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Spectroscopic observations of solar flare pulsations driven by oscillatory magnetic reconnection

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Abstract

Solar and stellar flares often exhibit oscillations, or quasi-periodic pulsations (QPPs), across the electromagnetic spectrum. While magnetic-field reconnection drives these events, it remains to be determined whether oscillatory reconnection causes the quasi-periodicity, or whether waves drive or mediate this process. Exploiting coordinated observations from NASA’s Interface Region Imaging Spectrograph and the Swedish 1 m Solar Telescope, here we present spectroscopic observations of QPPs in a solar flare at high-temporal (<1 s) and high-spatial (~60 km) resolution. Downwards velocities in the flare ribbon show synchronized oscillations at different atmospheric layers with a period of ~32 s. These velocities correlate with hard X-ray emissions, indicating a modulated deposition of accelerated electrons in the chromosphere as the driver. By negating magnetohydrodynamic sausage modes as the modulator, we demonstrate that repeated reconnection drives the QPPs. The QPP–reconnection relationship established here provides observational benchmarks for reconnection models and diagnostics for probing energy release across astrophysical environments.

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Fig. 1: Observational overview of the 3 May 2023 M4.4-class flare.
Fig. 2: Correlation between condensation and HXR oscillations.
Fig. 3: Correlation between Fe xxi Gaussian components.
Fig. 4: Map of QPP Ca ii K velocity periods for flare ribbon pixels.

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Data availability

The IRIS and SST/CHROMIS datasets used in this study are available for download from the Heliophysics Events Knowledgebase. SDO data products can be found at http://jsoc.stanford.edu/. ASO-S/HXI data can be downloaded from http://aso-s.pmo.ac.cn/sodc/dataArchive.jsp. Fermi/GBM data are available at https://fermi.gsfc.nasa.gov/ssc/data/. The three-dimensional magnetic-field extrapolations are secondary outputs derived from publicly available SDO/HMI data using methods outlined in the paper and are fully reproducible. Because they are a secondary product, large in size and require specialized software for visualization, we provide them upon request instead of making them publicly available in a repository.

Code availability

All data processing and analysis discussed in Methods used publicly available Python and SolarSoft/IDL libraries. Routines relevant for spectral analysis are outlined at https://iris.lmsal.com/analysis.html. The automated multi-Gaussian-fitting routine used for Si iv analysis is located at https://github.com/wilashfie/auto-Gauss. Relevant information for reducing the HXI data is located at http://aso-s.pmo.ac.cn/sodc/analysisGuide.jsp. The wavelet code used for the QPP signal analysis can be found at https://paos.colorado.edu/research/wavelets/. Code for the AFINO method is located at https://aringlis.github.io/AFINO/.

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Acknowledgements

W.A., V.P., J.L., N.F., S.B. and B.D.P. acknowledge support from the NASA IRIS contract (NNG09FA40C). W.A. acknowledges support from the Heliophysics Guest Investigator (H-GI) Open grant 80NSSC24K0451. J.L. and V.P. acknowledge support from the Heliophysics Guest Investigator (H-GI) Open grant 80NSSC24K0553. G.C. acknowledges support from NASA contract 80NSSC25K7691. N.F. acknowledges support from both the NASA SDO/AIA (NNG04EA00C) and Hinode/SOT (NNM07AA01C) contracts. L.R.v.D.V., R.J. and J.T.F. are supported by the Research Council of Norway (RCN) through its Centres of Excellence scheme, project number 262622. L.R.v.D.V. acknowledges support from RCN project number 325491. IRIS is a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research Center and major contributions to downlink communications funded by ESA and the Norwegian Space Centre. The Swedish 1-m Solar Telescope (SST) is operated on the island of La Palma by the Institute for Solar Physics of Stockholm University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. The SST is co-funded by the Swedish Research Council as a national research infrastructure (registration number 4.3-2021-00169).

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Authors and Affiliations

Authors

Contributions

W.A. led the research project, analysis of IRIS and SST spectra, image and signal processing, and coordination between collaborators. V.P. assisted in the analysis of the IRIS spectral data, the interpretation of the multi-wavelength oscillations and their correlation, and the interpretation of the results in terms of competing physical mechanisms. J.L. assisted in the analysis of IRIS data and periodic signals and aided in interpreting the observations. B.D.P. assisted in the interpretation of the multi-wavelength observations and the interpretation in terms of physical mechanisms. B.D.P. assisted in the planning and prioritization of observations with IRIS and SST. G.C. assisted in the planning and coordinating observations with IRIS and SST and performed the magnetic modelling of the observed target. J.L. and G.C. observed the flare with the SST. N.F. and S.B. helped plan the observation campaign and were involved with the SST observations. W.A. implemented the IRIS observing programme. L.R.v.D.V. helped with planning the SST observing programme. L.R.v.D.V. and R.J. processed the SST data. J.T.F. aligned the IRIS and SST datasets. All authors read and commented on the paper.

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Correspondence to William Ashfield IV.

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Nature Astronomy thanks Dong Li and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 QPP analysis of the Si IV 1402.77 Å velocity signal.

The top panel shows the downward velocity of the central Gaussian (light green), the slow-varying trend (red-dashed), and the subtracted detrended velocity (blue). The bottom panel shows the local wavelet power spectrum of the detrended velocity. Dashed contours display the local 95% confidence level. The right panel shows the global wavelet spectrum of the time-averaged local wavelet power (blue) and corresponding Lomb-Scargle periodogram of the detrended velocity (yellow). The green and red-dashed lines correspond to the 95% confidence intervals of the global wavelet and periodogram power spectra, respectively, using a red-noise background. The peak (grey-dashed) and FWHM of the global wavelet spectrum defines the period and uncertainty of the signal: \(32.{1}_{-7.8}^{+8.7}\) s.

Extended Data Fig. 2 Comparison of the HXI HXR signal to Fermi/GBM HXRs and GOES/XRS 1-8 Å SXRs.

Left panel: Detrended signals of GOES/XRS 1-8 Å (grey), HXI 25-50 keV (red), and Fermi/GBM 25-50 keV (purple). Right panel: Time-averaged (global) wavelet power spectrum of each oscillatory signal. Peaks and FWHM of each spectrum are shown in their respective color.

Supplementary information

Supplementary Information

Supplementary Figs. 1–18, Sections 1–4 and References.

Supplementary Video 1

Animation of the Ca ii K velocity map.

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Ashfield, W., Polito, V., Lörinčík, J. et al. Spectroscopic observations of solar flare pulsations driven by oscillatory magnetic reconnection. Nat Astron 10, 54–63 (2026). https://doi.org/10.1038/s41550-025-02706-4

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