Damn You, Little h! (or, Real-World Applications Of The Hubble Constant Using Observed And Simulated Data)

TL;DR

This paper discusses the challenges and solutions for handling the Hubble constant, 'little h', in galaxy data analysis, emphasizing its minimal uncertainty and proposing best practices for consistent comparisons.

Contribution

It provides a comprehensive overview of how 'little h' affects galaxy measurements and offers guidelines to improve data comparison and model calibration.

Findings

'little h' introduces significant challenges in data comparison.

Proper handling of 'little h' prevents errors in galaxy model calibration.

Authors propose a standardized approach for dealing with 'little h' in research.

Abstract

The Hubble constant, H0, or its dimensionless equivalent, "little h", is a fundamental cosmological property that is now known to an accuracy better than a few percent. Despite its cosmological nature, little h commonly appears in the measured properties of individual galaxies. This can pose unique challenges for users of such data, particularly with survey data. In this paper we show how little h arises in the measurement of galaxies, how to compare like-properties from different datasets that have assumed different little h cosmologies, and how to fairly compare theoretical data with observed data, where little h can manifest in vastly different ways. This last point is particularly important when observations are used to calibrate galaxy formation models, as calibrating with the wrong (or no) little h can lead to disastrous results when the model is later converted to the correct h cosmology. We argue that in this modern age little h is an anachronism, being one of least uncertain parameters in astrophysics, and we propose that observers and theorists instead treat this uncertainty like any other. We conclude with a "cheat sheet" of nine points that should be followed when dealing with little h in data analysis.