Regression of Fluctuating System Properties: Baryonic Tully–Fisher Scaling in Disk Galaxies

Geert Verdoolaege

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In various interesting physical systems, important properties or dynamics display a strongly fluctuating behavior that can best be described using probability distributions. Examples are fluid turbulence, plasma instabilities, textured images, porous media and cosmological structure. In order to quantitatively compare such phenomena, a similarity measure between distributions is needed, such as the Rao geodesic distance on the corresponding probabilistic manifold. This can form the basis for validation of theoretical models against experimental data and classification of regimes, but also for regression between fluctuating properties. This is the primary motivation for geodesic least squares (GLS) as a robust regression technique, with general applicability. In this contribution, we further clarify this motivation and we apply GLS to Tully–Fisher scaling of baryonic mass vs. rotation velocity in disk galaxies. We show that GLS is well suited to estimate the coefficients and tightness of the scaling. This is relevant for constraining galaxy formation models and for testing alternatives to the Lambda cold dark matter cosmological model.

Original languageEnglish
Title of host publicationBayesian Inference and Maximum Entropy Methods in Science and Engineering - MaxEnt 37, 2017
EditorsFrancisco Louzada, Julio Stern, Hellinton Takada, Adriano Polpo, Rafael Izbicki
PublisherSpringer New York LLC
Pages77-87
Number of pages11
ISBN (Print)9783319911427
DOIs
Publication statusPublished - 2018
Event37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2017 - Jarinu, Brazil
Duration: 9 Jul 201714 Jul 2017

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume239
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

Conference37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2017
Country/TerritoryBrazil
CityJarinu
Period9/07/1714/07/17

Keywords

  • Information geometry
  • Rao geodesic distance
  • Regression analysis
  • Tully-Fisher scaling

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