A novel Cosmic Filament catalogue from SDSS data

  title={A novel Cosmic Filament catalogue from SDSS data},
  author={Javier Carr'on Duque and Marina Migliaccio and Domenico Marinucci and Nicola Vittorio},
  journal={Astronomy \& Astrophysics},
Aims. In this work we present a new catalogue of Cosmic Filaments obtained from the latest Sloan Digital Sky Survey (SDSS) public data. Methods. In order to detect filaments, we implement a version of the Subspace-Constrained Mean-Shift algorithm, boosted by Machine Learning techniques. This allows us to detect cosmic filaments as one-dimensional maxima in the galaxy density distribution. Our filament catalogue uses the cosmological sample of SDSS, including Data Release 16, so it inherits its… 


Density Estimation for Statistics and Data Analysis.
The two main aims of the book are to explain how to estimate a density from a given data set and to explore how density estimates can be used, both in their own right and as an ingredient of other statistical procedures.
2014b, arXiv:1406.1803 [cs
  • 2014
sorFlow, 2nd Edition [Book] (O’Reilly Media
  • 2005
Hands-On Machine Learning with Scikit-Learn, Keras, and Ten
  • 2014
Density Estimation for Statistics and Data Analysis