Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies

Observations of non-random distribution of galaxies with opposite spin directions have recently attracted considerable attention. Here, a method for identifying cosine-dependence in a dataset of galaxies annotated by their spin directions is described in the light of different aspects that can impac...

Full description

Bibliographic Details
Main Author: Lior Shamir
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Particles
Subjects:
Online Access:https://www.mdpi.com/2571-712X/4/1/2
id doaj-0197f69c4d5b42e9898d13bb41130c06
record_format Article
spelling doaj-0197f69c4d5b42e9898d13bb41130c062021-01-06T00:00:10ZengMDPI AGParticles2571-712X2021-01-0142112810.3390/particles4010002Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral GalaxiesLior Shamir0Kansas State University, Manhattan, KS 66506, USAObservations of non-random distribution of galaxies with opposite spin directions have recently attracted considerable attention. Here, a method for identifying cosine-dependence in a dataset of galaxies annotated by their spin directions is described in the light of different aspects that can impact the statistical analysis of the data. These aspects include the presence of duplicate objects in a dataset, errors in the galaxy annotation process, and non-random distribution of the asymmetry that does not necessarily form a dipole or quadrupole axes. The results show that duplicate objects in the dataset can artificially increase the likelihood of cosine dependence detected in the data, but a very high number of duplicate objects is required to lead to a false detection of an axis. Inaccuracy in galaxy annotations has relatively minor impact on the identification of cosine dependence when the error is randomly distributed between clockwise and counterclockwise galaxies. However, when the error is not random, even a small bias of 1% leads to a statistically significant cosine dependence that peaks at the celestial pole. Experiments with artificial datasets in which the distribution was not random showed strong cosine dependence even when the data did not form a full dipole axis alignment. The analysis when using the unmodified data shows asymmetry profile similar to the profile shown in multiple previous studies using several different telescopes.https://www.mdpi.com/2571-712X/4/1/2cosmologygalaxieslarge-scale structure
collection DOAJ
language English
format Article
sources DOAJ
author Lior Shamir
spellingShingle Lior Shamir
Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
Particles
cosmology
galaxies
large-scale structure
author_facet Lior Shamir
author_sort Lior Shamir
title Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
title_short Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
title_full Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
title_fullStr Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
title_full_unstemmed Analysis of the Alignment of Non-Random Patterns of Spin Directions in Populations of Spiral Galaxies
title_sort analysis of the alignment of non-random patterns of spin directions in populations of spiral galaxies
publisher MDPI AG
series Particles
issn 2571-712X
publishDate 2021-01-01
description Observations of non-random distribution of galaxies with opposite spin directions have recently attracted considerable attention. Here, a method for identifying cosine-dependence in a dataset of galaxies annotated by their spin directions is described in the light of different aspects that can impact the statistical analysis of the data. These aspects include the presence of duplicate objects in a dataset, errors in the galaxy annotation process, and non-random distribution of the asymmetry that does not necessarily form a dipole or quadrupole axes. The results show that duplicate objects in the dataset can artificially increase the likelihood of cosine dependence detected in the data, but a very high number of duplicate objects is required to lead to a false detection of an axis. Inaccuracy in galaxy annotations has relatively minor impact on the identification of cosine dependence when the error is randomly distributed between clockwise and counterclockwise galaxies. However, when the error is not random, even a small bias of 1% leads to a statistically significant cosine dependence that peaks at the celestial pole. Experiments with artificial datasets in which the distribution was not random showed strong cosine dependence even when the data did not form a full dipole axis alignment. The analysis when using the unmodified data shows asymmetry profile similar to the profile shown in multiple previous studies using several different telescopes.
topic cosmology
galaxies
large-scale structure
url https://www.mdpi.com/2571-712X/4/1/2
work_keys_str_mv AT liorshamir analysisofthealignmentofnonrandompatternsofspindirectionsinpopulationsofspiralgalaxies
_version_ 1724347926744924160