Impulsive radio events in quiet solar corona and axion quark nugget dark matter
Bibliographic record
Abstract
The Murchison Widefield Array (MWA) recorded impulsive radio events in the quiet solar corona at frequencies 98, 120, 132, and 160 MHz [S. Mondal, D. Oberoi, and A. Mohan, Astrophys. J. 895, L39 (2020)]. We propose that these radio events are the direct manifestation of dark matter annihilation events within the axion quark nugget (AQN) framework. It has been argued [A. Zhitnitsky, J. Cosmol. Astropart. Phys. 10 (2017) 050; N. Raza, L. vanWaerbeke, and A. Zhitnitsky, Phys. Rev. D 98, 103527 (2018)] that the AQN-annihilation events in the quiet solar corona can be identified with the nanoflares conjectured by Parker [Astrophys. J. 264, 642 (1983)]. We further support this claim by demonstrating that observed impulsive radio events [S. Mondal, D. Oberoi, and A. Mohan, Astrophys. J. 895, L39 (2020)], including their rate of appearance, their temporal and spatial distributions, and their energetics, are matching the generic consequences of AQN annihilations in the quiet corona. We propose to test this idea by analyzing the correlated clustering of impulsive radio events in different frequency bands. These correlations are expressed in terms of the time delays between radio events in different frequency bands measured in seconds. We also make generic predictions for low (80 and 89 MHz) and high (179, 196, 217, and 240 MHz) frequency bands, that have been recorded, but not published, by Mondal et al. [Astrophys. J. 895, L392020]. We finally suggest to test our proposal by studying possible cross-correlation between MWA radio signals and Solar Orbiter recording of extreme UV photons (aka ``campfires'').
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 | 0.001 |
| 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 | 0.001 |
| 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".