Cosmic Web Reconstruction through Density Ridges: Catalogue
Yen-Chi Chen, Shirley Ho, Jon Brinkmann, Peter E. Freeman, Christopher, R. Genovese, Donald P. Schneider, Larry Wasserman

TL;DR
This paper presents a new catalogue of cosmic filaments detected using the SCMS method, which traces density ridges in galaxy data from SDSS across different redshifts, and analyzes galaxy luminosity relations.
Contribution
It introduces a novel filament detection approach based on density ridges with uncertainty measures, applied to SDSS data to map the cosmic web up to redshift 0.7.
Findings
Filament maps cover redshifts up to 0.7.
Galaxies near filaments are significantly brighter.
The catalogue provides statistical insights into cosmic web evolution.
Abstract
We construct a catalogue for filaments using a novel approach called SCMS (subspace constrained mean shift; Ozertem & Erdogmus 2011; Chen et al. 2015). SCMS is a gradient-based method that detects filaments through density ridges (smooth curves tracing high-density regions). A great advantage of SCMS is its uncertainty measure, which allows an evaluation of the errors for the detected filaments. To detect filaments, we use data from the Sloan Digital Sky Survey, which consist of three galaxy samples: the NYU main galaxy sample (MGS), the LOWZ sample and the CMASS sample. Each of the three dataset covers different redshift regions so that the combined sample allows detection of filaments up to z = 0.7. Our filament catalogue consists of a sequence of two-dimensional filament maps at different redshifts that provide several useful statistics on the evolution cosmic web. To construct the…
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