Oxygen abundance methods in the SDSS: view from modern statistics

TL;DR

This study evaluates various oxygen abundance determination methods in SDSS galaxy data using modern statistical techniques, finding the $T_e$ method to be the most reliable among them.

Contribution

It applies Bayesian analysis and information scoring to compare oxygen abundance methods, providing a rigorous statistical validation of their reliability.

Findings

The $T_e$ method is more reliable than Bayesian methods.

$P$ and $O3N2$ methods are consistent with $T_e$.

$N2$ method is unreliable.

Abstract

Our purpose is to find which is the most reliable one among various oxygen abundance determination methods. We will test the validity of several different oxygen abundance determination methods using methods of modern statistics. These methods include Bayesian analysis and information scoring. We will analyze a sample of $\sim$6000 $\hii$ galaxies from the Sloan Digital Sky Survey (SDSS) spectroscopic observations data release four. All methods that we used drew the same conclusion that the $T_e$ method is a more reliable oxygen abundance determination methods than the Bayesian metallcity method under the existing telescope ability. The ratios of the likelihoods between the different kinds of methods tell us that the $T_e$, $P$, and $O3N2$ methods are consistent with each other because the $P$ and $O3N2$ method are calibrated by $T_e$-method. The Bayesian and $R_{23}$ method are consistent with each other because both are calibrated by a galaxy model. In either case, the $N2$ method is an {\it unreliable} method.