Primordial Galactic Magnetic Fields: An Application of QCD Domain Walls
Bibliographic record
Abstract
We present a mechanism for generating primordial magnetic fields with large correlation lengths on the order of 100 kpc today. The mechanism is based on recently conjectured QCD domain walls or similar CP violating domain walls with QCD scale structure. Such domain walls align the electric and magnetic dipole moments of the nucleons shortly after the QCD phase transition, producing electromagnetic fields correlated along the domain walls. Through the Kibble mechanism, the domain walls attain Hubble-scale correlations which they transfer to the aligned electromagnetic fields. Due to the CP violation, the Hubble-scale walls produce helical (non-zero Chern-Simons) magnetohydrodynamic turbulence which then undergoes an inverse cascade, allowing the correlation lengths to grow to 100 kpc today. We present an estimate the magnitude of the generated electromagnetic fields in terms of the QCD parameters. We also discuss some other unexplained astrophysical phenomena which may be related to this mechanism. In particular, we discuss the relation between primordial magnetic fields and the Greisen-Zatsepin-Kuzmin (GZK) cutoff violations. We also outline how, by creating inhomogeneities in the nucleon density, QCD domain walls may lead to inhomogeneous big bang nucleosynthesis (IBBN) explaining the Omega_B excess recently measured through cosmic microwave background (CMB) distortions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".