# Accurate Distances to Important Spiral Galaxies: M63, M74, NGC 1291, NGC 4559, NGC 4625, NGC 5398

## TL;DR

This study uses Hubble Space Telescope data and the tip of the red giant branch method to accurately measure distances to six important spiral galaxies, improving upon previous estimates and highlighting discrepancies among various methods.

## Contribution

The paper presents new, precise distance measurements to six spiral galaxies using a well-calibrated method and Bayesian analysis, reducing uncertainties compared to prior techniques.

## Key findings

- Distances are more accurate with the TRGB method and Bayesian analysis.
- Significant discrepancies exist among different distance measurement techniques.
- Previous methods like Tully-Fisher and PNLF show inconsistent results.

## Abstract

Accurate distances are fundamental to interpreting many measured properties of galaxies. Surprisingly, many of the best-studied spiral galaxies in the Local Volume have distance uncertainties that are much larger than can be achieved with modern observations. Using Hubble Space Telescope optical imaging, we use the tip of the red giant branch method to measure the distances to six galaxies that are included in the Spitzer Infrared Nearby Galaxies Survey (SINGS) program and its offspring surveys. The sample includes M63, M74, NGC 1291, NGC 4559, NGC 4625, and NGC 5398. We compare our results with distances reported to these galaxies based on a variety of methods. Depending on the technique, there can be a wide range in published distances, particularly from the Tully-Fisher relation. In addition, differences between the Planetary Nebula Luminosity Function and Surface Brightness Fluctuation techniques can vary between galaxies suggesting inaccuracies that cannot be explained by systematics in the calibrations. Our distances improve upon previous results as we use a well-calibrated, stable distance indicator, precision photometry in an optimally selected field of view, and a Bayesian Maximum Likelihood technique that reduces measurement uncertainties.