The Bullet Cluster 1E0657-558 evidence shows Modified Gravity in the absence of Dark Matter
Bibliographic record
Abstract
A detailed analysis of the November 15, 2006 data release (Clowe et al., 2006) X-ray surface density Sigma-map and the strong and weak gravitational lensing convergence kappa-map for the Bullet Cluster 1E0657-558 is performed and the results are compared with the predictions of a modified gravity (MOG) and dark matter. Our surface density Sigma-model is computed using a King beta-model density, and a mass profile of the main cluster and an isothermal temperature profile are determined by the MOG. We find that the main cluster thermal profile is nearly isothermal. The MOG prediction of the isothermal temperature of the main cluster is T = 15.5 +- 3.9 keV, in good agreement with the experimental value T = 14.8{+2.0}{-1.7} keV. Excellent fits to the two-dimensional convergence kappa-map data are obtained without non-baryonic dark matter, accounting for the 8-sigma spatial offset between the Sigma-map and the kappa-map reported in Clowe et al. (2006). The MOG prediction for the kappa-map results in two baryonic components distributed across the Bullet Cluster 1E0657-558 with averaged mass-fraction of 83% intracluster medium (ICM) gas and 17% galaxies. Conversely, the Newtonian dark matter kappa-model has on average 76% dark matter (neglecting the indeterminant contribution due to the galaxies) and 24% ICM gas for a baryon to dark matter mass-fraction of 0.32, a statistically significant result when compared to the predicted Lambda-CDM cosmological baryon mass-fraction of 0.176{+0.019}{-0.012} (Spergel et al., 2006).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".