From a volume-limited sample of 45 542 galaxies and 6000 groups with z ≤ 0.213, we use an adapted minimal spanning tree algorithm to identify and classify large-scale structures within the Galaxy And Mass Assembly (GAMA) survey. Using galaxy groups, we identify 643 filaments across the three equatorial GAMA fields that span up to 200 h−1 Mpc in length, each with an average of eight groups within them. By analysing galaxies not belonging to groups, we identify a secondary population of smaller coherent structures composed entirely of galaxies, dubbed ‘tendrils’ that appear to link filaments together, or penetrate into voids, generally measuring around 10 h−1 Mpc in length and containing on average six galaxies. Finally, we are also able to identify a population of isolated void galaxies. By running this algorithm on GAMA mock galaxy catalogues, we compare the characteristics of large-scale structure between observed and mock data, finding that mock filaments reproduce observed ones extremely well. This provides a probe of higher order distribution statistics not captured by the popularly used two-point correlation function.
- Methods: observational
- Large-scale structure of Universe
- Cosmic web
- Redshift survey
- Luminosity functions