A model for the mass and distribution of particles in dark matter halos
Bibliographic record
Abstract
This model is intended for dark-matter-dominated galaxies and galaxy clusters for which the centrifugal force caused by system rotation is negligible. Such systems, ostensibly dark matter halos, would tend to be spherical. Consider a uniform sphere of identical, massive particles in equilibrium (not contracting or expanding). In the quantum model, gravitation pulls the particles together and quantum uncertainty pushes them apart. In the corresponding classical model, gravitation pulls the particles together and thermal motion pushes them apart. This model provides an expression for particle mass as a function of the total mass and density of the system and its quantum state or temperature. Using the measured total mass and density of our dark-matter-dominated galaxy, and assuming the system is in the ground state, the particle mass is found to be 10.5 eV and the temperature 0.042 K. This represents the lowest possible system temperature and particle mass. If, on the other hand, the system is in equilibrium with the cosmic microwave background, the particle mass is found to be 693 eV. This range of inferred particle masses supports the hypothesis of “low-mass dark matter” with approximate mass 100 eV. However, the system temperature is not presently known so it is possible that the temperature is higher and, consequently, the particles are heavier. The average speed of the particles is found to be approximately 1/1000 the speed of light in our galaxy. Remarkably, this result does not depend on the system temperature and, therefore, does not depend on the particle mass. The extension of this model to variable density provides a straightforward solution to the “core-cusp problem” because the distribution of dark matter that minimizes the system energy has a flat central dark matter density profile.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".