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arxiv: 2605.25325 · v1 · pith:BKA5SX7Bnew · submitted 2026-05-25 · 🌌 astro-ph.SR

Signs of Sulphur fractionation under high magnetic field strength

Dominik Orlovskij , Andy S. H. To , David M. Long This is my paper

Pith reviewed 2026-06-29 21:02 UTC · model grok-4.3

classification 🌌 astro-ph.SR
keywords solar coronaFIP fractionationsulphurmagnetic field strengthHinode EIScoronal loopselemental abundancesDEM inversion
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The pith

Sulphur fractionation decreases above 150 G in coronal loops, independent of length.

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

The paper quantifies how sulphur's first ionisation potential bias varies with properties of coronal loops derived from potential field source surface models. It processes nine Hinode/EIS raster observations through four diagnostic line pairs and regularised differential emission measure inversion to extract FIP biases. The results indicate that low-FIP abundances, including sulphur, fall relative to high-FIP argon once mean field strength exceeds roughly 150 G, while showing no relation to loop length. A sympathetic reader would see this as direct evidence that magnetic field strength, rather than geometry alone, controls the fractionation process in the solar atmosphere.

Core claim

Analysis of Hinode/EIS observations using four diagnostic line pairs (Si X/S X, S XI/Ar XI, Ca XIV/Ar XIV, Fe XVI/S XIII) and regularised DEM inversion shows that abundances of low-FIP elements, including sulphur, decrease above approximately 150 G relative to the high-FIP element Ar, while showing no dependence on loop length. This provides evidence that FIP fractionation is modulated by mean magnetic field strength of coronal loops.

What carries the argument

Regularised differential emission measure inversion from four diagnostic line pairs to derive FIP bias versus PFSS-derived mean magnetic field strength and loop length.

If this is right

  • FIP fractionation depends on mean magnetic field strength of coronal loops rather than on loop length.
  • Sulphur behaves as a high-FIP element once field strength exceeds approximately 150 G.
  • Variable sulphur behaviour observed during flares and magnetic restructuring may trace changes in local field strength.
  • The modulation supplies a mechanism that can reconcile remote-sensing and in-situ abundance measurements.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Coronal abundance models could be extended to predict elemental ratios directly from photospheric magnetic field maps.
  • The 150 G threshold offers a testable target for three-dimensional MHD simulations that include ion-neutral separation.
  • Future multi-instrument campaigns during active region evolution could check whether the same field-strength dependence appears in other elements near the FIP boundary.

Load-bearing premise

The diagnostic line pairs and regularised DEM inversion isolate true FIP bias without significant contamination from temperature structure, density, or calibration uncertainties.

What would settle it

Repeating the full analysis on the same or similar EIS rasters with an independent DEM method or different instrument that yields no abundance drop above 150 G would falsify the claim.

Figures

Figures reproduced from arXiv: 2605.25325 by Andy S. H. To, David M. Long, Dominik Orlovskij.

Figure 1
Figure 1. Figure 1: Overview of AR 11967 on 2014-02-05T10:41. Left to right: HMI line-of-sight magnetogram, AIA 193 Å image, and AIA 193 Å image with PFSS-extrapolated field lines overlaid. The EIS field of view (FOV) is outlined in blue. Cyan contours in the middle panel mark EIS Fe XII 195.12 Doppler velocity (≤ −10 km s−1 ) within the EIS FOV. Closed PFSS field lines are shown in white and open field lines in green. magnet… view at source ↗
Figure 2
Figure 2. Figure 2: Sample FIP bias maps for the four diagnostic line pairs, derived from DEM-corrected intensities during nine EIS observations in February 2014. Section A shows the filtered maps with both χ 2 and intensity masking applied for each observation date shown: 2014-02-01T10:50, 2014-02-02T10:25. Section B shows the unfiltered map for 2014-02- 01T10:50. The full analysis consists of 9 rasters spanning from 2014-02… view at source ↗
Figure 3
Figure 3. Figure 3: Elemental abundance versus magnetic loop length for all nine rasters combined, shown separately for diagnostic line pair. Blue points represent closed field lines; green dashed line indicates the median abundance per bin, calculated using a 5,000 km binning of loop length; blue solid line shows the corresponding mean; gray shaded region indicates the 25th – 75th percentile range. A logarithmic fit is plott… view at source ↗
Figure 4
Figure 4. Figure 4: Elemental abundance versus mean magnetic field strength along PFSS-traced field lines for all nine rasters combined, shown separately for each diagnostic line pair. The colour of dots indicates loop length, from shorter loops in blue to longer loops in yellow; green dashed line indicates the median abundance per bin, calculated using a 20 G binning of magnetic field strength; the blue dashed line shows the… view at source ↗
Figure 5
Figure 5. Figure 5: Example of the Solar-Y mask used for the AR periphery analysis in 6 and 7. Left: cleaned Fe/S composition map before applying the mask. Right: the same map after excluding the central band −200” < Y < −100”. below ∼200 G does not appear to continue at higher field strengths, but they did not establish a systematic decrease. An interesting finding is that the FIP bias/magnetic field strength slope between e… view at source ↗
Figure 6
Figure 6. Figure 6: Same as [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Same as [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Emissivity and ratio curves for the four diagnostic line pairs used in this study: Si X 258.37 Å / S X 264.23 Å, S XI 188.68 Å / Ar XI 188.81 Å, Ca XIV 193.87 Å / Ar XIV 194.40 Å, and Fe XVI 262.98 Å / S XIII 256.69 Å. The solid curves show emissivity versus temperature, and the dashed curves show emissivity ratios at three electron densities. Pairs with overlapping emissivity peaks and stable ratio curves… view at source ↗
Figure 9
Figure 9. Figure 9: Intensity maps for the Ca XIV, Fe XVI, Si X, S XI, Ar XIV, S XIII, S X, and Ar XI diagnostic lines, derived from raw Hinode/EIS observations on 2014-02-01T10:50. These maps were used for emission structure analysis and for intensity-based filtering [PITH_FULL_IMAGE:figures/full_fig_p013_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Distribution of valid closed field line pixels by mean magnetic field strength for all nine rasters combined, shown separately for each diagnostic line pair. The vertical line marks the 150 G threshold used for the two-slope fits in [PITH_FULL_IMAGE:figures/full_fig_p014_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: AIA 193 Å context images for all nine EIS rasters. For each raster time (left to right): AIA 193 Å image with Fe XII 195.12 Doppler upflow contours (cyan; ≤ −10 km s−1 ) and the EIS FOV (blue dashed box), and the corresponding AIA image with the PFSS field lines overlaid. Closed field lines are white, open field lines green. University and for establishing the collaboration with the European Space Agency.… view at source ↗
Figure 12
Figure 12. Figure 12: Fe/S FIP bias maps for all nine EIS rasters. For each raster time (left to right): the Fe/S map with Fe XII 195.12 Doppler upflow contours (cyan; ≤ −10 km s−1 ), and the corresponding map with the PFSS field lines overlaid. Closed field lines are blue, open field lines green [PITH_FULL_IMAGE:figures/full_fig_p016_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: AIA 193 Å context for the four large-FOV rasters used in the mean magnetic field analysis. The top row shows all traced PFSS field lines, with closed field lines of mean magnetic filed ≥ 150 G highlighted in cyan. The bottom row shows only the closed PFSS field lines with mean magnetic field ≥ 150 G. Open field lines are shown in green, other closed field lines in white, and the EIS FOV outlined in blue. … view at source ↗
read the original abstract

Sulphur, with a first ionisation potential (FIP) of 10.36 eV, lies at the boundary between low- and high-FIP elements, making it particularly sensitive to fractionation processes in the solar atmosphere. Sulphur exhibits variable behaviour across solar environments, with coronal remote sensing studies often observing it as a high-FIP element while in-situ measurements sometimes detect low-FIP-like enhancement. Sulphur also exhibits variable behaviour during flares and magnetic restructuring. To understand sulphur's variations, we quantify how sulphur's FIP bias depends on potential field source surface (PFSS)-derived loop properties. We analyse nine Hinode/EUV Imaging Spectrometer (EIS) raster observations using four diagnostic line pairs (Si X 258.37 A / S X 264.23 A, S XI 188.68 A / Ar XI 188.81 A, Ca XIV 193.87 A / Ar XIV 194.40 A, and Fe XVI 262.98 A / S XIII 256.69 A), with FIP biases derived using differential emission measures (DEM) calculated via regularised inversion. Our results show that abundances of low-FIP elements, including sulphur, decrease above approximately 150 G relative to the high-FIP element Ar, while showing no dependence on loop length. This provides evidence that FIP fractionation is modulated by mean magnetic field strength of coronal loops.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript analyzes nine Hinode/EIS raster observations of coronal loops using four diagnostic line pairs (Si X 258.37 Å/S X 264.23 Å, S XI 188.68 Å/Ar XI 188.81 Å, Ca XIV 193.87 Å/Ar XIV 194.40 Å, Fe XVI 262.98 Å/S XIII 256.69 Å) and regularised DEM inversion to derive FIP biases. It reports that low-FIP element abundances (including sulphur) decrease relative to high-FIP Ar above a PFSS-derived mean magnetic field strength of ~150 G, with no dependence on loop length, and interprets this as evidence that FIP fractionation is modulated by mean loop magnetic field strength.

Significance. If the central correlation holds after validation, the result would be significant for solar atmospheric physics: it supplies an observational link between the FIP effect and a measurable physical parameter (mean B), helps explain sulphur's variable fractionation across remote-sensing and in-situ data, and constrains fractionation models. The use of multiple independent line-pair diagnostics and PFSS models is a methodological strength when properly error-checked.

major comments (2)
  1. [Methods (diagnostics and DEM section)] Methods (diagnostics and DEM section): the abstract and available description supply no error bars on the derived FIP biases, no data-exclusion criteria for the nine rasters, and no validation of the four line-pair diagnostics against alternative DEM methods or density/temperature sensitivity tests; these steps are load-bearing for the claim that the reported trend isolates true FIP bias rather than temperature structure or calibration effects.
  2. [Results (magnetic-field dependence)] Results (magnetic-field dependence): the 150 G threshold and absence of length dependence rest on PFSS mean field strengths; no cross-check against NLFFF extrapolations, vector-field data, or direct coronal B proxies is described, yet PFSS is known to underestimate B by 30-50 % in active-region loops, which could shift the reported threshold and binning.
minor comments (1)
  1. [Abstract] Abstract: the number of individual loops per raster and the statistical significance or scatter of the abundance trend versus B should be stated explicitly.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments on our manuscript. We address each major comment below and outline the revisions we will make.

read point-by-point responses

  1. Referee: [Methods (diagnostics and DEM section)] Methods (diagnostics and DEM section): the abstract and available description supply no error bars on the derived FIP biases, no data-exclusion criteria for the nine rasters, and no validation of the four line-pair diagnostics against alternative DEM methods or density/temperature sensitivity tests; these steps are load-bearing for the claim that the reported trend isolates true FIP bias rather than temperature structure or calibration effects.

    Authors: We agree that the current manuscript lacks explicit error bars, data-exclusion criteria, and validation tests. In the revised version we will (i) propagate uncertainties from line intensities and the regularised DEM inversion to report error bars on all FIP-bias values, (ii) state the selection criteria applied to the nine EIS rasters, and (iii) add a dedicated subsection presenting density- and temperature-sensitivity tests together with a comparison against an alternative MCMC DEM method. These additions will confirm that the reported magnetic-field trend is not an artefact of temperature structure or calibration. revision: yes

  2. Referee: [Results (magnetic-field dependence)] Results (magnetic-field dependence): the 150 G threshold and absence of length dependence rest on PFSS mean field strengths; no cross-check against NLFFF extrapolations, vector-field data, or direct coronal B proxies is described, yet PFSS is known to underestimate B by 30-50 % in active-region loops, which could shift the reported threshold and binning.

    Authors: PFSS models are known to underestimate absolute field strengths, and we will add an explicit discussion of this limitation in the revised manuscript. Nevertheless, PFSS supplies a homogeneous, reproducible estimate of the mean loop field for all nine observations, preserving the relative ordering and the existence of a transition near 150 G. We therefore maintain that the observed correlation with FIP bias remains valid even if the absolute threshold shifts. Direct cross-checks with NLFFF extrapolations or vector-field data are not feasible for the full sample because co-temporal high-quality vector magnetograms are unavailable for several of the rasters; we will state this limitation clearly. revision: partial

Circularity Check

0 steps flagged

No circularity: observational correlation from independent spectra and models

full rationale

The paper reports an empirical correlation between FIP biases (derived from EIS line ratios via regularised DEM inversion) and PFSS-computed mean loop field strengths across nine rasters. No derivation, equation, or self-citation reduces the reported abundance trends or the 150 G threshold to a fitted parameter or input by construction. The central claim rests on external data products (EIS spectra, PFSS extrapolations) whose validity is independent of the target result. This matches the default expectation of a non-circular observational study.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The work is observational and relies on standard solar-physics background assumptions rather than new free parameters or invented entities.

axioms (2)
  • domain assumption The chosen spectral line pairs and regularised DEM inversion yield unbiased FIP ratios
    Invoked when deriving FIP biases from the four diagnostic pairs listed in the abstract.
  • domain assumption PFSS models accurately represent the mean magnetic field strength of the observed coronal loops
    Used to bin the FIP bias results by field strength.

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discussion (0)

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Reference graph

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