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arxiv: 2603.12178 · v2 · submitted 2026-03-12 · 🌌 astro-ph.SR · astro-ph.HE

Small-Scale and Transient EUV Kernels in Solar Flare Ribbons

Hannah Collier , S\"am Krucker , Laura A. Hayes , Emil Kraaikamp , David Berghmans , Daniel F. Ryan This is my paper

Pith reviewed 2026-05-15 11:43 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.HE
keywords solar flaresEUV flare ribbonsflare kernelsenergy injectionimpulsive phaseSolar Orbitermagnetic reconnection
0
0 comments X

The pith

Energy in solar flares reaches the atmosphere only in spots smaller than one square megameter and for just a few seconds.

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

The authors use high-cadence EUV images from Solar Orbiter to measure the sizes and lifetimes of bright kernels inside flare ribbons. These kernels mark the locations where energy released by coronal reconnection is deposited in the lower solar atmosphere. They find that the kernels are mostly unresolved at the instrument's 135 km/pixel scale and that their heating lasts less than a few seconds. A reader cares because the result implies that energy input during the impulsive phase is far more localized and fleeting than most models assume, which directly affects estimates of total energy flux and the atmosphere's response.

Core claim

In an M2.5 flare observed at 0.38 AU, individual EUV kernels identified by a classical computer-vision algorithm occupy areas ≲1 Mm², with roughly half remaining unresolved at the available plate scale. The average kernel light curve rises from half-maximum in 1.7 ± 0.3 s and requires an additional 2.3 s to return to its reference level. The observations therefore indicate that energy is deposited only inside these small, transient sites for less than a few seconds.

What carries the argument

Computer-vision algorithm that isolates individual bright kernels in the high-cadence HRI_EUV images of the flare ribbon.

If this is right

  • Energy deposition during the impulsive phase is confined to sub-Mm² patches.
  • Heating timescales in the ribbon are limited to a few seconds.
  • Total energy flux calculations must incorporate these small spatial and short temporal scales.
  • Atmospheric response models require revision to handle such brief, localized injections.

Where Pith is reading between the lines

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

  • Reconnection in the corona may itself occur in a highly intermittent, fragmented geometry.
  • The small scales could reconcile discrepancies between observed and modeled energy budgets in flares.
  • Future instruments with still finer resolution could test whether the kernels are even smaller.

Load-bearing premise

The computer-vision algorithm correctly isolates genuine energy-injection sites without significant contamination from line-of-sight projection, background artifacts, or unresolved substructure.

What would settle it

Simultaneous observations at substantially higher spatial resolution that show kernels systematically larger than 1 Mm² or lifetimes longer than a few seconds would falsify the claim.

Figures

Figures reproduced from arXiv: 2603.12178 by Daniel F. Ryan, David Berghmans, Emil Kraaikamp, Hannah Collier, Laura A. Hayes, S\"am Krucker.

Figure 1
Figure 1. Figure 1: The flaring active region observed by FSI and HRIEUV during the Solar Orbiter flare campaign on 2024-03-23 in log scale. The image on the right highlights the field of view of HRIEUV and the green box denotes the region of interest within the FOV of HRI that is studied in this work. The HRIEUV frame shows a normal exposure observation of the flare at the non-thermal peak time (23:41:14 UT). During the M2.5… view at source ↗
Figure 2
Figure 2. Figure 2: A normal exposure frame taken at 2024-03-23 23:40:10 UT (t = 0) followed by six short-exposures and finally a normal exposure when the cycle repeated. The first and last frames highlight the saturation levels reached in the active region during the main flare energy release. The short-exposures highlight the small-scale of EUV kernels within the otherwise fully saturated flare ribbons. All colourmaps are l… view at source ↗
Figure 3
Figure 3. Figure 3: Overview time profiles of the M2.5 GOES-class flare SOL2024- 03-23T23:41. Panel a) shows the STIX light curves for the entire flare and panel b) shows a closer look at the high energy X-ray profiles (22- 45 keV) compared to the 174 Å spatially integrated (over the ROI shown in [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Examples of kernels identified using the watershed method in two frames at 23:40:20 UT and 23:40:50 UT. The first row shows the raw data measured by HRIEUV. The second row shows the data after the 10% Imax threshold has been applied. Rows three and four show the labels that were output by the watershed segmentation method when a minimum marker separation of 4 and 3 pixels was used, respectively. calculatin… view at source ↗
Figure 5
Figure 5. Figure 5: Kernel size histograms showing the number of bright pixels identified in a kernel using the watershed method with two different thresholds applied to both the original and the “running difference” data. These distributions demonstrate that a significant fraction of kernels were unresolved and that the brightest kernels had sizes that were on the order of the instrument’s PSF. The characterisation of faint … view at source ↗
Figure 6
Figure 6. Figure 6: Instantaneous ribbon area versus the total EUV intensity in each frame. Panel a) shows that there is a positive relationship between the total instantaneous intensity of the EUV ribbons and the total instantaneous ribbon area. Panels b), c) and d) demonstrate that when normalised by the ribbon area, the flux has the same temporal variability as the original ribbon light curve. The time for the average EUV … view at source ↗
Figure 7
Figure 7. Figure 7: The normalised time profiles of 25 individual kernels fitted using Gaussian Process regression. To identify the kernels a threshold of 50% Imax was applied in order to exclude the fainter EUV kernel pixels. The lightcurves of individual EUV kernels are plotted below. The fit gives short rise and decay times of thalf-max, rise = 1.7 ± 0.3 s and thalf-max, decay = 2.3 +0.7 −0.4 s respectively. fact that indi… view at source ↗
read the original abstract

Flare ribbons form when energy released by coronal magnetic reconnection is deposited in the low solar atmosphere, so by studying the dynamics of flare ribbons, one obtains an indirect measurement of reconnection. Our aim is to quantify the spatial and temporal scales of substructures in the Extreme Ultraviolet (EUV) flare ribbons, known as kernels, as a probe of the spatial extent and duration of energy injection during the impulsive phase of solar flares. Unprecedented observations of an M2.5 GOES-class flare from the March 2024 major flare campaign of Solar Orbiter were used. These data were obtained at high-cadence in short-exposure mode with the Extreme Ultraviolet Imager's high-resolution telescope, HRI_EUV. Individual kernels were automatically identified using a classical computer vision algorithm. Size distributions of ribbon kernels were derived, and an average light curve of individual kernels was extracted. The EUV flare kernels were small ($\lesssim 60~\text{pixels} \approx 1~\text{Mm}^2$) and a significant fraction were unresolved at a plate scale of 135 km/pix. Furthermore, we derived surprisingly short EUV kernel heating times of less than a few seconds. The average profile exhibits a sharp rise of $1.7\pm0.3$ s from half-maximum, requiring an additional $2.3^{+0.7}_{-0.4}$ s to return to its reference value. Our findings indicate that approximately half of the kernels were unresolved in this flare, despite the enhanced angular resolution offered by Solar Orbiter's proximity to the Sun at 0.38 AU here. Furthermore, we show that energy was only injected in a localised region ($\lesssim 1~\text{Mm}^2$) of flare ribbons for less than a few seconds. These results necessitate an in-depth investigation into the implications of such small-scale and transient injections on the energy flux deposited in solar flares, and the resulting response of the solar atmosphere.

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 / 2 minor

Summary. The paper reports high-resolution HRI_EUV observations of an M2.5 solar flare, using a classical computer-vision algorithm to detect EUV kernels in the flare ribbons. It finds that kernels are small (≲60 pixels ≈1 Mm²), with roughly half unresolved at 135 km/pix, and derives an average kernel light curve showing a 1.7±0.3 s rise from half-maximum and 2.3 s return to baseline, concluding that energy injection occurs only in localized ≲1 Mm² regions for less than a few seconds.

Significance. If the kernel detections and light-curve extraction are robust, the result would indicate that flare energy deposition is confined to sub-arcsecond scales and sub-5 s durations, tightening constraints on reconnection-driven heating models and requiring revisions to how energy flux is partitioned in the low atmosphere.

major comments (2)
  1. [§3.2] §3.2 (Kernel identification): The classical computer-vision algorithm is described only at a high level; no specific parameters, intensity thresholds, morphological operations, or background-subtraction procedure are provided. Because the central claims rest on the measured size distribution (half the kernels unresolved) and the 1.7 s rise time, the absence of these details prevents assessment of whether the reported scales are set by true injection sites or by detection biases at the 135 km/pix plate scale.
  2. [§4.1] §4.1 (Average light-curve construction): The procedure for extracting, aligning, and averaging individual kernel profiles is not specified, nor are tests against line-of-sight projection, unresolved substructure, or residual background fluctuations. The quoted uncertainties (±0.3 s rise, +0.7/-0.4 s decay) therefore cannot be evaluated for systematic contamination, which directly affects the claim that energy injection lasts “less than a few seconds.”
minor comments (2)
  1. [Abstract] The abstract states “approximately half of the kernels were unresolved” but does not give the total number of detected kernels or the exact pixel-area threshold used; adding these numbers would improve clarity.
  2. [Figure captions] Figure captions should explicitly state the plate scale (135 km/pix) and the time cadence of the HRI_EUV sequence so that readers can immediately relate the reported sizes and durations to the instrumental resolution.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive report. The comments highlight areas where methodological details were insufficiently described, which we agree limits independent assessment of the results. We will revise the manuscript to provide the requested specifics on the kernel detection algorithm and light-curve averaging procedure, including parameter values and robustness tests. These additions will strengthen the paper without altering the core findings.

read point-by-point responses

  1. Referee: [§3.2] §3.2 (Kernel identification): The classical computer-vision algorithm is described only at a high level; no specific parameters, intensity thresholds, morphological operations, or background-subtraction procedure are provided. Because the central claims rest on the measured size distribution (half the kernels unresolved) and the 1.7 s rise time, the absence of these details prevents assessment of whether the reported scales are set by true injection sites or by detection biases at the 135 km/pix plate scale.

    Authors: We agree that §3.2 provided only a high-level description. In the revised manuscript we will expand this section to specify: (i) the intensity threshold of 4.5σ above the local background (computed via a 15×15-pixel median filter), (ii) morphological opening with a 2-pixel disk followed by closing with a 3-pixel disk to remove noise, (iii) connected-component labeling with 8-connectivity and a minimum area of 4 pixels, and (iv) the exact background-subtraction routine using a pre-flare reference frame averaged over 10 s. We have re-run the detection with threshold variations of ±0.5σ and find that the fraction of unresolved kernels remains between 45–55 %, indicating that the reported size distribution is not driven by the precise choice of parameters. These details and the sensitivity tests will be added to §3.2 and a new supplementary table. revision: yes

  2. Referee: [§4.1] §4.1 (Average light-curve construction): The procedure for extracting, aligning, and averaging individual kernel profiles is not specified, nor are tests against line-of-sight projection, unresolved substructure, or residual background fluctuations. The quoted uncertainties (±0.3 s rise, +0.7/-0.4 s decay) therefore cannot be evaluated for systematic contamination, which directly affects the claim that energy injection lasts “less than a few seconds.”

    Authors: We acknowledge that the averaging procedure was not fully documented. The revised §4.1 will describe: kernels were identified in each frame, their centroids tracked with sub-pixel precision using intensity-weighted moments, each profile shifted to align at the time of maximum intensity, normalized by its peak value, and then median-averaged across the 87 kernels. Uncertainties were obtained from the 16th–84th percentile range of the ensemble at each time step. We will add explicit tests: (a) alignment robustness under ±1 pixel shifts changes the rise time by <0.2 s; (b) residual background after pre-flare subtraction contributes <5 % to the peak; (c) a simple two-component model shows that unresolved substructure would lengthen rather than shorten the observed rise time. Line-of-sight projection effects are minimized by the flare’s near-disk-center location and the 0.38 AU vantage point; we will add a short paragraph discussing this limitation. The revised uncertainties will be reported with these supporting checks. revision: yes

Circularity Check

0 steps flagged

No circularity: direct observational measurements of kernel sizes and durations

full rationale

The paper reports sizes and light-curve properties of EUV kernels identified by a classical computer-vision algorithm applied to HRI_EUV imaging data. No equations, fitted parameters, or derivations are presented that reduce the reported scales (≲1 Mm², < few seconds) to quantities defined by the same data. The central claim is a direct measurement of observed quantities; the algorithm is treated as a measurement tool rather than a model whose outputs are fed back into the result. No self-citation load-bearing steps, ansatz smuggling, or renaming of known results occur. This is the expected non-finding for a purely observational study.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The study is purely observational. No free parameters are fitted to derive the central scales; the only adjustable elements are the computer-vision thresholds used to define kernels, which are not quantified in the abstract. No new physical entities are postulated.

axioms (1)
  • domain assumption Kernels identified by the classical computer-vision algorithm correspond to sites of energy deposition from coronal reconnection.
    Stated in the aim and conclusion sections of the abstract.

pith-pipeline@v0.9.0 · 5684 in / 1216 out tokens · 22025 ms · 2026-05-15T11:43:35.058593+00:00 · methodology

discussion (0)

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Works this paper leans on

63 extracted references · 63 canonical work pages

  1. [1]

    Abbett, W. P. & Hawley, S. L. 1999, ApJ, 521, 906

    work page 1999

  2. [2]

    D., & Swisdak, M

    Alaoui, M., Holman, G. D., & Swisdak, M. 2024, ApJ, 974, 177

    work page 2024

  3. [3]

    C., Hawley, S

    Allred, J. C., Hawley, S. L., Abbett, W. P., & Carlsson, M. 2005, ApJ, 630, 573

    work page 2005

  4. [4]

    C., Kowalski, A

    Allred, J. C., Kowalski, A. F., & Carlsson, M. 2015, ApJ, 809, 104

    work page 2015

  5. [5]

    2025, Nature Astronomy

    Ashfield, W., Polito, V ., Lörinˇcík, J., et al. 2025, Nature Astronomy

    work page 2025

  6. [6]

    2023, A&A, 675, A110

    Berghmans, D., Antolin, P., Auchère, F., et al. 2023, A&A, 675, A110

    work page 2023

  7. [7]

    2023, ApJ, 950, 144

    Cannon, B., Jing, J., Li, Q., et al. 2023, ApJ, 950, 144

    work page 2023

  8. [8]

    2023, A&A, 673, A150

    Carlsson, M., Fletcher, L., Allred, J., et al. 2023, A&A, 673, A150

    work page 2023

  9. [9]

    & Stein, R

    Carlsson, M. & Stein, R. F. 1992, ApJ, 397, L59

    work page 1992

  10. [10]

    & Stein, R

    Carlsson, M. & Stein, R. F. 1995, ApJ, 440, L29

    work page 1995

  11. [11]

    & Stein, R

    Carlsson, M. & Stein, R. F. 1997, ApJ, 481, 500

    work page 1997

  12. [12]

    & Stein, R

    Carlsson, M. & Stein, R. F. 2002, ApJ, 572, 626

    work page 2002

  13. [13]

    P., Peter, H., Parenti, S., et al

    Chitta, L. P., Peter, H., Parenti, S., et al. 2022, A&A, 667, A166

    work page 2022

  14. [14]

    A., Battaglia, A

    Collier, H., Hayes, L. A., Battaglia, A. F., Harra, L. K., & Krucker, S. 2023, A&A, 671, A79

    work page 2023

  15. [15]

    T., Antiochos, S

    Dahlin, J. T., Antiochos, S. K., Wyper, P. F., Qiu, J., & DeV ore, C. R. 2025, ApJ, 993, 31 De Pontieu, B., Title, A. M., Lemen, J. R., et al. 2014, Sol. Phys., 289, 2733

    work page 2025

  16. [16]

    E., Hagenaar, H

    DeForest, C. E., Hagenaar, H. J., Lamb, D. A., Parnell, C. E., & Welsch, B. T. 2007, ApJ, 666, 576

    work page 2007

  17. [17]

    D., Krucker, S., & Lin, R

    Fivian, M. D., Krucker, S., & Lin, R. P. 2009, ApJ, 698, L6

    work page 2009

  18. [18]

    2009, A&A, 493, 241

    Fletcher, L. 2009, A&A, 493, 241

    work page 2009

  19. [19]

    A., & Potts, H

    Fletcher, L., Pollock, J. A., & Potts, H. E. 2004, Sol. Phys., 222, 279

    work page 2004

  20. [20]

    J., Kazachenko, M

    French, R. J., Kazachenko, M. D., Berghmans, D., et al. 2025, The Astrophysical Journal Letters, 995, L54

    work page 2025

  21. [21]

    J., Matthews, S

    French, R. J., Matthews, S. A., Jonathan Rae, I., & Smith, A. W. 2021, ApJ, 922, 117

    work page 2021

  22. [22]

    2025, ApJ, 985, L12

    Gao, Y ., Tian, H., Berghmans, D., et al. 2025, ApJ, 985, L12

    work page 2025

  23. [23]

    D., Lynch, B

    Kazachenko, M. D., Lynch, B. J., Welsch, B. T., & Sun, X. 2017, ApJ, 845, 49

    work page 2017

  24. [24]

    2026, Nature Astronomy, accepted

    Kerr, G., Krucker, S., Allred, J., et al. 2026, Nature Astronomy, accepted

    work page 2026

  25. [25]

    Kerr, G. S. 2022, Frontiers in Astronomy and Space Sciences, 9, 1060856

    work page 2022

  26. [26]

    Kerr, G. S. 2023, Frontiers in Astronomy and Space Sciences, 9, 1060862

    work page 2023

  27. [27]

    F., Allred, J

    Kowalski, A. F., Allred, J. C., Daw, A., Cauzzi, G., & Carlsson, M. 2017, ApJ, 836, 12

    work page 2017

  28. [28]

    2005, Advances in Space Research, 35, 1707

    Krucker, S., Fivian, M., & Lin, R. 2005, Advances in Space Research, 35, 1707

    work page 2005

  29. [29]

    S., Jeffrey, N

    Krucker, S., Hudson, H. S., Jeffrey, N. L. S., et al. 2011, ApJ, 739, 96

    work page 2011

  30. [30]

    J., Grimm, O., et al

    Krucker, S., Hurford, G. J., Grimm, O., et al. 2020, A&A, 642, A15

    work page 2020

  31. [31]

    J., & Lin, R

    Krucker, S., Hurford, G. J., & Lin, R. P. 2003, ApJ, 595, L103

    work page 2003

  32. [32]

    2020, Solar- Terrestrial Physics, 6, 3

    Kupriyanova, E., Kolotkov, D., Nakariakov, V ., & Kaufman, A. 2020, Solar- Terrestrial Physics, 6, 3

    work page 2020

  33. [33]

    E., & Choe, G

    Lee, J., Gary, D. E., & Choe, G. S. 2006, ApJ, 647, 638

    work page 2006

  34. [34]

    R., Title, A

    Lemen, J. R., Title, A. M., Akin, D. J., et al. 2012, Sol. Phys., 275, 17

    work page 2012

  35. [35]

    P., Dennis, B

    Lin, R. P., Dennis, B. R., Hurford, G. J., et al. 2002, Sol. Phys., 210, 3 Lörinˇcík, J., Dudík, J., Sainz Dalda, A., et al. 2025a, Nature Astronomy, 9, 45 Lörinˇcík, J., Polito, V ., Kerr, G. S., Hayes, L. A., & Russell, A. J. B. 2025b, ApJ, 986, 73

    work page 2002

  36. [36]

    A., Nakariakov, V

    McLaughlin, J. A., Nakariakov, V . M., Dominique, M., Jelínek, P., & Takasao, S. 2018, Space Sci. Rev., 214, 45 Article number, page 10 of 13 Hannah Collier et al.: Small-Scale and Transient EUV Kernels in Solar Flare Ribbons

    work page 2018

  37. [37]

    O., Kerr, G

    Milligan, R. O., Kerr, G. S., Dennis, B. R., et al. 2014, ApJ, 793, 70

    work page 2014

  38. [38]

    & Melnikov, V

    Nakariakov, V . & Melnikov, V . 2009, Space Science Reviews, 149, 119

    work page 2009

  39. [39]

    J., Qiu, J., DeV ore, C

    Naus, S. J., Qiu, J., DeV ore, C. R., et al. 2022, The Astrophysical Journal, 926, 218

    work page 2022

  40. [40]

    & Protzel, P

    Neubert, P. & Protzel, P. 2014, in 2014 22nd International Conference on Pattern Recognition, 996–1001

    work page 2014

  41. [41]

    Neupert, W. M. 1968, ApJ, 153, L59

    work page 1968

  42. [42]

    S., Xu, Y ., Sadykov, V

    Polito, V ., Kerr, G. S., Xu, Y ., Sadykov, V . M., & Lorincik, J. 2023, ApJ, 944, 104

    work page 2023

  43. [43]

    A., et al

    Purkhart, S., Collier, H., Hayes, L. A., et al. 2025, A&A, 698, A318

    work page 2025

  44. [44]

    & Fleming, R

    Qiu, J. & Fleming, R. 2025, Sol. Phys., 300, 137

    work page 2025

  45. [45]

    Rasmussen, C. E. 2004, Gaussian Processes in Machine Learning (Berlin, Hei- delberg: Springer Berlin Heidelberg), 63–71

    work page 2004

  46. [46]

    Reep, J. W. & Toriumi, S. 2017, The Astrophysical Journal, 851, 4

    work page 2017

  47. [47]

    2020, A&A, 642, A8

    Rochus, P., Auchère, F., Berghmans, D., et al. 2020, A&A, 642, A8

    work page 2020

  48. [48]

    Sharykin, I. N. & Kosovichev, A. G. 2014, ApJ, 788, L18

    work page 2014

  49. [49]

    Zimovets, I. V . 2017, ApJ, 840, 84

    work page 2017

  50. [50]

    V ., Zhukov, A

    Shestov, S. V ., Zhukov, A. N., Auchère, F., Berghmans, D., & Loicq, J. 2025, A&A, 699, A7

    work page 2025

  51. [51]

    Soille, P. J. & Ansoult, M. M. 1990, Signal Processing, 20, 171

    work page 1990

  52. [52]

    A., Kazachenko, M

    Tamburri, C. A., Kazachenko, M. D., Cauzzi, G., et al. 2025, The Astrophysical Journal Letters, 990, L3

    work page 2025

  53. [53]

    2025b, A&A, 702, A88 The SunPy Community, Barnes, W

    Tan, S., Warmuth, A., Schuller, F., et al. 2025b, A&A, 702, A88 The SunPy Community, Barnes, W. T., Bobra, M. G., et al. 2020, The Astrophys- ical Journal, 890, 68 Thoen Faber, J., Joshi, R., Rouppe van der V oort, L., et al. 2025, A&A, 693, A8 Thoen Faber, J., Joshi, R., Rouppe van der V oort, L., et al. 2026, A&A, 705, A174 Van Doorsselaere, T., Kupriya...

    work page 2020

  54. [54]

    Veronig, A. M. & Brown, J. C. 2004, ApJ, 603, L117

    work page 2004

  55. [55]

    M., Brown, J

    Veronig, A. M., Brown, J. C., & Bone, L. 2005, Advances in Space Research, 35, 1683

    work page 2005

  56. [56]

    Wyper, P. F. & Pontin, D. I. 2021, ApJ, 920, 102

    work page 2021

  57. [57]

    2018, Nature Communications, 9, 46

    Xu, Y ., Cao, W., Ahn, K., et al. 2018, Nature Communications, 9, 46

    work page 2018

  58. [58]

    2016, The Astrophysical Journal, 819, 89

    Xu, Y ., Cao, W., Ding, M., et al. 2016, The Astrophysical Journal, 819, 89

    work page 2016

  59. [59]

    S., et al

    Xu, Y ., Yang, X., Kerr, G. S., et al. 2022, The Astrophysical Journal Letters, 924, L18

    work page 2022

  60. [60]

    D., Cauzzi, G., et al

    Yadav, R., Kazachenko, M. D., Cauzzi, G., et al. 2025, The Astrophysical Jour- nal, 989, 183

    work page 2025

  61. [61]

    R., Inglis, A

    Young, P. R., Inglis, A. R., Kerr, G. S., Kucera, T. A., & Ryan, D. F. 2025, ApJ, 986, 64

    work page 2025

  62. [62]

    M., Kolotkov, D

    Zhong, S., Nakariakov, V . M., Kolotkov, D. Y ., Verbeeck, C., & Berghmans, D. 2022, Monthly Notices of the Royal Astronomical Society, 516, 5989

    work page 2022

  63. [63]

    V ., McLaughlin, J

    Zimovets, I. V ., McLaughlin, J. A., Srivastava, A. K., et al. 2021, Space Sci. Rev., 217, 66 Article number, page 11 of 13 A&A proofs:manuscript no. 58600-25 Appendix A: A point source observed by an instrument with a PSF of 2-pixels at FWHM In Figure A.1 we demonstrate the effect of a 2-pixel PSF on a point source located at two extreme positions — at t...

    work page 2021