sconce: a cosmic web finder for spherical and conic geometries

Area of Science:

• Cosmology
• Astrophysics
• Galaxy Formation and Evolution

Background:

• The cosmic web's structure reveals insights into large-scale structure formation.
• Current cosmic web identification methods often assume Euclidean geometry, limiting their accuracy.

Purpose of the Study:

• To introduce sconce (Spherical and Conic Cosmic web finder), a novel method for cosmic web identification.
• To address limitations in filament detection within non-Euclidean cosmic geometries.

Main Methods:

• Developed algorithms generalizing the subspace constrained mean shift (scms) method.
• Implemented sconce to inherently consider 2D spherical and 3D conic geometries.
• Tested with artificial data, the SDSS galaxy catalogue, and Illustris N-body simulations.

Main Results:

• The 2D spherical sconce algorithm demonstrates robustness in high declination regions.
• The 3D conic sconce algorithm shows improved filament detection compared to standard scms under redshift distortions.
• sconce algorithms are invariant to data rotations and intrinsic to spherical/conic geometry.

Conclusions:

• sconce offers a more robust approach to cosmic web and filament detection.
• The method's geometric considerations improve accuracy in cosmological data analysis.
• The sconce-scms Python package is publicly available for broader research use.