A Problem with the Clustering of Recent Measures of the Distance to the Large Magellanic Cloud

TL;DR

This paper highlights a problematic over-concentration of recent distance measurements to the Large Magellanic Cloud around a widely accepted value, suggesting potential biases or systematic issues in the field.

Contribution

It identifies and analyzes the abnormal clustering of recent LMC distance measurements, revealing possible biases or systematic errors affecting the field.

Findings

Recent measurements cluster too tightly around the HSTKP value

Statistical tests show the clustering deviates from expected distributions

Potential correlations and biases may influence published distance estimates

Abstract

The distance to the Large Magellanic Cloud (LMC) has long been of key importance for the distance ladder and the distances to all galaxies, and as such many groups have provided measurements of its distance modulus (\mu) with many methods and various means of calibrating each method. Before the year 2001, the many measures spanned a wide range (roughly 18.1 < \mu < 18.8) with the quoted error bars being substantially smaller than the spread, and hence the consensus conclusion being that many of the measures had their uncertainties being dominated by unrecognized systematic problems. In 2001, the Hubble Space Telescope Key Project (HSTKP) on the distance scale made an extensive analysis of earlier results and adopted the reasonable conclusion that the distance modulus is 18.50+-0.10 mag, and the community has generally accepted this widely popularized value. After 2002, 31 independent papers have reported new distance measures to the LMC, and these cluster tightly around \mu=18.50 mag. Indeed, these measures cluster too tightly around the HSTKP value, with 68% of the measures being within 0.5-sigma of 18.50 mag. A Kolmogorov-Smirnov test proves that this concentration deviates from the expected Gaussian distribution at a >3-sigma probability level. This concentration is a symptom of a worrisome problem. Interpretations considered include correlations between papers, widespread over-estimation of error bars, and band-wagon effects. This note is to alert workers in the field that this is a serious problem that should be addressed.