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  1. Abstract

    We used 29 high-resolution line-of-sight magnetograms acquired with the Goode Solar Telescope (GST) in a quiet-Sun area to extrapolate a series of potential field configurations and study their time variations. The study showed that there are regions that consistently exhibit changes in loop connectivity, whereas other vast areas do not show such changes. Analysis of the topological features of the potential fields indicates that the photospheric footprint of the separatrix between open- and closed-loop systems closely matches the roots of rapid blue- and redshifted excursions, which are disk counterparts of type II spicules. There is a tendency for the footpoints of the observed Hαfeatures to be cospatial with the footpoints of the loops that most frequently change their connectivity, while the area occupied by the open fields that did not show any significant and persistent connectivity changes is void of prominent jet and spicular activity. We also detected and tracked magnetic elements using the Southwest Automatic Magnetic Identification Suite and GST magnetograms, which allowed us to construct artificial magnetograms and calculate the corresponding potential field configurations. Analysis of the artificial data showed tendencies similar to those found for the observed data. The present study suggests that a significant amount of chromospheric activity observed in the far wings of the Hαspectral line may be generated by reconnecting closed-loop systems and canopy fields consisting of “open” field lines.

     
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  2. Free, publicly-accessible full text available June 30, 2024
  3. Abstract Plumes are bright structures in coronal holes extending from the solar surface into the corona and are considered as a possible source of the solar wind. Plumes are thought to be rooted in strong unipolar photospheric flux patches (network/plage region). The magnetic activities at the base of plumes may play a crucial role in producing outflows and propagating disturbances (PDs). However, the role of photospheric/chromospheric activities (e.g., jets/spicules) at the base of plumes and their connection to PDs is poorly understood. Using high-resolution observations of a plume taken on 2020 July 23 with the 1.6 m Goode Solar Telescope (GST), Interface Region Imaging Spectrograph (IRIS), and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory, we analyzed chromospheric/transition region activities at the base of the plume and their connection to outflows/PDs in the plume. The GST Visible Imaging Spectrometer images reveal repetitive spicules with blueshifted emission (pseudo-Doppler maps) at the plume’s footpoint. In addition, the photospheric magnetograms provide evidence of mixed polarities at the base of the plume. The IRIS Mg ii k Dopplergrams show strong blueshifted emission (∼50 km s −1 ) and a high brightness temperature (Mg ii k2 line) at the footpoint of the plume. The long-period PDs ( P ≈ 20–25 minutes) along the plume (AIA 171 Å) match the periodicity of spicules in the chromospheric images, suggesting a close connection between the spicules and the PDs. We suggest that the interchange reconnection between the closed and open flux of the coronal bright point at the plume’s footpoint is the most likely candidate to produce upflows and associated PDs along the plume. 
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    Free, publicly-accessible full text available August 1, 2024
  4. Abstract

    Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail,Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials.C. aspersumsecretes three mucus—one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties that could be used to provide insight into structure-function relationships through an integrative “mucomics” approach. We identify macromolecular components of these hydrogels, including a previously unreported protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences betweenC. aspersummucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

     
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  5. A symmetry-based approach leads to the efficient discovery of magnets hosting topological magnons. 
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  6. Context. Solar observations of carbon monoxide (CO) indicate the existence of lower-temperature gas in the lower solar chromosphere. We present an observation of pores, and quiet-Sun, and network magnetic field regions with CO 4.66 μm lines by the Cryogenic Infrared Spectrograph (CYRA) at Big Bear Solar Observatory. Aims. We used the strong CO lines at around 4.66 μm to understand the properties of the thermal structures of lower solar atmosphere in different solar features with various magnetic field strengths. Methods. Different observations with different instruments were included: CO 4.66 μm imaging spectroscopy by CYRA, Atmospheric Imaging Assembly (AIA) 1700 Å images, Helioseismic and Magnetic Imager (HMI) continuum images, line-of-sight (LOS) magnetograms, and vector magnetograms. The data from 3D radiation magnetohydrodynamic (MHD) simulation with the Bifrost code are also employed for the first time to be compared with the observation. We used the Rybicki-Hummer (RH) code to synthesize the CO line profiles in the network regions. Results. The CO 3-2 R14 line center intensity changes to be either enhanced or diminished with increasing magnetic field strength, which should be caused by different heating effects in magnetic flux tubes with different sizes. We find several “cold bubbles” in the CO 3-2 R14 line center intensity images, which can be classified into two types. One type is located in the quiet-Sun regions without magnetic fields. The other type, which has rarely been reported in the past, is near or surrounded by magnetic fields. Notably, some are located at the edge of the magnetic network. The two kinds of cold bubbles and the relationship between cold bubble intensities and network magnetic field strength are both reproduced by the 3D MHD simulation with the Bifrost and RH codes. The simulation also shows that there is a cold plasma blob near the network magnetic fields, causing the observed cold bubbles seen in the CO 3-2 R14 line center image. Conclusions. Our observation and simulation illustrate that the magnetic field plays a vital role in the generation of some CO cold bubbles. 
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  7. Abstract

    Multiple solar instrument observation campaigns are increasingly popular among the solar physics and space science communities. Scientists organize high-resolution ground-based telescopes and spacecraft to study the evolution of the complex solar atmosphere and the origin of space weather. Image registration and coalignment between different instruments are vital for accurate data product comparison. We developed a Python language package for registration of ground-based high-resolution imaging data acquired by the Goode Solar Telescope (GST) to space-based full-disk continuum intensity data provided by the Solar Dynamics Observatory (SDO) with the scale-invariant feature transform method. The package also includes tools to align data sets obtained in different wavelengths and at different times utilizing the optical flow method. We present the image registration and coalignment workflow. The aliment accuracy of each alignment method is tested with the aid of radiative magnetohydrodynamics simulation data. We update the pointing information in GST data fits headers and generate GST and SDO imaging data products as science-ready four-dimensional (x,y,λ,t) data cubes.

     
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  8. Evans, Christopher J. ; Bryant, Julia J. ; Motohara, Kentaro (Ed.)