Issue |
A&A
Volume 576, April 2015
|
|
---|---|---|
Article Number | L17 | |
Number of page(s) | 4 | |
Section | Letters | |
DOI | https://doi.org/10.1051/0004-6361/201526006 | |
Published online | 17 April 2015 |
Cosmic web-type classification using decision theory
1
Institut d’Astrophysique de Paris (IAP), UMR 7095, CNRS – UPMC Université
Paris 6, Sorbonne Universités,
98bis boulevard Arago,
75014
Paris,
France
2
Institut Lagrange de Paris (ILP), Sorbonne
Universités, 98bis boulevard
Arago, 75014
Paris,
France
3
École polytechnique ParisTech, Route de Saclay,
91128
Palaiseau,
France
e-mail:
florent.leclercq@polytechnique.org
4
Excellence Cluster Universe, Technische Universität
München, Boltzmannstrasse
2, 85748
Garching,
Germany
5
Department of Physics, University of Illinois at
Urbana-Champaign, Urbana, IL
61801,
USA
Received: 2 March 2015
Accepted: 29 March 2015
Aims. We propose a decision criterion for segmenting the cosmic web into different structure types (voids, sheets, filaments, and clusters) on the basis of their respective probabilities and the strength of data constraints.
Methods. Our approach is inspired by an analysis of games of chance where the gambler only plays if a positive expected net gain can be achieved based on some degree of privileged information.
Results. The result is a general solution for classification problems in the face of uncertainty, including the option of not committing to a class for a candidate object. As an illustration, we produce high-resolution maps of web-type constituents in the nearby Universe as probed by the Sloan Digital Sky Survey main galaxy sample. Other possible applications include the selection and labelling of objects in catalogues derived from astronomical survey data.
Key words: large-scale structure of Universe / methods: statistical / catalogs
© ESO, 2015
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.