Self-consistent Color-Mass-to-Light-Ratio relations for Low Surface Brightness Galaxies

TL;DR

This paper re-calibrates color-mass-to-light ratio relations for low surface brightness galaxies across multiple bands, achieving consistent stellar mass estimates and reducing discrepancies among different models, especially in near-infrared bands.

Contribution

It provides self-consistent re-calibrated CMLRs for LSBGs across various photometric bands, extending previous work to SDSS filters and improving mass estimation accuracy.

Findings

Re-calibrated CMLRs reduce mass prediction discrepancies.

Self-consistent M* estimates across multiple bands.

Near-infrared luminosities are more reliable for M*/L predictions.

Abstract

The color - stellar mass-to-light ratio relation (CMLR) is a widely accepted tool to estimate the stellar mass (M*) of a galaxy. However, an individual CMLR tends to give distinct M* for a same galaxy when it is applied in different bands. Examining five representative CMLRs from literature, we find that the difference in M* predicted in different bands from optical to near-infrared by a CMLR is 0.1-0.3 dex. Therefore, based on a sample of low surface brightness galaxies (LSBG) that covers a wide range of color and luminosity, we re-calibrated each original CMLR in r, i, z, J, H, and K bands to give internally self-consistent M* for a same galaxy. The g-r is the primary color indicator in the re-calibrated relations which show little dependenceon red (r - z) or near-infrared (J - K) colors.Additionally, the external discrepancies in the originally predicted stellar mass-to-light ratio (M*/L) by the five independent CMLRs have been greatly reduced after re-calibration, especially in near-infrared bands, implying that the near-infrared luminosities are more robust to predict M*/L. For each CMLR, the re-calibrated relations provided in this work could produce internally self-consistent M* from divergent photometric bands, and are extensions of the re-calibrations from Johnson-Cousin filter system by the pioneering work of McGaugh & Schombert (2014) to SDSS filter system.