PyNeb: a new tool for analyzing emission lines

I. Code description and validation of results

¹ Instituto de Astrofísica de Canarias, c/ Vía Láctea s/n, 38205 La Laguna, Tenerife Spain
e-mail: vale@iac.es
² Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain
³ Instituto de Astronomía, Universidad Nacional Autónoma de México, Apdo. Postal 70264, 04510 México D.F., Mexico
⁴ National Optical Astronomy Observatory, Tucson, AZ 85719, USA

Received: 29 November 2013
Accepted: 29 September 2014

Abstract

Analysis of emission lines in gaseous nebulae yields direct measures of physical conditions and chemical abundances and is the cornerstone of nebular astrophysics. Although the physical problem is conceptually simple, its practical complexity can be overwhelming since the amount of data to be analyzed steadily increases; furthermore, results depend crucially on the input atomic data, whose determination also improves each year. To address these challenges we created PyNeb, an innovative code for analyzing emission lines. PyNeb computes physical conditions and ionic and elemental abundances and produces both theoretical and observational diagnostic plots. It is designed to be portable, modular, and largely customizable in aspects such as the atomic data used, the format of the observational data to be analyzed, and the graphical output. It gives full access to the intermediate quantities of the calculation, making it possible to write scripts tailored to the specific type of analysis one wants to carry out. In the case of collisionally excited lines, PyNeb works by solving the equilibrium equations for an n-level atom; in the case of recombination lines, it works by interpolation in emissivity tables. The code offers a choice of extinction laws and ionization correction factors, which can be complemented by user-provided recipes. It is entirely written in the python programming language and uses standard python libraries. It is fully vectorized, making it apt for analyzing huge amounts of data. The code is stable and has been benchmarked against IRAF/NEBULAR. It is public, fully documented, and has already been satisfactorily used in a number of published papers.