Cosmic web-type classification using decision theory

Abstract

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. 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. 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.

6 pages, 2 figures, text matches A&A Letters published version, figures contain more panels

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Cited by in corpus (17)

• Tracing the cosmic web
• Baryons in the CosmicWeb of IllustrisTNG - I: Gas in Knots, Filaments, Sheets and Voids
• Fast and accurate mock catalogue generation for low-mass galaxies
• Using rotation measure grids to detect cosmological magnetic fields -- a Bayesian approach
• Bayesian cosmic density field inference from redshift space dark matter maps
• Comparing cosmic web classifiers using information theory
• Probabilistic cosmic web classification using fast-generated training data
• The sparkling Universe: Clustering of voids and void clumps
• The Fabric of the Universe: Exploring the cosmic web in 3D prints and woven textiles
• The four cosmic tidal web elements from the $\beta$-skeleton
• Bayesian large-scale structure inference and cosmic web analysis
• Data-Space Validation of High-Dimensional Models by Comparing Sample Quantiles
• Mean maps for cosmic web structures in cosmological initial conditions
• SOMBI: Bayesian identification of parameter relations in unstructured cosmological data
• Probabilistic cartography of the large-scale structure
• Bisous model - detecting filamentary patterns in point processes
• Testing Inflationary Cosmology