Magnetic Fields in Starburst Galaxies and The Origin of the FIR-Radio Correlation
Bibliographic record
Abstract
We estimate minimum energy magnetic fields (B_min) for a sample of galaxies with measured gas surface densities, spanning from normal spirals to starbursts. We show that the ratio of the minimum energy magnetic pressure to the total pressure in the ISM decreases substantially with increasing surface density; for Arp 220 this ratio is ~10^-4. Therefore, if the minimum energy estimate is applicable, magnetic fields in starbursts are dynamically weak compared to gravity, in contrast to normal spiral galaxies. We argue, however, that rapid cooling of relativistic electrons in starbursts invalidates the minimum energy estimate. We critically assess a number of independent constraints on the magnetic field strength in starbursts. In particular, we argue that the existence of the FIR-radio correlation implies that the synchrotron cooling timescale for cosmic ray electrons is much shorter than their escape time from the galactic disk; this in turn implies that the true magnetic field in starbursts is significantly larger than B_min. The strongest argument against such large fields is that one might expect starbursts to have steep radio spectra indicative of strong synchrotron cooling, which is not observed. We show, however, that ionization and bremsstrahlung losses can flatten the nonthermal spectra of starburst galaxies even in the presence of rapid cooling, providing much better agreement with observed spectra. We further demonstrate that ionization and bremsstrahlung losses are likely to be important in shaping the radio spectra of most starbursts at GHz frequencies, thereby preserving the linearity of the FIR-radio correlation. We thus conclude that magnetic fields in starbursts are significantly larger than B_min. We highlight several observations that can test this conclusion.
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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) | 0.000 | 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 | 0.000 |
| 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".