The Halo Mass–Temperature Relation for Clusters, Groups, and Galaxies
Bibliographic record
Abstract
Abstract The halo mass–temperature (M–T) relation for a sample of 216 galaxy clusters, groups, and individual galaxies observed by the Chandra X-ray Observatory is presented. Using accurate spectral measurements of their hot atmospheres, we derive the M–T relation for systems with temperatures ranging between 0.4 and 15.0 keV. We measure the total masses of the clusters, groups, and galaxies at radius R 2500, finding that the M 2500 ∝ T α relation follows a power law with α = 1.65 ± 0.06. Our relation agrees with recent lensing studies of the M–T relation at R 200 and is consistent with self-similar theoretical predictions and recent simulations. This agreement indicates that the M–T relation is weakly affected by nongravitational heating processes. Using lensing masses within R 200 we find M 200–T follows a power law with a slope of 1.61 ± 0.19, consistent with the M 2500–T relation. No evidence for a break or slope change is found in either relation. Potential biases associated with sample selection, evolution, and the assumption of hydrostatic equilibrium that may affect the scaling are examined. No significant impacts attributable to these biases are found. Non-cool-core clusters and early spirals produce higher scatter in the M–T relation than cool-core clusters and elliptical galaxies.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".