Self-similarity of the mass distribution in rich galaxy clusters up to <i>z</i>∼1 tracked with weak lensing
Bibliographic record
Abstract
In the standard theory of growth of nonbaryonic dark matter, cosmic structures form hierarchically and self-similarly from smaller clumps. The assembly merger tree extends from the linear perturbations in the early Universe to highly non-linear structures at late times. Gravity is the driving force, and self-similarity should inform cosmic haloes. However, it is unclear whether the apparent anomalies at non-linear scales are due to baryonic or new physics. I show that the mass distribution of rich haloes evolved self-similarly at least since the Universe was 5.7 Gyr old. Using gravitational weak lensing, I constrained the mass profiles of galaxy clusters with M200c ≳ 2 × 1014 M⊙ that were optically detected in the HSC-SSP survey in the redshift range 0.2 ≤ z < 1.0. The cluster self-similarity confirms the standard theory of growth in the non-linear regime. Clusters are still growing, but neither violent mergers nor matter slowly falling in from the cosmic web disrupt the self-similarity, which is in place well before the halo formation time. Dark matter growth can fit the fossil cosmic microwave background as well as young, very massive haloes. Next-generation survey searches at scales in clusters in which self-similarity breaks might pose a new challenge to dark matter.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".