Pith. sign in

REVIEW 4 major objections 4 minor 1 cited by

A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity

T0 review · 4 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

Pith's one-line read The Faraday complexity seen toward 191 extragalactic radio sources near the Galactic plane comes primarily from Milky Way magneto-ionic structures smaller than 2.5 arcseconds, not from the sources or the telescope.

desk verdict A careful, honest paper that likely opens a new observational window into small-scale Galactic magnetic structure, but the central amplitude comparison rests on an extrapolated RM structure function and a heterogeneous extragalactic benchmark. read the letter →

arxiv 2506.18968 v1 pith:VKTSTYAM submitted 2025-06-23 astro-ph.GA

classification astro-ph.GA
keywords FaradaycomplexitydepthGalacticmagneticfieldsinterstellarmediumradiopolarimetryrotationmeasuremagneto-ionicstructuresturbulence
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to establish where the 'Faraday complexity' of background radio sources near the Milky Way's plane comes from: the sources themselves, the instrument, or gas and magnetic fields inside our Galaxy. Using 191 polarised extragalactic sources observed at 1–2 GHz, the authors define a new quantity, the FD spread, that captures the spatial scatter of Faraday depth within each source. They find the spread is largest near the Galactic mid-plane, roughly constant for source sizes from 2.5 to 300 arcseconds, and larger than extrapolations of the rotation-measure structure function predict. Together the evidence points to magneto-ionic structures smaller than 2.5 arcseconds in the Milky Way—most plausibly an anisotropic turbulent magnetic field shaped by spiral-arm shocks and shear, or small-scale turbulence from stellar winds—as the primary cause.

What carries the argument

The load-bearing object is the FD spread, a single number per source constructed from the best-fit Stokes QU-fitting model: $$\text{FD spread}=\sqrt{\frac{1}{N}\sum_i(\phi_i-\bar{\phi})^2+\sum_i\sigma_{\phi,i}^2+\sum_i\$\Delta$\$phi_i^{2}$}.$$ It converts the multi-component Faraday depth information of each source into a uniform measurement of spatial FD fluctuation, deliberately not weighting by polarised intensity as the RM-spectrum second moment does. The argument then leans on comparing twice the square of the FD spread against the RM structure function, exploiting the identity that a Gaussian FD distribution with variance $\sigma^2$ produces an RM structure-function amplitude of $2\sigma^2$. The paper's conclusion follows from the mismatch between the two quantities at angular scales of 2.5–300 arcseconds, combined with the absence of any dependence of FD spread on source size.

What would settle it

A direct measurement of the rotation-measure structure function below an arcminute, for example from high-resolution Faraday depth maps of a compact source field at about one arcsecond resolution, would show whether the RM variance actually reaches the level implied by the extrapolation; if the power law breaks and rises before 2.5 arcseconds, the two-order-of-magnitude gap disappears. Alternatively, a survey toward the Galactic anticentre testing the paper's prediction that no enhanced FD spread should appear there would distinguish the anisotropic-field explanation from a stellar-feedback origin.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that the Faraday complexity seen in the sample is dominated by sub-2.5-arcsecond magneto-ionic structures in the Milky Way foreground, not by the extragalactic sources or by instrumental artifacts. The new FD spread statistic has a mean of about 42 rad m$^{-2}$ (65 rad m$^{-2}$ among Faraday-complex sources), enhances toward $|b|<3^\circ$, shows a hint of excess around the Scutum arm tangent near $\ell=28$–$32^\circ$, and is independent of source angular size between 2.5 and 300 arcseconds. The decisive comparison is that twice the square of the FD spread lies up to two orders of magnitude above the rotation-measure structure function extrapolated to the same angular scales, so the conventional supernova-driven isotropic turbulent field cannot account for the signal.

Load-bearing premise

The argument that the FD spread amplitude exceeds the expected turbulence signal depends on the rotation-measure structure function power law measured between source pairs at larger separations continuing down to 2.5 arcseconds without a break or flattening.

Editorial extensions

If this is right

  • Galactic magnetism studies that use compact extragalactic sources as Faraday probes must treat each source's FD as potentially contaminated by sub-2.5-arcsecond Milky Way structures; selecting spatially extended sources and discarding Faraday-simple compact sources may be the safer strategy in the surveyed region.
  • High-resolution spectro-polarimetric follow-up at about one arcsecond should resolve the responsible structures into patches of different Faraday depth, and if the anisotropic turbulent field is the cause, the coherence length should be shorter along Galactic longitude than latitude.
  • The Scutum-arm-tangent excess, where only 15 percent of sources are Faraday simple compared with 41 percent elsewhere, predicts that Faraday complexity can serve as a tracer of spiral-arm compressions.
  • Omitting foreground diffuse-emission subtraction inflates the measured FD spread by about 50 percent, so future RM surveys in this region need that subtraction before quantifying Faraday complexity.
  • The two proposed mechanisms make opposite predictions toward the Galactic anticentre: no enhanced FD spread if anisotropic fields aligned with ring tangents dominate, versus possibly still elevated spread from stellar-wind bubbles, so observations there can separate the two.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the sub-2.5-arcsecond structures are real and widespread, the effective small-scale Faraday sky is much rougher than turbulence-cascade models predict, implying an additional energy-injection or anisotropy mechanism at physical scales below about 0.1 parsec at typical Galactic-plane distances.
  • The FD spread statistic could be applied to polarised sources behind other spiral galaxies or gas-rich systems, where the foreground structure function is measured at parsec scales, to test whether such ultra-compact magneto-ionic structure is generic rather than unique to the Milky Way.
  • A direct statistical test would compare the FD spread distribution of sources behind the Galactic plane with a matched sample at high latitude at the same angular resolution, isolating the Galactic contribution without relying on the structure-function extrapolation.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. This paper re-uses VLA L-band spectro-polarimetric data from Ma et al. (2020) for 191 polarized extragalactic sources at Galactic latitude |b| <= 5 deg and longitude 20-52 deg, applies Stokes QU-fitting with eight astrophysical models, and defines a new 'FD spread' parameter (Eq. 12) to quantify intra-source Faraday-depth variance. The authors report an enhancement of FD spread near the Galactic mid-plane with a fitted exponential scale height of about 5 deg, hints of longitudinal modulation around the Scutum arm tangent, no dependence of FD spread on source angular size over 2.5 arcsec to 300 arcsec, and no correlation with spectral index or H-alpha intensity. By comparing 2 x (FD spread)^2 with an RM structure function constructed from the same sources (Figs. 6-7), they conclude that the supernova-driven isotropic turbulent magnetic field cannot explain the amplitude, and that the Faraday complexity is dominated by <2.5 arcsec-scale magneto-ionic structures in the Milky Way, possibly the anisotropic turbulent magnetic field or stellar-wind-driven turbulence.

Significance. If the central conclusion is correct, the paper opens a genuinely new observational window: broadband polarimetry of background EGSs could map sub-arcsecond to sub-parsec scale magneto-ionic structure in the Milky Way using unresolved sources. The paper is methodologically transparent and unusually thorough in its robustness checks: it publishes machine-readable QU-fitting results and spectra, tests foreground subtraction (App. C), Delta-BIC filtering (App. D), and exclusion of sinc-component models (App. E), and it provides three concrete, falsifiable predictions in Section 4.2.4. These strengths make the study a useful contribution even if the <2.5 arcsec scale interpretation is later refined. However, the strongest quantitative inference depends on an extrapolation of the RM structure function to angular scales where no direct measurements exist, and the extragalactic comparison is based on heterogeneous samples, so the paper's headline claim needs additional support or careful qualification.

major comments (4)
  1. [Section 3.1.5, Figs. 6-7, Eq. (17)] The quantitative case against the conventional isotropic turbulent field is carried by comparing 2 x (FD spread)^2 with the RM structure function extrapolated down to 2.5 arcsec. The RM SF is computed from source pairs whose smallest angular separation is limited by the roughly 50 arcsec D-array beam, and the text does not state the minimum pair separation or the number of pairs in the innermost bins. The small-scale fitted slope (+1.07 +/- 0.10) is therefore extrapolated about a decade or more in angular scale down to 2.5 arcsec. If the RM SF flattens or breaks below the smallest measured separations, as expected near an inner scale of magneto-ionic turbulence, the predicted amplitude of 2 x sigma_FD^2 at 2.5 arcsec could be much higher and the claimed two-order discrepancy could largely disappear. Because this discrepancy is the main basis for excluding the supernova-driven isotropic turbulent field in Section 4.2.3, the conclusion is not uniquely established. Please report the minimum separation and fit range explicitly, test the sensitivity to removing the smallest bins, and either provide direct RM SF measurements at sub-arcminute separations or a physical argument bounding the inner scale and break behavior.
  2. [Section 4.1.2, Fig. 10] The claim in the abstract that the FD spread amplitude is higher than expected from extragalactic structures is only weakly supported by the statistical tests as presented. The KS tests comparing the full sample with Anderson et al. (2015) and O'Sullivan et al. (2017) give p = 0.13 and p = 0.33, respectively, meaning the full-sample distributions are not significantly different; only the |b| < 3 deg subset gives p = 0.058 and p = 8.6 x 10^-3 against those two samples. The comparison samples also differ in frequency band, angular resolution, sky region, and in the use of the second moment M2 versus the newly defined FD spread, so the quantitative distribution comparison is not apples-to-apples. Please either repeat the comparison on matched subsamples with comparable frequency coverage and resolution, or explicitly qualify the amplitude claim as applying only to the low-latitude subset.
  3. [Section 2.4, Section 3.1.5, Fig. 5] The inference that the responsible magneto-ionic structures are smaller than 2.5 arcsec uses the total-intensity angular size of each EGS as the scale sampled by the polarization measurement. The VLASS and RACS images trace all radio emission, whereas the polarized emission may be concentrated in compact cores or hotspots embedded in larger lobes. If the polarized emission is compact, the FD spread would be nearly independent of total source size even if the foreground magneto-ionic structures have scales of tens of arcseconds or more. The flat relation in Figure 5 therefore does not by itself place the structure scale below 2.5 arcsec. Please quantify the size of the polarized emitting regions, for example with high-resolution polarimetric data for a subsample, or by splitting the sample according to morphology and fractional polarization, before asserting the sub-2.5-arcsec scale in the conclusions.
  4. [Eq. (12), Section 2.3] FD spread is a model-dependent composite: depending on the best-fit Stokes QU model, it reduces to sigma_phi, Delta_phi, or a mixture of component separation and dispersion terms. The paper provides signal-to-noise cuts and robustness checks against Delta BIC and sinc-component exclusion, but no end-to-end injection-recovery simulations showing that the FD spread estimator is unbiased across the full range of input models, signal-to-noise, and frequency coverage. Such simulations would also test whether measurement noise can produce spurious multi-component fits and hence a positive FD-spread floor that varies with sky position. Given that FD spread is the central new observable, adding at least a targeted noise-injection study would materially strengthen the quantitative latitude and longitude results.
minor comments (4)
  1. [Figs. 6 and 7] The axis labels in the provided text extract appear garbled (e.g. '2 x (FD )p(ea )2'); please ensure the typeset version has correct mathematical notation.
  2. [Section 3.1.5] Please state explicitly the smallest angular separation used in the RM SF, the number of pairs per bin, and the range over which the broken power-law slopes are fitted, so that the reader can assess the extrapolation.
  3. [Section 4.2.3] The phrases 'ruled out' and 'impossible' are stronger than the evidence warrants given the extrapolation discussed in the first major comment; consider phrasing such conclusions as inconsistent with an unbroken power-law extrapolation of the RM SF.
  4. [Eq. (12)] The factor 1/N applies only to the first term in the definition of the FD spread; making this explicit with clearly separated summands would avoid ambiguity.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the FD spread is an independently defined observable and the central comparison against the RM structure function is empirical, though it relies on an extrapolation that is a correctness risk rather than a circular step.

full rationale

The paper's central claim, that <2.5"-scale Milky Way magneto-ionic structures dominate the Faraday complexity of the target EGSs, is not built into the definition of the FD spread or into the Stokes QU-fitting model selection. The FD spread is defined in Equation 12 as a combination of fitted model parameters (component Faraday depths, sigma_phi, and Delta-phi), and the observed constancy of FD spread across source angular sizes is a measured trend, not a tautology. The key amplitude comparison in Section 3.1.5 plots 2 x (FD spread)^2 against an RM structure function constructed independently from the peak RMs of the same 191 sources; this provides an external benchmark and is not the same quantity as the FD spread by construction. The authors further test robustness by removing sinc-component models (Appendix E) and low-DeltaBIC sources (Appendix D), and they compare their FD spread distributions with external samples (Anderson et al. 2015; O'Sullivan et al. 2017), so the conclusion is not solely carried by self-citation. The main vulnerability is that the RM SF at 2.5-300 arcsec is an extrapolation of a broken power-law fitted at separations down to roughly 36 arcsec, with no direct sub-arcminute pair measurements; if the RM SF flattens below the smallest measured separation, the claimed two-order discrepancy would shrink. That is an unverified assumption about the turbulence spectrum, not a circular reduction of the paper's own equations. Self-citations (e.g., Seta et al. 2023 for LMC/SMC RM SF slopes; Ranchod et al. 2024 for southern spiral-arm tangents; Ma et al. 2020 for the data) are supporting or data-provenance references and do not by themselves force the central conclusion. Overall the derivation chain is self-contained enough that no specific circular step can be exhibited.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central claim relies on several modeling choices and extrapolations rather than new physical entities. The main free parameters are descriptive fits and the RM SF power-law fit, with the latter being load-bearing for the '<2.5" scale' conclusion. The assumptions about model completeness, source-size interpretation, RM SF extrapolation, and cross-survey comparability are the key domain assumptions that must hold for the conclusion to be valid.

free parameters (3)
  • Exponential latitude fit amplitude A = 70 +/- 10 rad m^-2 (all data); 100 +/- 10 rad m^-2 (non-zero data)
    Fitted to the binned FD spread versus Galactic latitude in Equation 15 and 16. Descriptive summary of the observed trend, not directly load-bearing for the central claim.
  • Exponential latitude fit scale height C = 4.8 +/- 0.9 deg (all data); 6.3 +/- 1.6 deg (non-zero data)
    Fitted to the same binned data as A. Descriptive summary.
  • RM structure function broken power-law slopes and break = Slopes +0.10 +/- 0.04 and +1.07 +/- 0.10; break at 3.0 +/- 0.3 deg
    Fitted to the RM SF from 191 EGS pairs in Section 3.1.5. The small-scale slope is extrapolated to 2.5 arcseconds to support the central claim, so this fit is load-bearing.
assumptions (4)
  • domain assumption The Stokes QU-fitting model set (1T, 2T, 1Ed, 2Ed-c, 2Ed-s, 1S, 2S, 1Id) is complete enough to represent the true polarization structure of the sources.
    Section 2.3: the analysis selects among these models, and the FD spread is computed from the best-fit parameters. If the true polarization structure lies outside this model set, the FD spread would be biased.
  • domain assumption The angular size of EGSs measured from 2.5-arcsec VLASS total intensity images is an upper limit to the scale of magneto-ionic structures probed by the 50-arcsec polarization beam.
    Section 2.4 and Section 3.1.5: this assumption underpins the interpretation that constant FD spread with source size implies structure smaller than 2.5 arcseconds.
  • domain assumption The RM structure function power law measured at source-pair separations can be extrapolated to 2.5 arcseconds without a break or flattening.
    Section 3.1.5, Figure 6: the comparison of FD spread with the RM SF at 2.5-300 arcseconds relies on this extrapolation because no direct pair measurements exist at those small separations.
  • domain assumption Literature FD spread measurements from Anderson et al. (2015) and O'Sullivan et al. (2017) can be directly compared to this work without correcting for differences in angular resolution and frequency.
    Section 4.1.2: the argument that the observed FD spread is higher than extragalactic expectations depends on this comparison, even though the surveys differ in beam size (VLA D-array 50 arcsec vs ATCA) and frequency coverage.

how reviews work

0 comments
Cite this review

Pith. "Pith review of A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity." pith.science (2026). https://pith.science/paper/VKTSTYAM

@misc{pith2026250618968,
  author       = {Pith},
  title        = {Pith review of: A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VKTSTYAM}},
  note         = {Machine review of arXiv:2506.18968}
}
read the original abstract

Radio broadband 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 polarised extragalactic radio sources (EGSs) within 5 deg from the Galactic plane in the longitude range of 20-52 deg, using broadband 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 +-3 deg, (ii) exhibits hints of modulations across Galactic longitude, (iii) does not vary with the source size across the entire range of 2.5"-300", 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"-scale magneto-ionic structures in the Milky Way. We argue that the anisotropic turbulent magnetic field generated by galactic-scale shocks and shears, or the stellar feedback-driven isotropic turbulent magnetic field, are the most likely candidates. Our work highlights the use of broadband radio polarimetric observations of EGSs as a powerful probe of multi-scale magnetic structures in the Milky Way.

Figures

Figures reproduced from arXiv: 2506.18968 by the authors.

Figure 1
Figure 1. (Top) Spatial distribution of the best-fit Stokes QU-fitting model (Section 2.3) of the 191 polarised EGSs used in this study: 1T (red), 2T (cyan), 1Ed (orange), 2Ed-c (yellow), 1S (green), 2S (blue), and 1Id (magenta). (Bottom) Correspondingly, the spatial distribution of the spatial FD spread (Section 3.1) measured from the polarised EGSs. In both panels, the background grey-scale image is the Wisconsin H-Alpha Ma… view at source ↗
Figure 2
Figure 2. Example polarisation spectra of our target EGSs. (Left panels) The measured polarisation fraction, Stokes 𝑞 = 𝑄/𝐼, and Stokes 𝑢 = 𝑈/𝐼 across 𝜆 2 are shown as the black, blue, and red data points, respectively. The dashed lines depict the corresponding best-fit results from Stokes QU-fitting (Section 2.3). (Middle panels) The measured PA values across 𝜆 2 are shown as the black data points, with the dashed lines trac… view at source ↗
Figure 2
Figure 2. (Continued) Example polarisation spectra of our target EGSs. NVSS J184415−041757, and NVSS J184547−093821) are now clas￾sified as being unpolarised, as they have no remaining models after filtering. We believe that the linear polarisation signal from these sources reported by Ma et al. (2020) is from the Galactic diffuse polarised emission, which is now removed by our implemented fore￾ground emissions subtraction st… view at source ↗
Figures from the paper (8 more)
Figure 3
Figure 3. Figure 3: Examples of our EGS sample with various morphologies (see panel title suffixes). The background maps in cubehelix colour scheme (Green 2011) are from VLASS (Lacy et al. 2020) epoch 2 with 2. ′′5 beam, while the contours are from RACS-low1 (McConnell et al. 2020) at [2.…
Figure 4
Figure 4. Figure 4: The Galactic latitude and longitude dependences of the spatial FD spread. The 191 polarised EGSs are individually plotted as the black data points in both panels, with error bars included but in most cases are too small to be visible. The data points are further binned…
Figure 5
Figure 5. Figure 5: The FD spread against the angular size (𝜃) of the 191 polarised EGSs, plotted individually as the black data points with error bars included. The data are then averaged in independent angular size bins with constant bin widths in logarithmic space of log10 ( 𝜃/arcsec) …
Figure 7
Figure 7. Figure 7: Similar to [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]
Figure 9
Figure 9. Figure 9: The FD spread of the EGSs against the H𝛼 intensity of the Galactic ISM from WHAMSS (Haffner et al. 2003, 2010). The data points shown in black are further averaged within bins with a constant width in logarithmic space of log10 (𝐼H𝛼/rayleighs) = 0.25, for both cases of…
Figure 10
Figure 10. Figure 10: The statistical distribution of FD spread (for O’Sullivan et al. 2017, as well as this work) and the second moment of Faraday spectrum (𝑀2; for Anderson et al. 2015; Livingston et al. 2021). with Faraday complexity likely dominated by extragalactic contri￾butions (e.g…
Figure 11
Figure 11. Figure 11: Tests for various potential sources of instrumental effects. (Upper left) The FD spread against the PI (obtained from multiplying the 𝑝 from Stokes QU-fitting to the Stokes I flux density at 1400 MHz) of the weaker component. (Upper right) The FD spread against the St…
Figure 12
Figure 12. Figure 12: A schematic of the anisotropic turbulent magnetic fields of the Milky Way (𝐵® aniso) that can explain our observed FD spread towards background EGSs, showing a top-down view of the Milky Way disk as seen from the North Galactic Pole. The background greyscale image sho…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Helical radio jets as probes of magnetised cluster environments: Periodic Faraday Rotation Revealed in the Corkscrew Galaxy by POSSUM

    astro-ph.GA 2026-07 conditional novelty 6.5 of 10

    Periodic RM oscillations matching the Corkscrew jet's lateral deviations reveal a transition from jet/sheath to local-ICM Faraday media along the flow.

Reference graph

Works this paper leans on

131 extracted references · 13 canonical work pages · cited by 1 Pith paper

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    D., Bania T

    Anderson L. D., Bania T. M., Balser D. S., Cunningham V., Wenger T. V., Johnstone B. M., Armentrout W. P., 2014, @doi [ ] 10.1088/0067-0049/212/1/1 , https://ui.adsabs.harvard.edu/abs/2014ApJS..212....1A 212, 1

  3. [3]

    S., Gaensler B

    Anderson C. S., Gaensler B. M., Feain I. J., Franzen T. M. O., 2015, @doi [ ] 10.1088/0004-637X/815/1/49 , https://ui.adsabs.harvard.edu/abs/2015ApJ...815...49A 815, 49

  4. [4]

    G., Beck R., Krause M., Sokoloff D., 2009, @doi [ ] 10.1051/0004-6361:200810964 , https://ui.adsabs.harvard.edu/abs/2009A&A...494...21A 494, 21

    Arshakian T. G., Beck R., Krause M., Sokoloff D., 2009, @doi [ ] 10.1051/0004-6361:200810964 , https://ui.adsabs.harvard.edu/abs/2009A&A...494...21A 494, 21

  5. [5]

    Ashton G., et al., 2019, @doi [ ] 10.3847/1538-4365/ab06fc , https://ui.adsabs.harvard.edu/abs/2019ApJS..241...27A 241, 27

  6. [6]

    Astropy Collaboration et al., 2013, @doi [ ] 10.1051/0004-6361/201322068 , https://ui.adsabs.harvard.edu/abs/2013A&A...558A..33A 558, A33

  7. [7]

    Astropy Collaboration et al., 2018, @doi [ ] 10.3847/1538-3881/aabc4f , https://ui.adsabs.harvard.edu/abs/2018AJ....156..123A 156, 123

  8. [8]

    Astropy Collaboration et al., 2022, @doi [ ] 10.3847/1538-4357/ac7c74 , https://ui.adsabs.harvard.edu/abs/2022ApJ...935..167A 935, 167

Show all 131 references
  1. [9]

    A., Eilek J., Smirnov O., Vacca V., En lin T., 2023, @doi [ ] 10.3847/1538-4357/acebc5 , https://ui.adsabs.harvard.edu/abs/2023ApJ...955...16B 955, 16

    Baidoo L., Perley R. A., Eilek J., Smirnov O., Vacca V., En lin T., 2023, @doi [ ] 10.3847/1538-4357/acebc5 , https://ui.adsabs.harvard.edu/abs/2023ApJ...955...16B 955, 16

  2. [10]

    W., Stevens J., Tuntsov A

    Bannister K. W., Stevens J., Tuntsov A. V., Walker M. A., Johnston S., Reynolds C., Bignall H., 2016, @doi [Science] 10.1126/science.aac7673 , https://ui.adsabs.harvard.edu/abs/2016Sci...351..354B 351, 354

  3. [11]

    Beck R., 2007, @doi [ ] 10.1051/0004-6361:20066988 , https://ui.adsabs.harvard.edu/abs/2007A&A...470..539B 470, 539

  4. [12]

    Beck R., 2015, @doi [ ] 10.1051/0004-6361/201425572 , https://ui.adsabs.harvard.edu/abs/2015A&A...578A..93B 578, A93

  5. [13]

    Beck R., 2016, @doi [ ] 10.1007/s00159-015-0084-4 , http://adsabs.harvard.edu/abs/2015A\

  6. [14]

    D., Gilmore G., eds, Planets, Stars and Stellar Systems

    Beck R., Wielebinski R., 2013, in Oswalt T. D., Gilmore G., eds, Planets, Stars and Stellar Systems. Vol.\ 5: Galactic Structure and Stellar Populations. Springer, Berlin, p. 641

  7. [15]

    Beck R., Brandenburg A., Moss D., Shukurov A., Sokoloff D., 1996, @doi [ ] 10.1146/annurev.astro.34.1.155 , http://adsabs.harvard.edu/abs/1996ARA\

  8. [16]

    D., Ehle M., Moss D., Shoutenkov V., 2005, @doi [ ] 10.1051/0004-6361:20053556 , https://ui.adsabs.harvard.edu/abs/2005A&A...444..739B 444, 739

    Beck R., Fletcher A., Shukurov A., Snodin A., Sokoloff D. D., Ehle M., Moss D., Shoutenkov V., 2005, @doi [ ] 10.1051/0004-6361:20053556 , https://ui.adsabs.harvard.edu/abs/2005A&A...444..739B 444, 739

  9. [17]

    G., 2019, @doi [Galaxies] 10.3390/galaxies8010004 , https://ui.adsabs.harvard.edu/abs/2019Galax...8....4B 8, 4

    Beck R., Chamandy L., Elson E., Blackman E. G., 2019, @doi [Galaxies] 10.3390/galaxies8010004 , https://ui.adsabs.harvard.edu/abs/2019Galax...8....4B 8, 4

  10. [18]

    M., Gie \"u bel R., Mulcahy D

    Beck R., Berkhuijsen E. M., Gie \"u bel R., Mulcahy D. D., 2020, @doi [ ] 10.1051/0004-6361/201936481 , https://ui.adsabs.harvard.edu/abs/2020A&A...633A...5B 633, A5

  11. [19]

    Beuther H., et al., 2016, @doi [ ] 10.1051/0004-6361/201629143 , https://ui.adsabs.harvard.edu/abs/2016A&A...595A..32B 595, A32

  12. [20]

    Boulanger F., et al., 2018, @doi [ ] 10.1088/1475-7516/2018/08/049 , https://ui.adsabs.harvard.edu/abs/2018JCAP...08..049B 2018, 049

  13. [21]

    Brandenburg A., Ntormousi E., 2023, @doi [ ] 10.1146/annurev-astro-071221-052807 , https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..561B 61, 561

  14. [22]

    A., de Bruyn A

    Brentjens M. A., de Bruyn A. G., 2005, @doi [ ] 10.1051/0004-6361:20052990 , http://adsabs.harvard.edu/abs/2005A\

  15. [23]

    C., Taylor A

    Brown J. C., Taylor A. R., 2001, @doi [ ] 10.1086/338358 , https://ui.adsabs.harvard.edu/abs/2001ApJ...563L..31B 563, L31

  16. [24]

    J., 1966, @doi [ ] 10.1093/mnras/133.1.67 , https://ui.adsabs.harvard.edu/abs/1966MNRAS.133...67B 133, 67

    Burn B. J., 1966, @doi [ ] 10.1093/mnras/133.1.67 , https://ui.adsabs.harvard.edu/abs/1966MNRAS.133...67B 133, 67

  17. [25]

    CASA Team et al., 2022, @doi [ ] 10.1088/1538-3873/ac9642 , https://ui.adsabs.harvard.edu/abs/2022PASP..134k4501C 134, 114501

  18. [26]

    H., Del Popolo A., 2022, @doi [ ] 10.1093/mnrasl/slac091 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516L..72C 516, L72

    Chan M. H., Del Popolo A., 2022, @doi [ ] 10.1093/mnrasl/slac091 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516L..72C 516, L72

  19. [27]

    J., Geach J

    Chen J., Lopez-Rodriguez E., Ivison R. J., Geach J. E., Dye S., Liu X., Bendo G., 2024, @doi [A&A] 10.1051/0004-6361/202450969 , 692, A34

  20. [28]

    Cho J., Lazarian A., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06941.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.345..325C 345, 325

  21. [29]

    T., 2002, @doi [ ] 10.1086/324186 , https://ui.adsabs.harvard.edu/abs/2002ApJ...564..291C 564, 291

    Cho J., Lazarian A., Vishniac E. T., 2002, @doi [ ] 10.1086/324186 , https://ui.adsabs.harvard.edu/abs/2002ApJ...564..291C 564, 291

  22. [30]

    W., Fey A

    Clegg A. W., Fey A. L., Fiedler R. L., 1996, @doi [ ] 10.1086/309884 , https://ui.adsabs.harvard.edu/abs/1996ApJ...457L..23C 457, L23

  23. [31]

    J., Cotton W

    Condon J. J., Cotton W. D., Greisen E. W., Yin Q. F., Perley R. A., Taylor G. B., Broderick J. J., 1998, @doi [ ] 10.1086/300337 , http://adsabs.harvard.edu/abs/1998AJ....115.1693C 115, 1693

  24. [32]

    M., et al., 2019, @doi [ ] 10.3847/1538-4357/aaf85f , https://ui.adsabs.harvard.edu/abs/2019ApJ...871..106D 871, 106

    Dickey J. M., et al., 2019, @doi [ ] 10.3847/1538-4357/aaf85f , https://ui.adsabs.harvard.edu/abs/2019ApJ...871..106D 871, 106

  25. [33]

    M., et al., 2022, @doi [ ] 10.3847/1538-4357/ac94ce , https://ui.adsabs.harvard.edu/abs/2022ApJ...940...75D 940, 75

    Dickey J. M., et al., 2022, @doi [ ] 10.3847/1538-4357/ac94ce , https://ui.adsabs.harvard.edu/abs/2022ApJ...940...75D 940, 75

  26. [34]

    T., 2011, Physics of the Interstellar and Intergalactic Medium

    Draine B. T., 2011, Physics of the Interstellar and Intergalactic Medium . Princeton University Press

  27. [35]

    G., Scalo J., 2004, @doi [ ] 10.1146/annurev.astro.41.011802.094859 , https://ui.adsabs.harvard.edu/abs/2004ARA&A..42..211E 42, 211

    Elmegreen B. G., Scalo J., 2004, @doi [ ] 10.1146/annurev.astro.41.011802.094859 , https://ui.adsabs.harvard.edu/abs/2004ARA&A..42..211E 42, 211

  28. [36]

    Englmaier P., Gerhard O., 1999, @doi [ ] 10.1046/j.1365-8711.1999.02280.x , https://ui.adsabs.harvard.edu/abs/1999MNRAS.304..512E 304, 512

  29. [37]

    Farnsworth D., Rudnick L., Brown S., 2011, @doi [ ] 10.1088/0004-6256/141/6/191 , http://adsabs.harvard.edu/abs/2011AJ....141..191F 141, 191

  30. [38]

    S., 2012, @doi [ ] 10.1088/0004-637X/761/2/156 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761..156F 761, 156

    Federrath C., Klessen R. S., 2012, @doi [ ] 10.1088/0004-637X/761/2/156 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761..156F 761, 156

  31. [39]

    Ferri \`e re K., 2020, @doi [Plasma Physics and Controlled Fusion] 10.1088/1361-6587/ab49eb , https://ui.adsabs.harvard.edu/abs/2020PPCF...62a4014F 62, 014014

  32. [40]

    M., Mac Low M.-M., Zweibel E

    Ferriere K. M., Mac Low M.-M., Zweibel E. G., 1991, @doi [ ] 10.1086/170185 , https://ui.adsabs.harvard.edu/abs/1991ApJ...375..239F 375, 239

  33. [41]

    L., Jaffe T

    Ferri \`e re K., West J. L., Jaffe T. R., 2021, @doi [ ] 10.1093/mnras/stab1641 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.4968F 507, 4968

  34. [42]

    M., Horellou C., 2011, @doi [ ] 10.1111/j.1365-2966.2010.18065.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412.2396F 412, 2396

    Fletcher A., Beck R., Shukurov A., Berkhuijsen E. M., Horellou C., 2011, @doi [ ] 10.1111/j.1365-2966.2010.18065.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412.2396F 412, 2396

  35. [43]

    GRAVITY Collaboration et al., 2019, @doi [ ] 10.1051/0004-6361/201935656 , https://ui.adsabs.harvard.edu/abs/2019A&A...625L..10G 625, L10

  36. [44]

    M., Dickey J

    Gaensler B. M., Dickey J. M., McClure-Griffiths N. M., Green A. J., Wieringa M. H., Haynes R. F., 2001, @doi [ ] 10.1086/319468 , http://adsabs.harvard.edu/abs/2001ApJ...549..959G 549, 959

  37. [45]

    M., Landecker T

    Gaensler B. M., Landecker T. L., Taylor A. R., POSSUM Collaboration 2010, BAAS, http://adsabs.harvard.edu/abs/2010AAS...21547013G 42, 515

  38. [46]

    M., et al., 2025, @doi [ ] 10.48550/arXiv.2505.08272 , https://ui.adsabs.harvard.edu/abs/2025arXiv250508272G in press, arXiv:2505.08272

    Gaensler B. M., et al., 2025, @doi [ ] 10.48550/arXiv.2505.08272 , https://ui.adsabs.harvard.edu/abs/2025arXiv250508272G in press, arXiv:2505.08272

  39. [47]

    E., Lopez-Rodriguez E., Doherty M

    Geach J. E., Lopez-Rodriguez E., Doherty M. J., Chen J., Ivison R. J., Bendo G. J., Dye S., Coppin K. E. K., 2023, @doi [ ] 10.1038/s41586-023-06346-4 , https://ui.adsabs.harvard.edu/abs/2023Natur.621..483G 621, 483

  40. [48]

    Goldreich P., Sridhar S., 1995, @doi [ ] 10.1086/175121 , https://ui.adsabs.harvard.edu/abs/1995ApJ...438..763G 438, 763

  41. [49]

    C., Cox D

    G \'o mez G. C., Cox D. P., 2002, @doi [ ] 10.1086/343129 , https://ui.adsabs.harvard.edu/abs/2002ApJ...580..235G 580, 235

  42. [50]

    A., et al., 2021, @doi [ ] 10.3847/1538-4365/ac05c0 , https://ui.adsabs.harvard.edu/abs/2021ApJS..255...30G 255, 30

    Gordon Y. A., et al., 2021, @doi [ ] 10.3847/1538-4365/ac05c0 , https://ui.adsabs.harvard.edu/abs/2021ApJS..255...30G 255, 30

  43. [51]

    A., 2011, @doi [Bulletin of the Astronomical Society of India] 10.48550/arXiv.1108.5083 , https://ui.adsabs.harvard.edu/abs/2011BASI...39..289G 39, 289

    Green D. A., 2011, @doi [Bulletin of the Astronomical Society of India] 10.48550/arXiv.1108.5083 , https://ui.adsabs.harvard.edu/abs/2011BASI...39..289G 39, 289

  44. [52]

    A., 2019, @doi [Journal of Astrophysics and Astronomy] 10.1007/s12036-019-9601-6 , https://ui.adsabs.harvard.edu/abs/2019JApA...40...36G 40, 36

    Green D. A., 2019, @doi [Journal of Astrophysics and Astronomy] 10.1007/s12036-019-9601-6 , https://ui.adsabs.harvard.edu/abs/2019JApA...40...36G 40, 36

  45. [53]

    M., Reynolds R

    Haffner L. M., Reynolds R. J., Tufte S. L., Madsen G. J., Jaehnig K. P., Percival J. W., 2003, @doi [ ] 10.1086/378850 , http://adsabs.harvard.edu/abs/2003ApJS..149..405H 149, 405

  46. [54]

    M., Reynolds R

    Haffner L. M., Reynolds R. J., Madsen G. J., Hill A. S., Barger K. A., Jaehnig K. P., Mierkiewicz E. J., Percival J. W., 2010, BAAS, http://adsabs.harvard.edu/abs/2010AAS...21541528H 42, 265

  47. [55]

    L., et al., 2021, @doi [ ] 10.1017/pasa.2021.47 , https://ui.adsabs.harvard.edu/abs/2021PASA...38...58H 38, e058

    Hale C. L., et al., 2021, @doi [ ] 10.1017/pasa.2021.47 , https://ui.adsabs.harvard.edu/abs/2021PASA...38...58H 38, e058

  48. [56]

    L., Beck R., Ehle M., Haynes R

    Han J. L., Beck R., Ehle M., Haynes R. F., Wielebinski R., 1999, , https://ui.adsabs.harvard.edu/abs/1999A&A...348..405H 348, 405

  49. [57]

    R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357

    Harris C. R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357

  50. [58]

    F., Schinnerer E., Nasiri S., 2022, @doi [ ] 10.1093/mnras/stab3202 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510...11H 510, 11

    Hassani H., Tabatabaei F., Hughes A., Chastenet J., McLeod A. F., Schinnerer E., Nasiri S., 2022, @doi [ ] 10.1093/mnras/stab3202 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510...11H 510, 11

  51. [59]

    M., Melioli C., eds, Astrophysics and Space Science Library Vol

    Haverkorn M., 2015, in Lazarian A., de Gouveia Dal Pino E. M., Melioli C., eds, Astrophysics and Space Science Library Vol. 407, Magnetic Fields in Diffuse Media. Springer-Verlag, Berlin, p. 483

  52. [60]

    R., 2013, @doi [ ] 10.1007/s11214-013-0014-6 , https://ui.adsabs.harvard.edu/abs/2013SSRv..178..483H 178, 483

    Haverkorn M., Spangler S. R., 2013, @doi [ ] 10.1007/s11214-013-0014-6 , https://ui.adsabs.harvard.edu/abs/2013SSRv..178..483H 178, 483

  53. [61]

    C., Gaensler B

    Haverkorn M., Brown J. C., Gaensler B. M., McClure-Griffiths N. M., 2008, @doi [ ] 10.1086/587165 , http://adsabs.harvard.edu/abs/2008ApJ...680..362H 680, 362

  54. [62]

    W., et al., 2021, @doi [ ] 10.1017/pasa.2021.1 , https://ui.adsabs.harvard.edu/abs/2021PASA...38....9H 38, e009

    Hotan A. W., et al., 2021, @doi [ ] 10.1017/pasa.2021.1 , https://ui.adsabs.harvard.edu/abs/2021PASA...38....9H 38, e009

  55. [63]

    G., Han J

    Hou L. G., Han J. L., 2015, @doi [ ] 10.1093/mnras/stv1904 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454..626H 454, 626

  56. [64]

    H., Vaillancourt J

    Houde M., Fletcher A., Beck R., Hildebrand R. H., Vaillancourt J. E., Stil J. M., 2013, @doi [ ] 10.1088/0004-637X/766/1/49 , https://ui.adsabs.harvard.edu/abs/2013ApJ...766...49H 766, 49

  57. [65]

    Hovatta T., O'Sullivan S., Mart \' -Vidal I., Savolainen T., Tchekhovskoy A., 2019, @doi [ ] 10.1051/0004-6361/201832587 , https://ui.adsabs.harvard.edu/abs/2019A&A...623A.111H 623, A111

  58. [66]

    D., 2007, @doi [Computing in Science & Engineering] 10.1109/MCSE.2007.55 , 9, 90

    Hunter J. D., 2007, @doi [Computing in Science & Engineering] 10.1109/MCSE.2007.55 , 9, 90

  59. [67]

    Hutschenreuter S., et al., 2022, @doi [ ] 10.1051/0004-6361/202140486 , https://ui.adsabs.harvard.edu/abs/2022A&A...657A..43H 657, A43

  60. [68]

    R., Leahy J

    Jaffe T. R., Leahy J. P., Banday A. J., Leach S. M., Lowe S. R., Wilkinson A., 2010, @doi [ ] 10.1111/j.1365-2966.2009.15745.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.401.1013J 401, 1013

  61. [69]

    R., 2017, @doi [ ] 10.3847/1538-3881/aa77f8 , http://adsabs.harvard.edu/abs/2017AJ....154...56J 154, 56

    Jagannathan P., Bhatnagar S., Rau U., Taylor A. R., 2017, @doi [ ] 10.3847/1538-3881/aa77f8 , http://adsabs.harvard.edu/abs/2017AJ....154...56J 154, 56

  62. [70]

    R., 2012a, @doi [ ] 10.1088/0004-637X/757/1/14 , http://adsabs.harvard.edu/abs/2012ApJ...757...14J 757, 14

    Jansson R., Farrar G. R., 2012a, @doi [ ] 10.1088/0004-637X/757/1/14 , http://adsabs.harvard.edu/abs/2012ApJ...757...14J 757, 14

  63. [71]

    R., 2012b, @doi [ ] 10.1088/2041-8205/761/1/L11 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761L..11J 761, L11

    Jansson R., Farrar G. R., 2012b, @doi [ ] 10.1088/2041-8205/761/1/L11 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761L..11J 761, L11

  64. [72]

    S., 2023, @doi [ ] 10.3847/1538-4357/acb99b , https://ui.adsabs.harvard.edu/abs/2023ApJ...945...36K 945, 36

    Khademi M., Nasiri S., Tabatabaei F. S., 2023, @doi [ ] 10.3847/1538-4357/acb99b , https://ui.adsabs.harvard.edu/abs/2023ApJ...945...36K 945, 36

  65. [73]

    Kierdorf M., et al., 2020, @doi [ ] 10.1051/0004-6361/202037847 , https://ui.adsabs.harvard.edu/abs/2020A&A...642A.118K 642, A118

  66. [74]

    R., Federrath C., 2019, @doi [Frontiers in Astronomy and Space Sciences] 10.3389/fspas.2019.00007 , https://ui.adsabs.harvard.edu/abs/2019FrASS...6....7K 6, 7

    Krumholz M. R., Federrath C., 2019, @doi [Frontiers in Astronomy and Space Sciences] 10.3389/fspas.2019.00007 , https://ui.adsabs.harvard.edu/abs/2019FrASS...6....7K 6, 7

  67. [75]

    Lacy M., et al., 2020, @doi [ ] 10.1088/1538-3873/ab63eb , https://ui.adsabs.harvard.edu/abs/2020PASP..132c5001L 132, 035001

  68. [76]

    A., 1980, @doi [ ] 10.1093/mnras/193.3.439 , https://ui.adsabs.harvard.edu/abs/1980MNRAS.193..439L 193, 439

    Laing R. A., 1980, @doi [ ] 10.1093/mnras/193.3.439 , https://ui.adsabs.harvard.edu/abs/1980MNRAS.193..439L 193, 439

  69. [77]

    Liu Z., Cui W., Liu C., Huang Y., Zhao G., Zhang B., 2019, @doi [ ] 10.3847/1538-4365/ab0a0d , https://ui.adsabs.harvard.edu/abs/2019ApJS..241...32L 241, 32

  70. [78]

    Liu M., et al., 2021, @doi [ ] 10.1051/0004-6361/202039615 , https://ui.adsabs.harvard.edu/abs/2021A&A...650A..14L 650, A14

  71. [79]

    D., McClure-Griffiths N

    Livingston J. D., McClure-Griffiths N. M., Gaensler B. M., Seta A., Alger M. J., 2021, @doi [ ] 10.1093/mnras/stab253 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.3814L 502, 3814

  72. [80]

    D., McClure-Griffiths N

    Livingston J. D., McClure-Griffiths N. M., Mao S. A., Ma Y. K., Gaensler B. M., Heald G., Seta A., 2022, @doi [ ] 10.1093/mnras/stab3375 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510..260L 510, 260

  73. [81]

    K., Mao S

    Ma Y. K., Mao S. A., Stil J., Basu A., West J., Heiles C., Hill A. S., Betti S. K., 2019a, @doi [ ] 10.1093/mnras/stz1325 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3432M 487, 3432

  74. [82]

    K., Mao S

    Ma Y. K., Mao S. A., Stil J., Basu A., West J., Heiles C., Hill A. S., Betti S. K., 2019b, @doi [ ] 10.1093/mnras/stz1328 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3454M 487, 3454

  75. [83]

    K., Mao S

    Ma Y. K., Mao S. A., Ordog A., Brown J. C., 2020, @doi [ ] 10.1093/mnras/staa2105 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.3097M 497, 3097

  76. [84]

    S., 2004, @doi [Reviews of Modern Physics] 10.1103/RevModPhys.76.125 , http://adsabs.harvard.edu/abs/2004RvMP...76..125M 76, 125

    Mac Low M.-M., Klessen R. S., 2004, @doi [Reviews of Modern Physics] 10.1103/RevModPhys.76.125 , http://adsabs.harvard.edu/abs/2004RvMP...76..125M 76, 125

  77. [85]

    Mackey J., Green S., Moutzouri M., 2020, in Journal of Physics Conference Series. IOP, p. 012012, @doi 10.1088/1742-6596/1620/1/012012

  78. [86]

    A., et al., 2014, @doi [arXiv e-prints] 10.48550/arXiv.1401.1875 , https://ui.adsabs.harvard.edu/abs/2014arXiv1401.1875M p

    Mao S. A., et al., 2014, @doi [arXiv e-prints] 10.48550/arXiv.1401.1875 , https://ui.adsabs.harvard.edu/abs/2014arXiv1401.1875M p. arXiv:1401.1875

  79. [87]

    A., Zweibel E., Fletcher A., Ott J., Tabatabaei F., 2015, @doi [ ] 10.1088/0004-637X/800/2/92 , https://ui.adsabs.harvard.edu/abs/2015ApJ...800...92M 800, 92

    Mao S. A., Zweibel E., Fletcher A., Ott J., Tabatabaei F., 2015, @doi [ ] 10.1088/0004-637X/800/2/92 , https://ui.adsabs.harvard.edu/abs/2015ApJ...800...92M 800, 92

  80. [88]

    A., et al., 2017, @doi [Nature Astronomy] 10.1038/s41550-017-0218-x , http://adsabs.harvard.edu/abs/2017NatAs...1..621M 1, 621

    Mao S. A., et al., 2017, @doi [Nature Astronomy] 10.1038/s41550-017-0218-x , http://adsabs.harvard.edu/abs/2017NatAs...1..621M 1, 621

  81. [89]

    McConnell D., et al., 2020, @doi [ ] 10.1017/pasa.2020.41 , https://ui.adsabs.harvard.edu/abs/2020PASA...37...48M 37, e048

  82. [90]

    P., Waters B., Schiebel D., Young W., Golap K., 2007, in Shaw R

    McMullin J. P., Waters B., Schiebel D., Young W., Golap K., 2007, in Shaw R. A., Hill F., Bell D. J., eds, ASP Conf. Ser. Vol. 376, Astronomical Data Analysis Software and Systems XVI. ASP, San Francisco, CA, p. 127

  83. [91]

    D., Beck R., Heald G

    Mulcahy D. D., Beck R., Heald G. H., 2017, @doi [ ] 10.1051/0004-6361/201629907 , https://ui.adsabs.harvard.edu/abs/2017A&A...600A...6M 600, A6

  84. [92]

    Nakanishi H., Sofue Y., 2016, @doi [ ] 10.1093/pasj/psv108 , https://ui.adsabs.harvard.edu/abs/2016PASJ...68....5N 68, 5

  85. [93]

    A., Ferrara A., 1996, @doi [ ] 10.1086/177603 , http://adsabs.harvard.edu/abs/1996ApJ...467..280N 467, 280

    Norman C. A., Ferrara A., 1996, @doi [ ] 10.1086/177603 , http://adsabs.harvard.edu/abs/1996ApJ...467..280N 467, 280

  86. [94]

    Ntormousi E., Tassis K., Del Sordo F., Fragkoudi F., Pakmor R., 2020, @doi [ ] 10.1051/0004-6361/202037835 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A.165N 641, A165

  87. [95]

    P., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20554.x , http://adsabs.harvard.edu/abs/2012MNRAS.421.3300O 421, 3300

    O'Sullivan S. P., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20554.x , http://adsabs.harvard.edu/abs/2012MNRAS.421.3300O 421, 3300

  88. [96]

    P., Purcell C

    O'Sullivan S. P., Purcell C. R., Anderson C. S., Farnes J. S., Sun X. H., Gaensler B. M., 2017, @doi [ ] 10.1093/mnras/stx1133 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.469.4034O 469, 4034

  89. [97]

    Oberhelman L., Van Eck C., McClure-Griffiths N., Vanderwoude S., 2024, Technical Report 71, Diffuse Emission Subtraction for POSSUM Survey. POSSUM

  90. [98]

    Offner S. S. R., Arce H. G., 2015, @doi [ ] 10.1088/0004-637X/811/2/146 , https://ui.adsabs.harvard.edu/abs/2015ApJ...811..146O 811, 146

  91. [99]

    C., Kothes R., Landecker T

    Ordog A., Brown J. C., Kothes R., Landecker T. L., 2017, @doi [ ] 10.1051/0004-6361/201730740 , http://adsabs.harvard.edu/abs/2017A\

  92. [100]

    V., et al., 2023, @doi [ ] 10.1093/mnras/stad1900 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.1291P 524, 1291

    Padmanabh P. V., et al., 2023, @doi [ ] 10.1093/mnras/stad1900 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.1291P 524, 1291

  93. [101]

    Pakmor R., Marinacci F., Springel V., 2014, @doi [ ] 10.1088/2041-8205/783/1/L20 , https://ui.adsabs.harvard.edu/abs/2014ApJ...783L..20P 783, L20

  94. [102]

    Pasetto A., Carrasco-Gonz \'a lez C., O'Sullivan S., Basu A., Bruni G., Kraus A., Curiel S., Mack K.-H., 2018, @doi [ ] 10.1051/0004-6361/201731804 , https://ui.adsabs.harvard.edu/abs/2018A&A...613A..74P 613, A74

  95. [103]

    R., Van Eck C

    Purcell C. R., Van Eck C. L., West J., Sun X. H., Gaensler B. M., 2020, RM-Tools: Rotation measure (RM) synthesis and Stokes QU-fitting , Astrophysics Source Code Library, record ascl:2005.003 ( @eprint ascl 2005.003 )

  96. [104]

    A., Deane R., Sridhar S

    Ranchod S., Mao S. A., Deane R., Sridhar S. S., Damas-Segovia A., Livingston J. D., Ma Y. K., 2024, @doi [ ] 10.1051/0004-6361/202348993 , https://ui.adsabs.harvard.edu/abs/2024A&A...686A.104R 686, A104

  97. [105]

    C., 2000, @doi [ ] 10.1086/301421 , https://ui.adsabs.harvard.edu/abs/2000AJ....120..314R 120, 314

    Reed B. C., 2000, @doi [ ] 10.1086/301421 , https://ui.adsabs.harvard.edu/abs/2000AJ....120..314R 120, 314

  98. [106]

    C., 2003, @doi [ ] 10.1086/374771 , https://ui.adsabs.harvard.edu/abs/2003AJ....125.2531R 125, 2531

    Reed B. C., 2003, @doi [ ] 10.1086/374771 , https://ui.adsabs.harvard.edu/abs/2003AJ....125.2531R 125, 2531

  99. [107]

    (Springer-Verlag Berlin Heidelberg)

    Ruzmaikin A., Sokolov D., Shukurov A., 1988, Magnetic Fields of Galaxies . (Springer-Verlag Berlin Heidelberg)

  100. [108]

    Schnitzeler D. H. F. M., 2018, @doi [ ] 10.1093/mnras/stx2754 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474..300S 474, 300

  101. [109]

    Seta A., Federrath C., 2022, @doi [ ] 10.1093/mnras/stac1400 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514..957S 514, 957

  102. [110]

    Seta A., Federrath C., 2024, @doi [ ] 10.1093/mnras/stae1935 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.tmp.1898S

  103. [111]

    S., Bushby P

    Seta A., Shukurov A., Wood T. S., Bushby P. J., Snodin A. P., 2018, @doi [ ] 10.1093/mnras/stx2606 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473.4544S 473, 4544

  104. [112]

    D., McClure-Griffiths N

    Seta A., Federrath C., Livingston J. D., McClure-Griffiths N. M., 2023, @doi [ ] 10.1093/mnras/stac2972 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518..919S 518, 919

  105. [113]

    Shanahan R., et al., 2019, @doi [ ] 10.3847/2041-8213/ab58d4 , https://ui.adsabs.harvard.edu/abs/2019ApJ...887L...7S 887, L7

  106. [114]

    H., Cordes J

    Simonetti J. H., Cordes J. M., Spangler S. R., 1984, @doi [ ] 10.1086/162391 , https://ui.adsabs.harvard.edu/abs/1984ApJ...284..126S 284, 126

  107. [115]

    V., eds, American Institute of Physics Conference Series Vol

    Skilling J., 2004, in Fischer R., Preuss R., Toussaint U. V., eds, American Institute of Physics Conference Series Vol. 735, Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 24th International Workshop on Bayesian Inference and Maximum Entropy Methods...

  108. [116]

    D., Bykov A

    Sokoloff D. D., Bykov A. A., Shukurov A., Berkhuijsen E. M., Beck R., Poezd A. D., 1998, @doi [ ] 10.1046/j.1365-8711.1998.01782.x , https://ui.adsabs.harvard.edu/abs/1998MNRAS.299..189S 299, 189

  109. [117]

    S., Gallagher III J

    Sparke L. S., Gallagher III J. S., 2006, Galaxies in the Universe . (Cambridge Univ.\ Press, Cambridge), @doi 10.2277/0521855934

  110. [118]

    M., Taylor A

    Stil J. M., Taylor A. R., 2007, @doi [ ] 10.1086/519791 , https://ui.adsabs.harvard.edu/abs/2007ApJ...663L..21S 663, L21

  111. [119]

    M., Taylor A

    Stil J. M., Taylor A. R., Sunstrum C., 2011, @doi [ ] 10.1088/0004-637X/726/1/4 , http://adsabs.harvard.edu/abs/2011ApJ...726....4S 726, 4

  112. [120]

    H., et al., 2015, @doi [ ] 10.1088/0004-6256/149/2/60 , https://ui.adsabs.harvard.edu/abs/2015AJ....149...60S 149, 60

    Sun X. H., et al., 2015, @doi [ ] 10.1088/0004-6256/149/2/60 , https://ui.adsabs.harvard.edu/abs/2015AJ....149...60S 149, 60

  113. [121]

    Takamura M., et al., 2023, @doi [ ] 10.3847/1538-4357/acd9a8 , https://ui.adsabs.harvard.edu/abs/2023ApJ...952...47T 952, 47

  114. [122]

    Thomson A. J. M., et al., 2019, @doi [ ] 10.1093/mnras/stz1438 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.4751T 487, 4751

  115. [123]

    Thomson A. J. M., et al., 2023, @doi [ ] 10.1017/pasa.2023.38 , https://ui.adsabs.harvard.edu/abs/2023PASA...40...40T 40, e040

  116. [124]

    P., 2022, @doi [ ] 10.1016/j.newast.2022.101896 , https://ui.adsabs.harvard.edu/abs/2022NewA...9701896V 97, 101896

    Vall \'e e J. P., 2022, @doi [ ] 10.1016/j.newast.2022.101896 , https://ui.adsabs.harvard.edu/abs/2022NewA...9701896V 97, 101896

  117. [125]

    L., et al., 2011, @doi [ ] 10.1088/0004-637X/728/2/97 , http://adsabs.harvard.edu/abs/2011ApJ...728...97V 728, 97

    Van Eck C. L., et al., 2011, @doi [ ] 10.1088/0004-637X/728/2/97 , http://adsabs.harvard.edu/abs/2011ApJ...728...97V 728, 97

  118. [126]

    L., et al., 2023, @doi [ ] 10.3847/1538-4365/acda24 , https://ui.adsabs.harvard.edu/abs/2023ApJS..267...28V 267, 28

    Van Eck C. L., et al., 2023, @doi [ ] 10.3847/1538-4365/acda24 , https://ui.adsabs.harvard.edu/abs/2023ApJS..267...28V 267, 28

  119. [127]

    L., 2009, Python 3 Reference Manual

    Van Rossum G., Drake F. L., 2009, Python 3 Reference Manual. CreateSpace, Scotts Valley, CA

  120. [128]

    Virtanen P., et al., 2020, @doi [Nature Methods] 10.1038/s41592-019-0686-2 , https://rdcu.be/b08Wh 17, 261

  121. [129]

    Wolleben M., et al., 2021, @doi [ ] 10.3847/1538-3881/abf7c1 , https://ui.adsabs.harvard.edu/abs/2021AJ....162...35W 162, 35

  122. [130]

    M., Manchester R

    Yao J. M., Manchester R. N., Wang N., 2017, @doi [ ] 10.3847/1538-4357/835/1/29 , https://ui.adsabs.harvard.edu/\#abs/2017ApJ...835...29Y 835, 29

  123. [131]

    T., Frail D

    de Gasperin F., Intema H. T., Frail D. A., 2018, @doi [ ] 10.1093/mnras/stx3125 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.5008D 474, 5008

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.