The redshift evolution of Λ cold dark matter halo parameters: concentration, spin and shape
Bibliographic record
Abstract
We present a detailed study of the redshift evolution of dark matter halo structural parameters in a Λ cold dark matter cosmology. We study the mass and redshift dependence of the concentration, shape and spin parameter in N-body simulations spanning masses from 1010 to 1015h−1 M⊙ and redshifts from 0 to 2. We present a series of fitting formulae that accurately describe the time evolution of the concentration–mass (cvir–Mvir) relation since z= 2. Using arguments based on the spherical collapse model, we study the behaviour of the scalelength of the density profile during the assembly history of haloes, obtaining physical insights into the origin of the observed time evolution of the cvir–Mvir relation. We also investigate the evolution with redshift of dark matter halo shape and its dependence on mass. Within the studied redshift range, the relation between the halo shape and mass can be well fitted by a redshift-dependent power law. Finally we show that although for z= 0 the spin parameter is practically mass independent, at increasing redshift it shows an increasing correlation with mass.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".