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Transition region response to Quiet Sun Ellerman Bombs

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arxiv 2406.09585 v1 pith:2XJURC7Y submitted 2024-06-13 astro-ph.SR

classification astro-ph.SR
keywords qsebsbrighteningsregionsolarobservationsquiettransitionatmosphere
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abstract

Quiet Sun Ellerman Bombs (QSEBs) are key indicators of small-scale photospheric magnetic reconnection events. Recent high-resolution observations have shown that they are ubiquitous and that large numbers of QSEBs can be found in the quiet Sun. We aim to understand the impact of QSEBs on the upper solar atmosphere by analysing their spatial and temporal relationship with the UV brightenings observed in transition region diagnostics. We analyse high-resolution H-beta observations from the Swedish 1-m Solar Telescope and utilise k-means clustering to detect 1423 QSEBs in a 51 min time series. We use coordinated and co-aligned observations from the Interface Region Imaging Spectrograph (IRIS) to search for corresponding signatures in the 1400 A slit-jaw image (SJI) channel and in the Si IV 1394 A and Mg II 2798.8 A triplet spectral lines. We identify UV brightenings from SJI 1400 using a threshold of 5$\sigma$ above the median background. We focused on 453 long-lived QSEBs ($>1$ min) and found 67 cases of UV brightenings from SJI 1400 occurring near the QSEBs, both temporally and spatially. Temporal analysis of these events indicates that QSEBs start before UV brightenings in 57 % of cases, while UV brightenings lead in 36 % of instances. The majority of the UV brightenings occur within 1000 km from the QSEBs in the direction of the solar limb. We also identify 21 QSEBs covered by the IRIS slit, with 4 of them showing emissions in both or one of the Si IV 1394 A and Mg II 2798.8 A triplet lines, at distances within 500 km from the QSEBs in the limb direction. We conclude that a small fraction (15 %) of the long-lived QSEBs contribute to localized heating observable in transition region diagnostics, indicating a minimal role in the global heating of the upper solar atmosphere.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Automatic detection of Ellerman bombs using Deep Learning

    astro-ph.SR 2025-05 conditional novelty 6.0 of 10

    Neural networks can automatically detect Ellerman bombs in high-resolution Hα data, but SDO/AIA four-passband intensity maps alone are insufficient for reliable detection.

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