A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity
Bibliographic record
Abstract
ABSTRACT Radio broad-band spectro-polarimetric observations are sensitive to the spatial fluctuations of the Faraday depth (FD) within the telescope beam. Such FD fluctuations are referred to as ‘Faraday complexity’, and can unveil small-scale magneto-ionic structures in both the synchrotron-emitting and the foreground volumes. We explore the astrophysical origin of the Faraday complexity exhibited by 191 polarized extragalactic radio sources (EGSs) within $5^\circ$ from the Galactic plane in the longitude range of $20^\circ$–$52^\circ$, using broad-band data from the Karl G. Jansky Very Large Array presented by a previous work. A new parameter called the FD spread is devised to quantify the spatial FD fluctuations. We find that the FD spread of the EGSs (i) demonstrates an enhancement near the Galactic mid-plane, most notable within Galactic latitude of $\pm 3^\circ$, (ii) exhibits hints of modulations across Galactic longitude, (iii) does not vary with the source size across the entire range of $2.5$–$300\,\,\mathrm{ arcsec}$, and (iv) has an amplitude higher than expected from magneto-ionic structures of extragalactic origin. All these suggest that the primary cause of the Faraday complexity exhibited by our target EGSs is $< 2.5\,\,\mathrm{ arcsec}$-scale magneto-ionic structures in the Milky Way. We argue that the anisotropic turbulent magnetic fields generated by galactic-scale shocks and shears, or the stellar feedback-driven isotropic turbulent magnetic fields, are the most likely candidates. Our work highlights the use of broad-band radio polarimetric observations of EGSs as a powerful probe of multiscale magnetic structures in the Milky Way.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".