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Abstract Stellar flares occasionally present apeak-bumplight-curve morphology, consisting of an initial impulsive phase followed by a gradual late phase. Analyzing this specific morphology can uncover the underlying physics of stellar flare dynamics, particularly the plasma heating–evaporation–condensation process. While previous studies have mainly examined peak-bump occurrences on M dwarfs, this report extends the investigation to G-, K-, and M-type stars. We utilize the flare catalog published by J. Crowley et al., encompassing 12,597 flares, detected by using Transiting Exoplanet Survey Satellite (TESS) observations. Our analysis identifies 10,142 flares with discernible classical and complex morphology, of which 197 (∼1.9%) exhibit the peak-bump feature. We delve into the statistical properties of these TESS late-phase flares, noting that both the amplitude and FWHM durations of both the peaks and bumps show positive correlations across all source-star spectral types, following a power law with indices 0.69 ± 0.09 and 1.0 ± 0.15, respectively. Additionally, a negative correlation between the flare amplitude and the effective temperature of their host stars is observed. Compared to the other flares in our sample, peak-bump flares tend to have larger and longer initial peak amplitudes and FWHM durations and possess energies ranging from 10³¹to 10³⁶erg. 

Abstract Quiet-Sun regions cover most of the Sun's surface; their magnetic fields contribute significantly to solar chromospheric and coronal heating. However, characterizing the magnetic fields of the quiet Sun is challenging due to their weak polarization signal. The 4 m Daniel K. Inouye Solar Telescope (DKIST) is expected to improve our understanding of quiet-Sun magnetism. In this paper, we assess the diagnostic capability of the Diffraction Limited Near Infrared Spectropolarimeter (DL-NIRSP) instrument on DKIST for the energy transport processes in the quiet-Sun photosphere. To this end, we synthesize high-resolution, high-cadence Stokes profiles of the Fei630 nm lines using a realistic magnetohydrodynamic simulation, degrade them to emulate the DKIST/DL-NIRSP observations, and subsequently infer the vector magnetic and velocity fields. For the assessment, we first verify that a widely used flow tracking algorithm, the Differential Affine Velocity Estimator for Vector Magnetograms, works well for estimating the large-scale (>200 km) photospheric velocity fields with these high-resolution data. We then examine how the accuracy of the inferred velocity depends on the temporal resolution. Finally, we investigate the reliability of the Poynting flux estimate and its dependence on the model assumptions. The results suggest that the unsigned Poynting flux, estimated with existing schemes, can account for about 71.4% and 52.6% of the reference ground truth at $\log \tau =0.0$and $\log \tau =-1$. However, the net Poynting flux tends to be significantly underestimated. The error mainly arises from the underestimated contribution of the horizontal motion. We discuss the implications for DKIST observations. 

Cloud systems are increasingly being managed by operation programs termed operators, which automate tedious, human-based operations. Operators of modern management platforms like Kubernetes, Twine, and ECS implement declarative interfaces based on the state-reconciliation principle. An operation declares a desired system state and the operator automatically reconciles the system to that declared state. Operator correctness is critical, given the impacts on system operations—bugs in operator code put systems in undesired or error states, with severe consequences. However, validating operator correctness is challenging due to the enormous system-state space and complex operation interface. A correct operator must not only satisfy correctness properties of its own code, but it must also maintain managed systems in desired states. Unfortunately, end-to-end testing of operators significantly falls short. We present Acto, the first automatic end-to-end testing technique for cloud system operators. Acto uses a statecentric approach to test an operator together with a managed system. Acto continuously instructs an operator to reconcile a system to different states and checks if the system successfully reaches those desired states. Acto models operations as state transitions and systematically realizes state-transition sequences to exercise supported operations in different scenarios. Acto’s oracles automatically check whether a system’s state is as desired. To date, Acto has helped find 56 serious new bugs (42 were confirmed and 30 have been fixed) in eleven Kubernetes operators with few false alarms. 

In this work we analyze a small B-class flare that occurred on 29 April 2021 and was observed simultaneously by the Interface Region Imaging Spectrograph (IRIS) and the Nuclear Spectroscopic Telescope Array (NuSTAR) X-ray instrument. The IRIS observations of the ribbon of the flare show peculiar spectral characteristics that are typical signatures of energy deposition by non-thermal electrons in the lower atmosphere. The presence of the non-thermal particles is also confirmed directly by fitting the NuSTAR spectral observations. We show that, by combining IRIS and NuSTAR multi-wavelength observations from the corona to the lower atmosphere with hydrodynamic simulations using the RADYN code, we can provide strict constraints on electron-beam heated flare models. This work presents the first NuSTAR, IRIS and RADYN joint analysis of a non-thermal microflare, and presents a self-consistent picture of the flare-accelerated electrons in the corona and the chromospheric response to those electrons. 

Abstract We measure the sunspot areas of activity cycle 24 using ten years of continuum images from the Helioseismic and Magnetic Imager, and compare them with the peak flare soft X-ray flux from the Geostationary Operational Environmental Satellite. We find that the sunspot area in our sample is positively correlated with the magnitude of the largest flare they produce. Complex spot groups with βγδ  magnetic classification tend to be larger and more likely to produce intense flares. Our findings are qualitatively consistent with previous studies.