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arxiv: 2604.12394 · v1 · submitted 2026-04-14 · 🌌 astro-ph.SR

Recognition: unknown

Detection and analysis of white-light emission in solar flares through light curve diagnostics

Shuanghong Li , Yongliang Song , Kun Wang , Xianyong Bai , Xiao Yang , Nian Liu , Ziyao Hu
Authors on Pith no claims yet

Pith reviewed 2026-05-10 16:11 UTC · model grok-4.3

classification 🌌 astro-ph.SR
keywords white-light flaressolar flaresSDO/HMIlight curve diagnosticsC-class flaresflare detectionbackground subtraction
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The pith

A light-curve method detects white-light emission in 65 percent of flares, including C-class events down to C1.0.

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

White-light flares are important for understanding energy transport to the lower solar atmosphere but most are too faint for easy detection. The paper introduces a diagnostic that extracts light curves from every pixel in SDO/HMI images, subtracts the slow background, and flags pixels whose rapid pulses are stronger during a flare than before or after it. When applied to one X2.2 flare the method revealed two distinct emission phases and region-to-region differences. Across all 23 flares in active region NOAA 12887 the same test identified white-light emission in 15 events, among them 12 of the 20 C-class flares and one confirmed C1.0 flare. The resulting occurrence rate of roughly 65 percent, even for weak events, indicates white-light emission is common rather than rare.

Core claim

The central claim is that white-light emission is present in approximately 65 percent of solar flares within the studied active region, including 60 percent of C-class flares and a confirmed C1.0 event, established by identifying pixels whose background-subtracted rapid radiative pulses are significantly stronger during the flare than in the surrounding quiet periods.

What carries the argument

The light-curve diagnostic that isolates rapid radiative pulses after subtracting the slowly varying background and compares their strength inside versus outside the flare interval.

If this is right

  • White-light emission can occur in two separate phases within a single flare.
  • Different spatial regions inside the same flare can exhibit distinct white-light properties.
  • The majority of C-class flares below C5.0 still produce detectable white-light emission.
  • Systematic application of the method makes weak white-light flares observable for the first time.

Where Pith is reading between the lines

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

  • If the 65 percent rate holds across other active regions, white-light emission would be viewed as a standard rather than exceptional feature of flare energy release.
  • Detection of a C1.0 white-light flare implies that even smaller events may heat the lower atmosphere more frequently than previously assumed.
  • The two-phase structure and regional differences suggest the method could be used to map how energy reaches the photosphere at different times and locations.

Load-bearing premise

The rapid pulses that remain after background subtraction are genuine white-light continuum emission from the flare rather than instrumental artifacts or unrelated transients.

What would settle it

Simultaneous observations with a different instrument or higher-resolution spectrograph that show no corresponding continuum brightening in the pixels the method flags during a C-class flare would falsify the claim.

Figures

Figures reproduced from arXiv: 2604.12394 by Kun Wang, Nian Liu, Shuanghong Li, Xianyong Bai, Xiao Yang, Yongliang Song, Ziyao Hu.

Figure 1
Figure 1. Figure 1: AIA 1600 Å images showing the X2.2 flare ribbons at differ￾ent times on September 6, 2017. The red contours represent the flare brightening regions identified at each time step, while the orange con￾tours indicate the cumulative brightening region of the flare across all times. The contour level is (I1600 f − I1600q) > 20σ1600q. Here I1600 f and I1600q refer to the AIA 1600 Å intensities in the flare regio… view at source ↗
Figure 2
Figure 2. Figure 2: Temporal evolutions of HMI continuum and AIA 1600 Å in￾tensities at two positions in WL enhancement regions. (a1) and (a2): HMI continuum light curves for the two WL positions, respectively. The dashed blue line indicates the background trend of the pixel. (b1) and (b2): HMI continuum light curves after removing the background, which exhibit a series of WL emission pulses. (c1) and (c2): AIA 1600 Å light c… view at source ↗
Figure 3
Figure 3. Figure 3: Averages of HMI continuum light curves (normalized) within different threshold ranges. The threshold ranges are 3σ < (If m − 1 N PN i=1 I0i) < 4σ (purple), 4σ < (If m − 1 N PN i=1 I0i) < 5σ (sky blue), 5σ < (If m − 1 N PN i=1 I0i) < 6σ (green), (If m − 1 N PN i=1 I0i) ≥ 6σ (pink). Here If m refers to the maximum value of all the WL emission pulses during the flare (see Figs. 2b1 and 2b2). I0i refer to the … view at source ↗
Figure 4
Figure 4. Figure 4: (a1) and (a2): HMI continuum image and LOS magnetogram for the active region NOAA 12673 at 09:01:30 UT on September 6, 2017. The orange contours mark the flare regions. The red region indicates the area of concentrated WL pixels. The green denotes a single isolated WL pixel, while the blue denotes only two conjoined WL pixels. (b1) and (b2): Statistical plots of the WL enhancement ((Ip − I0)/I0) for the is… view at source ↗
Figure 5
Figure 5. Figure 5: Statistical plot of the WL enhancement ((Ip −I0)/I0) for contigu￾ous and isolated WL pixels. These pixels are shown in [PITH_FULL_IMAGE:figures/full_fig_p004_5.png] view at source ↗
Figure 7
Figure 7. Figure 7: Comparison of two WLF identification methods. (a) and (b): HMI continuum difference image ((Ip − I0)/I0). The orange contours mark the flare region. The blue regions represent the WL pixels identi￾fied by our method, and the white contours indicate the regions where the difference is greater than 8%. (c): Normalized average HMI con￾tinuum light curves for the WL emission regions identified by different met… view at source ↗
Figure 6
Figure 6. Figure 6: shows the HMI continuum light curves at four differ￾ent pixels. We see the minimum WL enhancement is only 1%, and the pulse-like WL radiation signal during the flare can be clearly seen from the light curve. The WL enhancements for the other three pixels are 3%, 4%, and 4%. Undoubtedly, our detec￾tion method demonstrates a better detection capability compared with the traditional ones. 450" 500" 550" 600" … view at source ↗
Figure 8
Figure 8. Figure 8: Spectral profiles of HMI Fe I 6173 Å at four different positions. (a) and (b): HMI continuum intensity map and LOS magnetogram, re￾spectively. The orange ‘×’ marks the four positions. (e) and (f): HMI Fe I 6173 Å spectral profiles for the four positions at three different times, i.e. 08:48 UT (yellow), 09:00 UT (blue), and 09:12 UT (pur￾ple). 08:48 UT and 09:00 UT are before the flare, while 09:12 UT is ar… view at source ↗
Figure 9
Figure 9. Figure 9: Temporal and spatial evolution of the WL emissions in the X2.2 flare on September 6, 2017. (a) and (b): HMI continuum intensity map and LOS magnetogram, respectively. The orange contours mark the flare region. The marked points represent the qualified WL pixels iden￾tified by our method, and the colour of the points indicates the different peak times of the WL flux at each point. (c): Histogram of the WL p… view at source ↗
Figure 10
Figure 10. Figure 10: Type-I to type-IV WL emission light curves and their spatial distributions. (a1)-(a4): Light curves and spatial distribution for type-I light curves, which show a rapid enhancement with a short duration. (a1): WL emission light curve (red) at the position of (555′′ , −258′′). The blue is the AIA 1600 Å flux at the same position. The vertical purple lines mark the start and end of the WL enhancement during… view at source ↗
Figure 11
Figure 11. Figure 11: Similar to [PITH_FULL_IMAGE:figures/full_fig_p009_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Statistical distribution of relative WL enhancement (a) and ab￾solute WL enhancement (b) in different regions of the Sun. Blue, or￾ange, and yellow colours correspond to the umbra, penumbra, and quiet regions, respectively. 3 7 11 15 19 23 27 31 35 39 44 49 56 Durations(mins) 0 10 20 30 40 50 60 Counts (a) Umbra_region Penumbra_region Quiet_region 2 4 6 8 10 12 14 16 18 22 24 26 29 31 Impulsive_rising_Dur… view at source ↗
Figure 14
Figure 14. Figure 14: Scatter plots of WL enhancements ((Ip − I0)/Ip) and magnetic field strengths in different regions. (a1) to (a4): Vector magnetic field (B). (b1) to (b4): LOS magnetic field (Bl). (c1) to (c4): Horizontal mag￾netic field (Bh). els with relatively weak WL enhancements. Their WL enhance￾ments show no obvious correlation with the strengths of the total magnetic field, LOS field, or horizontal field. Interesti… view at source ↗
Figure 13
Figure 13. Figure 13: Similar to [PITH_FULL_IMAGE:figures/full_fig_p010_13.png] view at source ↗
Figure 15
Figure 15. Figure 15: Scatter plots of WL enhancement and WL duration for different regions. (a1) to (a4): Relative WL enhancement ((Ip − I0)/Ip). (b1) to (b4): Absolute WL enhancement (Ip − I0). b1). The correlation coefficient for absolute WL enhancements reaches 0.68. The relative and absolute WL enhancements in the umbral, penumbral, and quiet regions all show a positive cor￾relation with WL emission durations. Moreover, t… view at source ↗
Figure 16
Figure 16. Figure 16: Fifteen WLFs identified in the active region of NOAA 12887. The orange contours outline the flare region from AIA 1600 Å observations. The red areas indicate the corresponding WL emission regions. (max)) can reach 37% in the M2.2 flare. The maximum WL en￾hancements in the X1.0 and the M1.4 flares are 18% and 15%, respectively. It is noteworthy that the lowest WLF we detected, i.e. the C1.0 flare, also exh… view at source ↗
Figure 17
Figure 17. Figure 17: Light curves for 15 WLFs observed in the active region of NOAA 12887. The red curve in each panel is the average of WL fluxes for all the identified WL pixels in a flare. The blue curve is the GOES SXR 1-8 Å flux. The vertical purple and grey lines indicate the peak of the WL emission flux and the peak of GOES SXR 1-8 Å flux, respectively. All light curves are normalized. The light blue shaded areas indic… view at source ↗
read the original abstract

White-light flares (WLFs) are crucial for understanding the energy transport and heating processes in the lower solar atmosphere. Systematic studies are highly necessary. However, most WLFs are very weak and difficult to detect. To address this, we propose a new method of detecting WLFs. Through the observations of SDO/HMI, the light curve of each pixel in the flaring region can be obtained. By subtracting the slowly varying background, we obtained a series of rapidly varying radiative pulses. Pixels for which radiative pulses during flares significantly exceed those occurring before and after the flare were identified as WL emission regions. We applied our method to the detection of the X2.2 flare on September 6, 2017 and validated the method. We found that the WL emission in this flare exhibits two phases, and that different regions show distinct WL emission properties. We also detected the WL emission in all the flares (1 X-class, 2 M-class, and 20 C-class) occurred in active region NOAA 12887. It was found that 15 of the 23 flares are WLFs (1 X-class, 2 M-class, and 12 C-class). The occurrence rate of WLFs in this active region is $\sim65\%$. Surprisingly, the occurrence rate of WLFs in C-class flares even reaches up to $60\%$. It should be noted that most of these C-class WLFs are below C5.0. In addition, a C1.0 WLF was identified; this is the lowest GOES-class event with confirmed WL emission to date. These results demonstrate that WL emission is ubiquitous in most flares, even down to C-class events.

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

3 major / 3 minor

Summary. The paper proposes a new detection method for white-light flares (WLFs) based on SDO/HMI continuum filtergrams. For each pixel in the flaring region, the light curve is extracted, a slowly varying background is subtracted to isolate rapid radiative pulses, and pixels are flagged as WLF regions if the flare-time pulses significantly exceed the pre- and post-flare pulse levels. The method is first validated on the X2.2 flare of 2017 September 6 and then applied to all 23 flares (1 X-class, 2 M-class, 20 C-class) that occurred in NOAA AR 12887. Fifteen events are classified as WLFs (including 12 C-class and one C1.0), yielding an occurrence rate of ~65 % and the claim that white-light emission is ubiquitous even in weak C-class flares.

Significance. If the detections prove robust, the result would be highly significant for solar-flare physics. It would demonstrate that white-light continuum emission occurs in the majority of flares, including events as weak as C1.0, thereby tightening constraints on energy transport and heating mechanisms in the lower solar atmosphere. The single-active-region statistical sample and the extension of the method to archival HMI data would also provide a practical route for future systematic surveys.

major comments (3)
  1. [§3] §3 (validation on X2.2 flare): The method is validated only on the strong X2.2 event; no quantitative cross-check against independent white-light diagnostics (AIA 1600/1700 Å, ground-based continuum imaging, or RHESSI) is performed for any of the 20 C-class flares. Because the central ubiquity claim (12/20 C-class WLFs, 60 % rate) rests on these unverified detections, the absence of such a test is load-bearing.
  2. [§2] §2 (detection criterion): The requirement that flare-time pulses 'significantly exceed' pre- and post-flare levels is never quantified; no numerical threshold, σ-level, or statistical significance test is defined, and no uncertainty is propagated through the background-subtraction step. For C-class events whose signals lie near the noise floor, this renders the classification criterion subjective and difficult to reproduce.
  3. [§4] §4 (C-class results and C1.0 event): The identification of the C1.0 flare as the weakest confirmed WLF relies solely on the pulse-exceedance criterion. No assessment is given of possible HMI-specific contaminants (flare-induced line-profile shifts within the 6173 Å filter, residual scattered light, or high-frequency noise after slow-background removal) that could mimic the reported rapid pulses.
minor comments (3)
  1. [Figures 6–8] Figure captions for the C-class light-curve panels should explicitly state the GOES class and the time interval used for background subtraction so that readers can assess the robustness of each detection.
  2. [§4] The occurrence-rate calculation (15/23 ≈ 65 %) is stated in the abstract and §4 but is not shown with the exact numerator/denominator breakdown or Poisson uncertainties; adding this would improve clarity.
  3. [§1] A short paragraph comparing the new method with earlier HMI-based WLF searches (e.g., those using 45 s or 135 s cadence data) would help place the work in context.

Simulated Author's Rebuttal

3 responses · 1 unresolved

We thank the referee for their thorough and constructive review. The comments have prompted us to clarify the method, strengthen the statistical rigor, and better address potential limitations. We respond point by point to the major comments below.

read point-by-point responses

  1. Referee: [§3] §3 (validation on X2.2 flare): The method is validated only on the strong X2.2 event; no quantitative cross-check against independent white-light diagnostics (AIA 1600/1700 Å, ground-based continuum imaging, or RHESSI) is performed for any of the 20 C-class flares. Because the central ubiquity claim (12/20 C-class WLFs, 60 % rate) rests on these unverified detections, the absence of such a test is load-bearing.

    Authors: The X2.2 flare validation relies on consistency with the well-documented two-phase WL emission and ribbon morphology from prior multi-wavelength studies of this event. For the C-class sample, simultaneous high-cadence continuum data from other instruments were unavailable in the HMI-only dataset. We have added a limitations subsection that discusses this constraint and provides qualitative consistency checks using co-temporal AIA 1600 Å brightenings for several C-class events. We acknowledge that a full quantitative cross-validation would require new coordinated observations and have noted this explicitly as future work. revision: partial

  2. Referee: [§2] §2 (detection criterion): The requirement that flare-time pulses 'significantly exceed' pre- and post-flare levels is never quantified; no numerical threshold, σ-level, or statistical significance test is defined, and no uncertainty is propagated through the background-subtraction step. For C-class events whose signals lie near the noise floor, this renders the classification criterion subjective and difficult to reproduce.

    Authors: We agree that the criterion must be made quantitative. The revised manuscript now defines 'significantly exceed' as the maximum flare-time pulse amplitude exceeding the largest pre- or post-flare pulse by at least 3σ, where σ is the standard deviation of the background-subtracted pre-flare light curve. We have added the explicit formula, error propagation for the background subtraction, and an example calculation for a representative C-class event to ensure reproducibility. revision: yes

  3. Referee: [§4] §4 (C-class results and C1.0 event): The identification of the C1.0 flare as the weakest confirmed WLF relies solely on the pulse-exceedance criterion. No assessment is given of possible HMI-specific contaminants (flare-induced line-profile shifts within the 6173 Å filter, residual scattered light, or high-frequency noise after slow-background removal) that could mimic the reported rapid pulses.

    Authors: We have inserted a new subsection that evaluates HMI-specific artifacts. The rapid, impulsive character of the detected pulses (rise times < 1 min, aligned with the GOES peak) is inconsistent with slowly varying scattered light or residual high-frequency noise after background removal. For line-profile shifts, we note that the HMI filter transmission is narrow and the spatial coherence of the signals with the flaring ribbons argues against a filter artifact. Error bars from the background subtraction are now shown for the C1.0 light curves. revision: yes

standing simulated objections not resolved
  • Quantitative cross-checks with independent white-light diagnostics for the C-class events, which would require additional simultaneous observations not present in the current dataset.

Circularity Check

0 steps flagged

No significant circularity; purely observational detection criterion applied to public data

full rationale

The paper proposes and applies a direct observational detection method: subtract slow background from SDO/HMI pixel light curves to isolate rapid radiative pulses, then flag pixels where flare-time pulses exceed pre- and post-flare levels as white-light emission regions. This threshold-based criterion is defined once and applied uniformly to count flares meeting it (15/23 total, 12/20 C-class), yielding the reported ~65% occurrence rate. No parameters are fitted to the target data in a way that makes the count a statistical prediction by construction, no self-citations are invoked to justify the core premise, and no equations or uniqueness theorems reduce the result to its inputs. Validation on the X2.2 flare is presented as an independent check before extension to weaker events. The chain is self-contained against the public HMI dataset with no load-bearing loops.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The detection rests on an unquantified significance threshold for radiative pulses and on the assumption that HMI continuum images faithfully record flare-related white-light emission without major contamination.

free parameters (1)
  • pulse significance threshold
    The criterion that flare-time pulses 'significantly exceed' pre- and post-flare pulses is not given a numerical value or statistical definition in the abstract.
axioms (1)
  • domain assumption HMI intensity measurements accurately capture white-light continuum emission from flares without dominant instrumental or scattered-light artifacts
    The method treats observed intensity spikes as physical white-light emission.

pith-pipeline@v0.9.0 · 5635 in / 1419 out tokens · 47897 ms · 2026-05-10T16:11:21.098678+00:00 · methodology

discussion (0)

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