A universal profile for stacked filaments from cold dark matter simulations
Bibliographic record
Abstract
ABSTRACT We study the stacked filaments connecting group-mass halo pairs, using dark-matter-only N-body simulations. We calculate the dark matter overdensity profile of these stacked filaments at different redshifts as a function of the distance perpendicular to the filament axis. A four-parameter universal functional form, including three comoving scale radii and one amplitude parameter (core density), provides a good fit out to a radius of 20h−1cMpc for stacked filaments over a range of redshifts, lengths, and masses. The scale radii are approximately independent of redshift but increase as power laws with the comoving filament length. Lastly, we compare the scaling of the filament mass measured directly from the simulations to the predicted scaling from the halo–halo–matter three-point correlation function as a function of redshift and of the mass of the halo pairs. We find that both measured scalings are similar to, but somewhat shallower than the predictions, by 10 per cent and 30 per cent, respectively. These results provide a template to interpret present and upcoming observational results based on stacking, for example, weak lensing, thermal and kinetic Sunyaev-Zel’dovich, or X-ray observations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".