The Tully-Fisher Relation for 25,000 SDSS Galaxies as Function of Environment

TL;DR

This study constructs Tully-Fisher relations for over 25,000 SDSS galaxies across multiple bands, demonstrating that fiber measurements can reliably estimate galaxy velocities and that environment has minimal impact on the relation.

Contribution

The paper develops a methodology to accurately construct Tully-Fisher relations from SDSS data and assesses environmental effects on these relations with a large galaxy sample.

Findings

TFRs are consistent across different environments.

Fiber aperture effects can be modeled to recover true galaxy velocities.

No significant environmental dependence on TFRs was found.

Abstract

We construct Tully-Fisher relationships (TFRs) in the $u$, $g$, $r$, $i$ and $z$ bands and stellar mass TFRs (smTFRs) for a sample of $25,698$ late spiral type galaxies (with $0.045<z<0.085$) from the Sloan Digital Sky Survey (SDSS) and study the effects of environment on the relation. We use SDSS-measured Balmer emission line widths, $v_{\rm FWHM}$, as a proxy for disc circular velocity, $v_{\rm circ}$. A priori it is not clear whether we can construct accurate TFRs given the small $3"$ diameter of the fibres used for SDSS spectroscopic measurements. However, we show by modelling the H$\alpha$ emission profile as observed through a $3"$ aperture that for galaxies at appropriate redshifts ($z>0.045$) the fibres sample enough of the disc to obtain a linear relationship between $v_{\rm FWHM}$ and $v_{\rm circ}$, allowing us to obtain a TFR and to investigate dependence on other variables. We also develop a methodology for distinguishing between astrophysical and sample bias in the fibre TFR trends. We observe the well-known steepening of the TFR in redder bands in our sample. We divide the sample of galaxies into four equal groups using projected neighbour density ($\Sigma$) quartiles and find no significant dependence on environment, extending previous work to a wider range of environments and a much larger sample. Having demonstrated that we can construct SDSS-based TFRs is very useful for future applications because of the large sample size available.