extinction-coefficient values is less than 1%. A Python/C implementation of this algorithm is open-source and available at https://github.com/pcubillos/repack. So far, this code handles the Exomol and HITRAN line-transition format.