Analysis of $\sim10^6$ spiral galaxies from four telescopes shows large-scale patterns of asymmetry in galaxy spin directions

TL;DR

This study analyzes nearly one million spiral galaxies from four telescopes to identify large-scale asymmetries in galaxy spin directions, revealing consistent patterns across different datasets and annotation methods.

Contribution

It provides the largest-scale analysis to date of galaxy spin asymmetry patterns using multi-telescope data and both automatic and manual annotations.

Findings

Detected statistically significant asymmetry patterns

Patterns are consistent across different telescopes

Automatic and manual annotations yield similar results

Abstract

The ability to collect unprecedented amounts of astronomical data has enabled the studying scientific questions that were impractical to study in the pre-information era. This study uses large datasets collected by four different robotic telescopes to profile the large-scale distribution of the spin directions of spiral galaxies. These datasets cover the Northern and Southern hemispheres, in addition to data acquired from space by the Hubble Space Telescope. The data were annotated automatically by a fully symmetric algorithm, as well as manually through a long labor-intensive process, leading to a dataset of nearly $10^6$ galaxies. The data shows possible patterns of asymmetric distribution of the spin directions, and the patterns agree between the different telescopes. The profiles also agree when using automatic or manual annotation of the galaxies, showing very similar large-scale patterns. Combining all data from all telescopes allows the most comprehensive analysis of its kind to date in terms of both the number of galaxies and the footprint size. The results show a statistically significant profile that is consistent across all telescopes. The instruments used in this study are DECam, HST, SDSS, and Pan-STARRS. The paper also discusses possible sources of bias, and analyzes the design of previous work that showed different results. Further research will be required to understand and validate these preliminary observations.