Identification of filamentary structures in the environment of superclusters of galaxies in the Local Universe
Bibliographic record
Abstract
Context.Characterization of the internal structure of the superclusters of galaxies (walls, filaments, and knots where the clusters are located) is crucial for understanding the formation of the large-scale structure and for outlining the environment where galaxies evolved in the last few gigayears. Aims.We aim to detect the compact regions of high relative density (clusters and rich groups of galaxies), to map the elongated structures of low relative density (filaments, bridges, and tendrils of galaxies), and to characterize the galaxies that populate the filaments and study the environmental effects they are subject to. Methods.We used optical galaxies with spectroscopic redshifts from the SDSS-DR13 inside rectangular boxes encompassing the volumes of a sample of 46 superclusters of galaxies up toz= 0.15. A virial approximation was applied to correct the positions of the galaxies in the redshift space for the “finger of God” projection effect. Our methodology implements different classical pattern recognition and machine-learning techniques (Voronoi tessellation, hierarchical clustering, graph-network theory, and minimum spanning trees, among others), pipelined in the Galaxy System-Finding algorithm and the Galaxy Filament-Finding algorithm. Results.In total, we detected 2705 galaxy systems (clusters and groups, of which 159 are new) and 144 galaxy filaments in the 46 superclusters of galaxies. The filaments we detected have a density contrast of above 3, with a mean value of around 10, a radius of about 2.5 h70−1Mpc, and lengths of between 9 and 130 h70−1Mpc. Correlations between the galaxy properties (mass, morphology, and activity) and the environment in which they reside (systems, filaments, and the dispersed component) suggest that galaxies closer to the skeleton of the filaments are more massive by up to 25% compared to those in the dispersed component; 70% of the galaxies in the filament region present early-type morphologies and the fractions of active galaxies (both AGNs and star-forming galaxies) seem to decrease as galaxies approach the filament. Conclusions.Our results support the idea that galaxies in filaments are subject to environmental effects leading them to be more massive (probably due to larger rates of both merging and gas accretion), less active both in star formation and nuclear activity, and prone to the density–morphology relation. These results suggest that preprocessing in large-scale filaments could have significant effects on galaxy evolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".