Search for: All records

Abstract We report on high-resolution observations of recurrent fan-like jets by the Goode Solar Telescope in multiple wavelengths inside a sunspot group. The dynamics behavior of the jets is derived from the H α line profiles. Quantitative values for one well-identified event have been obtained, showing a maximum projected velocity of 42 km s −1 and a Doppler shift of the order of 20 km s −1 . The footpoints/roots of the jets have a lifted center on the H α line profile compared to the quiet Sun, suggesting a long-lasting heating at these locations. The magnetic field between the small sunspots in the group shows a very high resolution pattern with parasitic polarities along the intergranular lanes accompanied by high-velocity converging flows (4 km s −1 ) in the photosphere. Magnetic cancellations between the opposite polarities are observed in the vicinity of the footpoints of the jets. Along the intergranular lanes horizontal magnetic field around 1000 G is generated impulsively. Overall, all the kinetic features at the different layers through the photosphere and chromosphere favor a convection-driven reconnection scenario for the recurrent fan-like jets and evidence a site of reconnection between the photosphere and chromosphere corresponding to the intergranular lanes. 

Abstract Obtaining high-quality magnetic and velocity fields through Stokes inversion is crucial in solar physics. In this paper, we present a new deep learning method, named Stacked Deep Neural Networks (SDNN), for inferring line-of-sight (LOS) velocities and Doppler widths from Stokes profiles collected by the Near InfraRed Imaging Spectropolarimeter (NIRIS) on the 1.6 m Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). The training data for SDNN are prepared by a Milne–Eddington (ME) inversion code used by BBSO. We quantitatively assess SDNN, comparing its inversion results with those obtained by the ME inversion code and related machine-learning (ML) algorithms such as multiple support vector regression, multilayer perceptrons, and a pixel-level convolutional neural network. Major findings from our experimental study are summarized as follows. First, the SDNN-inferred LOS velocities are highly correlated to the ME-calculated ones with the Pearson product–moment correlation coefficient being close to 0.9 on average. Second, SDNN is faster, while producing smoother and cleaner LOS velocity and Doppler width maps, than the ME inversion code. Third, the maps produced by SDNN are closer to ME’s maps than those from the related ML algorithms, demonstrating that the learning capability of SDNN is better than those of the ML algorithms. Finally, a comparison between the inversion results of ME and SDNN based on GST/NIRIS and those from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory in flare-prolific active region NOAA 12673 is presented. We also discuss extensions of SDNN for inferring vector magnetic fields with empirical evaluation. 

Abstract We present a detailed study of very strong magnetic fields in the NOAA Active Region (AR) 12673, which was the most flare productive AR in solar cycle 24. It produced four X-class flares including the X9.3 flare on 2017 September 6 and the X8.2 limb event on September 10. Our analysis is based on direct measurements of full Zeeman splitting of the Fei1564.85 nm line using all Stokes I, Q, U, and V profiles. This approach allowed us to obtain reliable estimates of the magnitude of magnetic fields independent of the filling factor and atmosphere models. Thus, the strongest fields up to 5.5 kG were found in a light bridge (LB) of a spot, while in the dark umbra magnetic fields did not exceed 4 kG. In the case of the LB, the magnitude of the magnetic field is not related to the underlying continuum intensity, while in the case of umbral fields we observed a well-known anticorrelation between the continuum intensity and the field magnitude. In this study, the LB was cospatial with a polarity inversion line ofδ-sunspot, and we speculate that the 5.5 kG strong horizontal fields may be associated with a compact twisted flux rope at or near the photosphere. A comparison of the depth of the Zeemanπandσcomponents showed that in the LB magnetic fields are, on average, more horizontal than those in the dark umbra. 

Spicules are rapidly evolving fine-scale jets of magnetized plasma in the solar chromosphere. It remains unclear how these prevalent jets originate from the solar surface and what role they play in heating the solar atmosphere. Using the Goode Solar Telescope at the Big Bear Solar Observatory, we observed spicules emerging within minutes of the appearance of opposite-polarity magnetic flux around dominant-polarity magnetic field concentrations. Data from the Solar Dynamics Observatory showed subsequent heating of the adjacent corona. The dynamic interaction of magnetic fields (likely due to magnetic reconnection) in the partially ionized lower solar atmosphere appears to generate these spicules and heat the upper solar atmosphere.