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This paper reports fifteen sloshing oscillations in seven coronal loops, triggered by successive M- and C-class flares, and shows that their periods, damping times, and inferred temperatures vary from flare to flare, with damping not always

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2026-08-01 17:15 UTC pith:U6VLWQUG

load-bearing objection Useful new sloshing-oscillation events, but the derived temperatures and scaling exponents rest on an unquantified loop-length geometry assumption and pooled non-independent events; the 131/94 damping comparison is the most robust result. the 3 major comments →

arxiv 2607.17685 v1 pith:U6VLWQUG submitted 2026-07-20 astro-ph.SR

Sloshing Oscillations in coronal loops excited by successive M- and C-Class flares

Hitesh Paliwal , S. Krishna Prasad , M. V. Sunil Krishna This is my paper
classification astro-ph.SR
keywords sloshing oscillationscoronal loopsslow magnetoacoustic wavessolar flaresAIA/SDOcoronal seismologywave dampingflare-driven oscillations
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The authors set out to measure how flare-triggered sloshing oscillations — plasma bouncing back and forth between the footpoints of a coronal loop — behave when the same loop is hit by flares of different strength. Using AIA 131 and 94 Å images, they identified fifteen oscillation events in seven loops and extracted periods (304–637 s), damping times (129–1660 s), and phase speeds (446–842 km/s). They find that oscillation properties change considerably between successive flares in the same loop, that damping times are not always longer in the cooler 94 Å channel, and that the damping-time–period relation is steeper than the nearly linear scaling found for standing slow waves. If correct, sloshing oscillations become a repeatable probe of how individual flares reshape the local coronal plasma and of which damping mechanisms dominate.

Core claim

The central claim is that sloshing oscillations excited by successive M- and C-class flares provide a rare controlled comparison of flare strength as a driver of loop oscillations. Fifteen events in seven loops yield periods from 304 to 637 s, damping times from 129 to 1660 s, and phase speeds from 446 to 842 km/s; interpreting the phase speed v=2L/P as sound speed gives plasma temperatures of 9–31 MK. Two results stand out: the damping time is not always longer in the cooler 94 Å channel than in 131 Å, contrary to the earlier thermal-conduction picture, and the damping-time–period power-law exponent (≈1.4) is significantly steeper than the ≈1.0 found for standing slow waves, while the perio

What carries the argument

The analysis rests on two tools: a modified damped-sloshing light-curve model (an exponential decay times a Gaussian spatial envelope of a cosine-shaped back-and-forth perturbation, plus a quadratic background) fitted to footpoint time series in AIA 131 and 94 Å channels, and the semicircular-loop deprojection model of Aschwanden et al. (2002) that turns a manually traced 2D loop path into a length L=πr. The length enters the phase speed v=2L/P, and the temperature T=(v/152)² MK; the loop length is the quantity that carries all absolute scaling.

Load-bearing premise

The paper assumes each loop is a semicircular arc whose length is well estimated by fitting a projected 2D image with the Aschwanden model; every derived speed and temperature scales linearly with that length, and the authors note the true length uncertainty may be substantially larger than the quoted statistical errors.

What would settle it

Measure the same seven loops with a three-dimensional reconstruction (e.g., stereoscopy or a magnetic-field model) and recompute L; if the true lengths differ systematically from the semicircular estimates by more than ~20%, the reported phase speeds (446–842 km/s), temperatures (9–31 MK), and the ~600 km/s period–length slope would shift correspondingly. Alternatively, an independent dataset of sloshing events with more non-flare triggers could test whether the steeper damping-time–period exponent is real or a small-sample artifact.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • If sloshing oscillations respond measurably to flare strength, repeated flares in the same loop become natural experiments for tracking how individual flares deposit energy and alter local loop conditions.
  • The finding that 94 Å damping is not always longer than 131 Å damping implies thermal conduction is not the sole or dominant damping mechanism; compressive viscosity or heating-cooling misbalance must be invoked in at least some events.
  • A steeper-than-linear damping-time–period relation (1.38–1.44) for sloshing oscillations, distinct from the ~1.0 exponent for standing slow waves, points to a different or additional damping channel for propagating sloshing modes.
  • The tight linear period–loop-length scaling with ~600 km/s representative phase speed means sloshing events are mostly governed by loop length, and shorter loops should host shorter periods regardless of flare strength.
  • Extending the observed period range to C-class flares suggests short-period sloshing events are not confined to strong flares, enlarging the coronal-seismology sample.

Where Pith is reading between the lines

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

  • The near-constant phase speed across loops (~600 km/s) hints that these flare-heated loops settle into a common temperature regime; if so, the damping-time scatter may be a cleaner diagnostic of loop density and magnetic field than the period itself.
  • One could test the flare-strength dependence directly by comparing energy-flux-normalized properties: the paper's C1.1 vs M2.0 contrast in loop 1 suggests a scaling of damping time with peak GOES flux that a dedicated multi-event study could quantify.
  • If the semicircular length assumption is the main systematic, the quoted 9–31 MK temperatures should be treated as provisional; a stereoscopic or magnetic-field-model validation of a few loops would calibrate the whole sample.
  • A natural extension is to search for sloshing oscillations in the same loops during quiescent (non-flare) brightenings; the absence of oscillation then would prove the flare trigger rather than loop properties is what sets the period.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper reports 15 sloshing-oscillation events in 7 distinct coronal loops observed with SDO/AIA, triggered by successive M- and C-class flares. For each event the authors fit a damped sinusoidal model (Eq. 1) to time series extracted near a loop footpoint in the 131 and 94 Å channels, obtaining periods of 304–637 s and damping times of 129–1660 s. Loop lengths are estimated by fitting a semicircular Aschwanden model to manually traced loop points (Appendix A), and phase speeds are computed as v = 2L/P and converted to temperatures through the sound-speed relation T = (v/152)^2. The central claims are that oscillation properties vary from flare to flare within the same loop, that damping times are not always longer in the cooler 94 Å channel, and that period and loop length follow a linear scaling with a representative phase speed near 600 km/s. The paper also compares the damping-time/period power-law slope with earlier standing-mode results.

Significance. If the results hold, this is the largest targeted sample of sloshing oscillations in flaring coronal loops, and the first to compare multiple M- and C-class flares in the same loops. The 94 Å damping-time comparison challenges the assumption that thermal conduction is the sole or dominant damping mechanism, and the P–L scaling suggests that short-period sloshing events may be common in shorter loops regardless of flare class. The parameter extraction is transparent: uncertainties on period and damping time are propagated from AIA noise estimates, exposure-time variations are explicitly handled, cases with poor visibility are left blank, and the appendices show the time–distance maps and fits for all loops. These are real strengths. The quantitative temperature and phase-speed results, however, rest on an unquantified semicircular-geometry assumption for loop length and on treating a partly non-independent sample as independent in the scaling relations, so the numerical precision of the headline seismological values is not yet established.

major comments (3)
  1. [Section 3; Appendix A, Eq. A1; Table 1; Fig. 4] Loop length L is the most load-bearing derived quantity: it enters every phase speed v=2L/P and every temperature T=(2L/152P)^2. The quoted uncertainties (e.g., 179.5±2.7 Mm) are only statistical fit errors from the semicircular Aschwanden model and manual tracing. The text acknowledges that the true uncertainty may be substantially larger, but this is never quantified or propagated. Because T scales as L^2, a 20% systematic error in L produces a 44% error in T, which would expand or shift the claimed 9–31 MK range and the P–L phase speed of 641±34 km/s. Please estimate the systematic length uncertainty by, for example, varying the traced points, using multiple reference frames, fitting an elliptical/arcade model instead of a purely semicircular one, or cross-checking against stereoscopic or DEM-constrained loop models, and propagate that into the reported quantities.
  2. [Table 1; Figs. 3 and 4] The statistical independence of the 15 events is overstated. Loops 3, 5, and 6 share the same flare start times and coordinates (2022-06-16T02:03 for the C1.4 flare and 03:52 for the M1.6 flare), and each loop contributes 2–3 events with the same L. In the P–L fits of Figure 4, repeated points for the same loop are not independent, and the effective number of independent L values is only 7. The similarly correlated structure applies to the τ–P fits. Please report cluster-robust uncertainties, or average per loop per flare, or otherwise account for the non-independence before claiming a 'strong' Pearson correlation of 0.8 and a 1.38–1.56 power-law slope.
  3. [Section 3, Eq. (4) and the DEM paragraph] The conversion from phase speed to temperature assumes v equals the local adiabatic sound speed. The DEM analysis yields peak temperatures clustered at 10–12 MK, which the authors attribute to DEM saturation. This is plausible, but the alternative interpretation — that the seismological temperatures are biased by the semicircular length assumption or by a non-sound-speed phase speed — is not ruled out. Since the shorter-period-during-M-flare inference is explicitly acknowledged to be circular (T is derived from P), that part of the argument should be removed or rephrased. More generally, please compare the seismological temperatures with an independent, saturation-aware temperature diagnostic (e.g., including GOES or high-temperature emission in the DEM) or state explicitly that the 9–31 MK range is conditional on the sound-speed identification and nominal geometry.
minor comments (4)
  1. [Throughout] The manuscript would benefit from a final proofread: e.g., the LaTeX header shows 'LATEXdefaultstyle', and some in-text references in figure legends and captions omit author initials (e.g., 'Kumar 2013' in Fig. 3 should be 'P. Kumar et al. 2013').
  2. [Section 3, Eqs. (2)–(3)] Define 'DN' explicitly at first use and clarify that the exposure-normalized intensities are still fitted in DN-like units; the noise model is quoted for raw DN only.
  3. [Section 4 and Fig. 3] The text reports Pearson r values of ~0.5 for the τ–P relation, but the figure also lists R values for combined data; please state in the text whether the quoted r is for the present sample alone or the combined sample, and give the number of points used in each fit.
  4. [Appendix A, Eq. A1] Eq. A1 defines r from h0 and Lbase, but the text says L=πr; please explicitly note that the semi-circular assumption fixes the arc length to πr and that the inclination angle θ enters only through the projection. This will make the geometric assumption clearer to readers.

Circularity Check

0 steps flagged

No significant circularity: derived temperatures are explicitly flagged as dependent on measured periods; the P–L and τ–P scalings are fits of the same data, not predictions; self-citations are methodological, not load-bearing.

full rationale

The paper's derivation chain is not circular. The oscillation period and damping time are obtained by fitting the time series model (Eq. 1), while loop lengths are estimated independently from the Aschwanden semi-circular model (Eq. A1). The phase speed and temperature are then derived via v = 2L/P and T = (v/152)^2; this is a physical conversion with explicitly stated assumptions, and the authors themselves acknowledge that these temperature estimates cannot be used to explain the period differences because the period enters the calculation (Section 3). The P–L scaling in Figure 4 is presented as a fit whose slope gives a representative phase speed, not as a prediction of a separate quantity, and the τ–P scaling is likewise a correlation of two independently fitted parameters. Self-citations to S. Krishna Prasad & T. Van Doorsselaere (2021) are used for a fitting approach and for contextual comparison, not to justify a uniqueness theorem or to substitute for an argument. The acknowledged limitation that the quoted loop-length uncertainties exclude systematic errors from the semi-circular geometry assumption is a statement about uncertainty, not a definitional equivalence. No load-bearing step reduces to its own input by construction.

Axiom & Free-Parameter Ledger

4 free parameters · 6 axioms · 0 invented entities

No new physical entities are introduced. The main hidden inputs are geometric and wave-identification assumptions: semicircular loop deprojection, the v=2L/P round-trip relation, and the sound-speed-to-temperature conversion. The derived temperature is not an independent measurement because it is calculated from the same period used in the flare-strength comparison.

free parameters (4)
  • Loop center height h0 (Aschwanden model) = 25.4 Mm for Loop 1; per loop otherwise
    Fit parameter in the deprojection model; directly determines L and therefore v and T. Systematic geometry uncertainty is not included.
  • Loop inclination angle θ (Aschwanden model) = -89.5 deg for Loop 1; per loop otherwise
    Second deprojection parameter; affects the estimated loop length.
  • Fitted model constants in Eq. 1 (A0, B0, C0, D, phi, sigma) = Per event
    Constants of the background polynomial and Gaussian pulse shape used in the chi-square fit; needed to extract P and tau.
  • Oscillation period P and damping time tau per event = Listed in Table 1 for each event/channel
    Outputs of the nonlinear least-squares fit, but they are free parameters of the fit and carry the main uncertainties that propagate into all derived quantities.
axioms (6)
  • domain assumption Semi-circular loop geometry and Aschwanden deprojection model (Appendix A, Eq. A1)
    Used to convert the projected 2D loop trace into a 3D length L. The authors acknowledge that the true systematic uncertainty may be substantially larger than the quoted fit errors.
  • domain assumption Sloshing phase speed satisfies v = 2L/P (round-trip distance 2L per period)
    Stated in Section 3 for sloshing oscillations; reasonable for a perturbation reflecting from footpoints, but if the propagation path or reflection geometry differs, v and T shift.
  • domain assumption Phase speed equals local sound speed, with gamma=1.67 and mu=0.6, to convert v to temperature (Eq. 4)
    Standard slow-wave assumption supported by prior Doppler studies, but not independently verified for these events; the resulting 9–31 MK temperatures inherit this assumption.
  • domain assumption Exponential damping plus moving Gaussian pulse model (Eq. 1) describes the observed light curves
    The fitted P and tau are only as good as this functional form; non-exponential damping or changing pulse shapes would bias the extracted parameters.
  • domain assumption AIA 131 and 94 Å intensity at the chosen footpoint location is dominated by the selected loop
    Manual loop selection and fixed extraction position assume negligible line-of-sight contamination; the paper notes a different loop along the line of sight in Loop 5, showing contamination is possible.
  • domain assumption Visually selected events are representative of the sloshing-oscillation population
    Events were chosen by inspecting low-resolution animations for clear back-and-forth motion; no objective detection threshold or completeness estimate is provided, so selection bias is possible.

pith-pipeline@v1.3.0-alltime-deepseek · 14633 in / 12199 out tokens · 131633 ms · 2026-08-01T17:15:47.031534+00:00 · methodology

0 comments
read the original abstract

Slow magnetoacoustic waves in hot coronal loops have remained a topic of considerable interest and debate over the past two decades. The periodic back-and-forth motion of plasma within a coronal loop, often initiated by a flare, is commonly referred to as sloshing oscillation. In the present study, we report unprecedented observations of sloshing oscillations in coronal loops excited by successive M- and C-class flares, using data from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). A total of fifteen oscillation events were identified within seven distinct coronal loops, providing the rare opportunity to evaluate the influence of flare strength on the characteristics of the oscillations. Based on the appearance of the oscillations, their properties were extracted mainly from the AIA 131 and 94 {\AA} channels. Additionally, we estimate the deprojected length of each loop by assuming a semi-circular geometry. Our results indicate considerable changes in the properties of oscillations from one flare to another, suggesting the role of individual flares in shaping the local physical conditions. The plasma temperature estimated from the loop length and oscillation period ranges from 9 to 31 MK. Additionally, we find that the damping times are not always longer in the colder 94 {\AA} channel as previously observed. By combining the results obtained from all events, we study the inter-dependences between various parameters, including oscillation period, damping time, loop length, and plasma temperature, and discuss these results in the context of the theory of slow waves.

Figures

Figures reproduced from arXiv: 2607.17685 by Hitesh Paliwal, M. V. Sunil Krishna, S. Krishna Prasad.

Figure 1
Figure 1. Figure 1: (a) Map of the loop structure corresponding to Event a in loop 1 listed in [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Extraction of oscillation parameters. The symbols with error bars represent data points with the nominal exposure time extracted from the original time–distance maps at the locations marked by the orange solid lines in [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: The dependence of damping time on oscillation period in the AIA 131 ˚A and 94 ˚A channels. The filled black circles/squares represent the data from this work, and the color symbols represent the data from previous studies (P. Kumar et al. 2013; T. Wang et al. 2015; P. Kumar et al. 2015; S. Krishna Prasad & T. Van Doorsselaere 2021) as listed in the legend. The black solid line represents the best fit to ou… view at source ↗
Figure 4
Figure 4. Figure 4: The dependence of oscillation period on loop length in AIA 131 and 94 ˚A channels. Black dots/squares with error bars represent results from the present study, while colored markers correspond to previous studies (P. Kumar et al. 2013, 2015; T. Wang et al. 2015; S. Krishna Prasad & T. Van Doorsselaere 2021; R. Karakotov et al. 2024) as denoted in the legend. The black solid line shows the best-fit linear r… view at source ↗
Figure 5
Figure 5. Figure 5: Estimation of loop length following the model of M. J. Aschwanden et al. (2002). (a) Snapshot of loop 1 in AIA 131 ˚A channel selected from an instant when the entire loop structure is clearly visible. The solid black curve shows the best fit obtained from the model. (b) Diamond markers indicate the locations of manually selected points along the loop for fitting the model. The geometry of the loop is high… view at source ↗
Figure 6
Figure 6. Figure 6: Similar to figure 1 but for Loop 2 in table 1. (a) (b) [PITH_FULL_IMAGE:figures/full_fig_p015_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Similar to figure 2 but for Loop 2 in table 1. The data points shown by red markers in the bottom panel correspond to frames with low exposure times and were excluded from the fitting procedure [PITH_FULL_IMAGE:figures/full_fig_p015_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Similar to figure 1 but for Loop 3 in table 1. (a) (b) [PITH_FULL_IMAGE:figures/full_fig_p016_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Similar to figure 2 but for Loop 3 in table 1 [PITH_FULL_IMAGE:figures/full_fig_p016_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Similar to figure 1 but for Loop 4 in table 1. Note that in panel b), the brightening near 06:25 UT is associated with a small flare that occurred prior to the M-class flare considered here. The vertical stripes visible in both time–distance maps originate from the alternating low-exposure images automatically acquired by AIA in specific channels during flares. Despite doing exposure time normalisation, t… view at source ↗
Figure 11
Figure 11. Figure 11: Similar to figure 2 but for Loop 4 in table 1 [PITH_FULL_IMAGE:figures/full_fig_p017_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Similar to figure 1 but for Loop 5 in table 1. In the top-right panel, only a single bright ridge is visible in the time–distance map, preventing a reliable estimation of the oscillation properties. Consequently, no oscillation parameters were derived for that event. Note that the oscillatory pattern visible in the lower part of the time-distance map correspond to a different, smaller coronal loop along t… view at source ↗
Figure 13
Figure 13. Figure 13: Same as [PITH_FULL_IMAGE:figures/full_fig_p018_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Similar to figure 1 but for Loop 6 in table 1. (a) (b) [PITH_FULL_IMAGE:figures/full_fig_p019_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Similar to figure 2 but for Loop 6 in table 1 [PITH_FULL_IMAGE:figures/full_fig_p019_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: Similar to figure 1 but for Loop 7 in table 1. (a) (b) [PITH_FULL_IMAGE:figures/full_fig_p020_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: Similar to figure 2 but for Loop 7 in table 1 [PITH_FULL_IMAGE:figures/full_fig_p020_17.png] view at source ↗

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