Magnetic field strength in cosmic web filaments
Bibliographic record
Abstract
ABSTRACT We used the rotation measure (RM) catalogue derived from the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS DR2) at 144 MHz to measure the evolution with redshift of the extragalactic RM (RRM: Residual RM) and the polarization fraction (p) of sources in low-density environments. We also measured the same at 1.4 GHz by cross-matching with the NRAO VLA Sky Survey RM catalogue. We find that RRM versus redshift is flat at 144 MHz, but, once redshift-corrected, it shows evolution at high significance. Also, p evolves with redshift with a decrement by a factor of ∼8 at z ∼ 2. Comparing the 144-MHz and 1.4-GHz data, we find that the observed RRM and p are most likely to have an origin local to the source at 1.4 GHz, while a cosmic web filament origin is favoured at 144 MHz. If we attribute the entire signal to filaments, we infer a mean rest-frame RRM per filament of RRM$_{\rm 0,f} = 0.71 \pm 0.07 \, \, \rm rad\, m^{-2}$ and a magnetic field per filament of Bf = 32 ± 3 nG. This is in agreement with estimates obtained with a complementary method based on synchrotron emission stacking, and with cosmological simulations if primordial magnetic fields are amplified by astrophysical source field seeding. The measurement of an RRM0, f supports the presence of diffuse baryonic gas in filaments. We also estimated a conservative upper limit of the filament magnetic turbulence of $\sigma _{\rm RRM_{\rm 0,f}} =0.039 \pm 0.001 \, \, \rm rad\, m^{-2}$, concluding that the ordered magnetic field component dominates in filaments.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".