Diffuse x-ray and gamma-ray limits on boson stars that interact with nuclei
Bibliographic record
Abstract
Abstract Light bosonic dark matter can form gravitationally bound states known as boson stars. In this work, we explore a new signature of these objects interacting with the interstellar medium (ISM). We show how small effective couplings between the bosonic dark matter and the nucleon lead to a potential that accelerates ISM baryons as they transit the boson star, making the ISM within radiate at a high rate and energy. The low ISM density, however, implies the majority of Galactic boson stars will be too faint to be observable through this effect. By contrast, the diffuse photon flux, in hard x-rays and soft gamma-rays, produced by boson stars interacting with the ionized ISM phases can be sizable. We compute this diffuse flux and compare it to existing observations from HEAO-1, INTEGRAL and COMPTEL to infer limits on the fraction of these objects. This novel method places constraints on boson star dark matter while avoiding back-action effects from ambient baryons on the boson star configuration, unlike terrestrial searches where it has been noted that back-action can screen light bosonic fields. In addition, this study could be extended to other couplings and structures formed from light dark matter. For dark matter masses (10-14, 10-8) eV and boson star masses (10-10, 10-1)M⊙, we find the constraints on the fraction can go down to f*≲ 10-9for dark matter in boson stars that is directly coupled to the Standard Model.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".