arXiv subjects

Jie Hong

Publications and source records attributed to Jie Hong.

At least 37 records · Page 2Linked to original sources

arXiv2023

Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE

The heating mechanisms of solar white-light flares remain unclear. We present an X1.0 white-light flare on 2022 October 2 (SOL2022-10-02T20:25) observed by the Chinese \ha\ Solar Explorer (CHASE) that provides two-dimensional spectra in the visible light for the full solar disk with a seeing-free condition. The flare shows a prominent enhancement of $\sim$40\% in the photospheric \fe\ line at 6569.2 Å, and the nearby continuum also exhibits a maximum enhancement of $\sim$40\%. For the continuum near the \fe\ line at 6173 Å from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO), it is enhanced up to $\sim$20\%. At the white-light kernels, the \fe\ line at 6569.2 Å has a symmetric Gaussian profile that is still in absorption and the H$α$ line at 6562.8 Å displays a very broad emission profile with a central reversal plus a red or blue asymmetry. The white-light kernels are co-spatial with the microwave footpoint sources observed by the Expanded Owens Valley Solar Array (EOVSA) and the time profile of the white-light emission matches that of the hard X-ray emission above 30 keV from the Gamma-ray Burst Monitor (GBM) on Fermi. These facts indicate that the white-light emission is qualitatively related to a nonthermal electron beam. We also perform a radiative hydrodynamic simulation with the electron beam parameters constrained by the hard X-ray observations from Fermi/GBM. The result reveals that the white-light enhancement cannot be well explained by a pure electron-beam heating together with its induced radiative backwarming but may need additional heating sources such as \alfven\ waves.

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arXiv2023

What Images are More Memorable to Machines?

This paper studies the problem of measuring and predicting how memorable an image is to pattern recognition machines, as a path to explore machine intelligence. Firstly, we propose a self-supervised machine memory quantification pipeline, dubbed ``MachineMem measurer'', to collect machine memorability scores of images. Similar to humans, machines also tend to memorize certain kinds of images, whereas the types of images that machines and humans memorize are different. Through in-depth analysis and comprehensive visualizations, we gradually unveil that``complex" images are usually more memorable to machines. We further conduct extensive experiments across 11 different machines (from linear classifiers to modern ViTs) and 9 pre-training methods to analyze and understand machine memory. This work proposes the concept of machine memorability and opens a new research direction at the interface between machine memory and visual data.

cs.CV↗

arXiv2023

Winking filaments due to cyclic evaporation-condensation

Observations have shown that some filaments appear and disappear in the H$α$ line wing images periodically. There have been no attempts to model these "winking filaments" thus far. The evaporation--condensation mechanism is widely used to explain the formation of solar filaments. Here, we demonstrate, for the first time, how multi-dimensional evaporation--condensation in an arcade setup invariably causes a stretching of the magnetic topology. We aim to check whether this magnetic stretching during cyclic evaporation--condensation could reproduce a winking filament. We used our open-source code MPI-AMRVAC to carry out 2D magnetohydrodynamic simulations based on a quadrupolar configuration. A periodic localized heating, which modulates the evaporation--condensation process, was imposed before, during, and after the formation of the filament. Synthetic H$α$ and 304 Å, images were produced to compare the results with observations. For the first time, we noticed the winking filament phenomenon in a simulation of the formation of on-disk solar filaments, which was in good agreement with observations. Typically, the period of the winking is different from the period of the impulsive heating. A forced oscillator model explains this difference and fits the results well. A parameter survey is also done to look into details of the magnetic stretching phenomenon. We found that the stronger the heating or the higher the layer where the heating occurs, the more significant the winking effect appears.

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arXiv2022

Statistical analysis of the Si I 6560.58 Å line observed by CHASE

The Si I 6560.58 Å line in the H$α$ blue wing is blended with a telluric absorption line from water vapor in ground-based observations. Recent observations with the space-based telescope CHASE provide a new window to study this line. We aim to study the Si I line statistically and to explore possible diagnostics. We select three scannings in the CHASE observations, and measure the equivalent width (EW) and the full width at half maximum (FWHM) for each pixel on the solar disk. We then calculate the theoretical EW and FWHM from the VALC model. An active region is also studied in particular for difference in the quiet Sun and the sunspots. The Si I line is formed at the bottom of the photosphere. The EW of this line increases from the disk center to $μ$ = 0.2, and then decreases toward the solar limb, while the FWHM shows a monotonically increasing trend. Theoretically predicted EW agrees well with observations, while the predicted FWHM is far smaller due to the absence of unresolved turbulence in models. The macroturbulent velocity is estimated to be 2.80 km s$^{-1}$ at the disk center, and increases to 3.52 km s$^{-1}$ at $μ$ = 0.2. We do not find any response to flare heating in current observations. Doppler shifts and line widths of the Si I 6560.58 Å and Fe I 6569.21 Å lines can be used to study the mass flows and turbulence of the different photospheric layers. The Si I line has good potentials to diagnose the dynamics and energy transport in the photosphere.

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arXiv2022

Curved Geometric Networks for Visual Anomaly Recognition

Learning a latent embedding to understand the underlying nature of data distribution is often formulated in Euclidean spaces with zero curvature. However, the success of the geometry constraints, posed in the embedding space, indicates that curved spaces might encode more structural information, leading to better discriminative power and hence richer representations. In this work, we investigate benefits of the curved space for analyzing anomalies or out-of-distribution objects in data. This is achieved by considering embeddings via three geometry constraints, namely, spherical geometry (with positive curvature), hyperbolic geometry (with negative curvature) or mixed geometry (with both positive and negative curvatures). Three geometric constraints can be chosen interchangeably in a unified design given the task at hand. Tailored for the embeddings in the curved space, we also formulate functions to compute the anomaly score. Two types of geometric modules (i.e., Geometric-in-One and Geometric-in-Two models) are proposed to plug in the original Euclidean classifier, and anomaly scores are computed from the curved embeddings. We evaluate the resulting designs under a diverse set of visual recognition scenarios, including image detection (multi-class OOD detection and one-class anomaly detection) and segmentation (multi-class anomaly segmentation and one-class anomaly segmentation). The empirical results show the effectiveness of our proposal through the consistent improvement over various scenarios.

cs.CV↗

arXiv2022

Blind Image Decomposition

We propose and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that is, both the source components involved in mixing as well as the mixing mechanism are unknown. For example, rain may consist of multiple components, such as rain streaks, raindrops, snow, and haze. Rainy images can be treated as an arbitrary combination of these components, some of them or all of them. How to decompose superimposed images, like rainy images, into distinct source components is a crucial step toward real-world vision systems. To facilitate research on this new task, we construct multiple benchmark datasets, including mixed image decomposition across multiple domains, real-scenario deraining, and joint shadow/reflection/watermark removal. Moreover, we propose a simple yet general Blind Image Decomposition Network (BIDeN) to serve as a strong baseline for future work. Experimental results demonstrate the tenability of our benchmarks and the effectiveness of BIDeN.

cs.CV↗

arXiv2022

Imaging and Spectroscopic Observations of the Dynamic Processes in Limb Solar Flares

We investigate various dynamic processes including magnetic reconnection, chromospheric evaporation, and coronal rain draining in two limb solar flares through imaging and spectroscopic observations from the Interface Region Imaging Spectrograph (IRIS) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. In the early phase of the flares, a bright and dense loop-top structure with a cusp-like shape can be seen in multi-wavelength images, which is co-spatial with the hard X-ray 25--50 keV emission. In particular, intermittent magnetic reconnection downflows are detected in the time-space maps of AIA 304 Å. The reconnection downflows are manifested as redshifts on one half of the loops and blueshifts on the other half in the IRIS Si {\sc iv} 1393.76 Å line due to a projection effect. The Si {\sc iv} profiles exhibit complex features (say, multi-peak) with a relatively larger width at the loop-top region. During the impulsive phase, chromospheric evaporation is observed in both AIA images and the IRIS Fe {\sc xxi} 1354.08 Å line. Upward motions can be seen from AIA 131 Å images. The Fe {\sc xxi} line is significantly enhanced and shows a good Gaussian shape. In the gradual phase, warm rains are observed as downward moving plasmas in AIA 304 Å images. Both the Si {\sc iv} and Fe {\sc xxi} lines show a relatively symmetric shape with a larger width around the loop top. These results provide observational evidence for various dynamic processes involved in and are crucial to understand the energy release process of solar flares.

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arXiv2022

You Only Cut Once: Boosting Data Augmentation with a Single Cut

We present You Only Cut Once (YOCO) for performing data augmentations. YOCO cuts one image into two pieces and performs data augmentations individually within each piece. Applying YOCO improves the diversity of the augmentation per sample and encourages neural networks to recognize objects from partial information. YOCO enjoys the properties of parameter-free, easy usage, and boosting almost all augmentations for free. Thorough experiments are conducted to evaluate its effectiveness. We first demonstrate that YOCO can be seamlessly applied to varying data augmentations, neural network architectures, and brings performance gains on CIFAR and ImageNet classification tasks, sometimes surpassing conventional image-level augmentation by large margins. Moreover, we show YOCO benefits contrastive pre-training toward a more powerful representation that can be better transferred to multiple downstream tasks. Finally, we study a number of variants of YOCO and empirically analyze the performance for respective settings. Code is available at GitHub.

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arXiv2022

Calibration procedures for the CHASE/HIS science data

The Hα line is an important optical line in solar observations containing the information from the photosphere to the chromosphere. To study the mechanisms of solar eruptions and the plasma dynamics in the lower atmosphere, the Chinese Hα Solar Explorer (CHASE) was launched into a Sun-synchronous orbit on October 14, 2021. The scientific payload of the CHASE satellite is the Hα Imaging Spectrograph (HIS). The CHASE/HIS acquires, for the first time, seeing-free Hα spectroscopic observations with high spectral and temporal resolutions. It consists of two observational modes. The raster scanning mode provides full-Sun or region-of-interest spectra at Hα (6559.7-6565.9 Å) and Fe I (6567.8-6570.6 Å) wavebands. The continuum imaging mode obtains full-Sun photospheric images at around 6689 Å. In this paper, we present detailed calibration procedures for the CHASE/HIS science data, including the dark-field and flat-field correction, slit image curvature correction, wavelength and intensity calibration, and coordinate transformation. The higher-level data products can be directly used for scientific research.

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arXiv2022

Towards Open-Set Object Detection and Discovery

With the human pursuit of knowledge, open-set object detection (OSOD) has been designed to identify unknown objects in a dynamic world. However, an issue with the current setting is that all the predicted unknown objects share the same category as "unknown", which require incremental learning via a human-in-the-loop approach to label novel classes. In order to address this problem, we present a new task, namely Open-Set Object Detection and Discovery (OSODD). This new task aims to extend the ability of open-set object detectors to further discover the categories of unknown objects based on their visual appearance without human effort. We propose a two-stage method that first uses an open-set object detector to predict both known and unknown objects. Then, we study the representation of predicted objects in an unsupervised manner and discover new categories from the set of unknown objects. With this method, a detector is able to detect objects belonging to known classes and define novel categories for objects of unknown classes with minimal supervision. We show the performance of our model on the MS-COCO dataset under a thorough evaluation protocol. We hope that our work will promote further research towards a more robust real-world detection system.

cs.CV↗

arXiv2022

GOSS: Towards Generalized Open-set Semantic Segmentation

In this paper, we present and study a new image segmentation task, called Generalized Open-set Semantic Segmentation (GOSS). Previously, with the well-known open-set semantic segmentation (OSS), the intelligent agent only detects the unknown regions without further processing, limiting their perception of the environment. It stands to reason that a further analysis of the detected unknown pixels would be beneficial. Therefore, we propose GOSS, which unifies the abilities of two well-defined segmentation tasks, OSS and generic segmentation (GS), in a holistic way. Specifically, GOSS classifies pixels as belonging to known classes, and clusters (or groups) of pixels of unknown class are labelled as such. To evaluate this new expanded task, we further propose a metric which balances the pixel classification and clustering aspects. Moreover, we build benchmark tests on top of existing datasets and propose a simple neural architecture as a baseline, which jointly predicts pixel classification and clustering under open-set settings. Our experiments on multiple benchmarks demonstrate the effectiveness of our baseline. We believe our new GOSS task can produce an expressive image understanding for future research. Code will be made available.

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arXiv2022

An approximate recipe of chromospheric radiative losses for solar flares

Radiative losses in the chromosphere are very important in the energy balance. There have been efforts to make simple lookup tables for chromospheric radiative losses in the quiet Sun. During solar flares, the atmospheric conditions are quite different, and the currently available recipe of Gan & Fang (1990) is constructed from semi-empirical models. It remains to be evaluated how these recipes work in flare conditions. We aim to construct an approximate recipe of chromospheric radiative losses for solar flares. We follow the method of Carlsson & Leenaarts (2012) to tabulate the optically thin radiative loss, escape probability, and ionization fraction, while using a grid of flare models from radiative hydrodynamic simulations as our dataset. We provide new lookup tables to calculate chromospheric radiative losses for flares. Compared with previous recipes, our recipe provides a better approximation to the detailed radiative losses for flares.

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arXiv2022

Diagnosing the Optically Thick/Thin Features Using the Intensity Ratio of Si IV Resonance Lines in Solar Flares

In the optically thin regime, the intensity ratio of the two Si IV resonance lines (1394 and 1403 Å ) are theoretically the same as the ratio of their oscillator strengths, which is exactly 2. Here, we study the ratio of the integrated intensity of the Si IV lines ($R=\int I_{1394}(λ)\mathrm{d}λ/\int I_{1403}(λ)\mathrm{d}λ$) and the ratio of intensity at each wavelength point ($r(Δλ)=I_{1394}(Δλ)/I_{1403}(Δλ)$) in two solar flares observed by the Interface Region Imaging Spectrograph. We find that at flare ribbons, the ratio $R$ ranges from 1.8 to 2.3 and would generally decrease when the ribbons sweep across the slit position. Besides, the distribution of $r(Δλ)$ shows a descending trend from the blue wing to the red wing. In loop cases, the Si IV line presents a wide profile with a central reversal. The ratio $R$ deviates little from 2, but the ratio $r(Δλ)$ can vary from 1.3 near the line center to greater than 2 in the line wings. Hence we conclude that in flare conditions, the ratio $r(Δλ)$ varies across the line, due to the variation of the opacity at the line center and line wings. We notice that, although the ratio $r(Δλ)$ could present a value which deviates from 2 as a result of the opacity effect near the line center, the ratio $R$ is still close to 2. Therefore, caution should be taken when using the ratio of the integrated intensity of the Si IV lines to diagnose the opacity effect.

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arXiv2021

Revisiting the Spectral Features of Ellerman Bombs and UV Bursts. I. Radiative Hydrodynamic Simulations

Ellerman bombs (EBs) and UV bursts are both small-scale solar activities that occur in active regions. They are now believed to form at different heights in the lower atmosphere. In this paper, we use one-dimensional radiative hydrodynamic simulations to calculate various line profiles in response to heating in different atmospheric layers. We confirm that heating in the upper photosphere to the lower chromosphere can generate spectral features of typical EBs, while heating in the mid to upper chromosphere can generate spectral features of typical UV bursts. The intensity evolution of the H$α$ line wing in EBs shows a rise--plateau pattern, while that of the Si IV 1403 Å line center in UV bursts shows a rise--fall pattern. However, the predicted enhancement of FUV continuum near 1400 Å for EBs is rarely reported and requires further observations to check it. With two heating sources or an extended heating source in the atmosphere, both EB and UV burst features could be reproduced simultaneously.

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arXiv2021

Reinforced Attention for Few-Shot Learning and Beyond

Few-shot learning aims to correctly recognize query samples from unseen classes given a limited number of support samples, often by relying on global embeddings of images. In this paper, we propose to equip the backbone network with an attention agent, which is trained by reinforcement learning. The policy gradient algorithm is employed to train the agent towards adaptively localizing the representative regions on feature maps over time. We further design a reward function based on the prediction of the held-out data, thus helping the attention mechanism to generalize better across the unseen classes. The extensive experiments show, with the help of the reinforced attention, that our embedding network has the capability to progressively generate a more discriminative representation in few-shot learning. Moreover, experiments on the task of image classification also show the effectiveness of the proposed design.

cs.CV↗

arXiv2020

The Lyman-alpha Emission in Solar Flares. I. a Statistical Study on Its Relationship with the 1--8 Å Soft X-ray Emission

We statistically study the relationship between the Lyman-alpha (\lya) and 1--8 Å soft X-ray (SXR) emissions from 658 M- and X-class solar flares observed by the {\em Geostationary Operational Environmental Satellite} during 2006--2016. Based on the peak times of the two waveband emissions, we divide the flares into three types. Type I (III) has an earlier (a later) peak time in the \lya\ emission than that in the SXR emission, while type II has nearly a same peak time (within the time resolution of 10 s) between the \lya\ and SXR emissions. In these 658 flares, we find that there are 505 (76.8\%) type I flares, 10 (1.5\%) type II flares, and 143 (21.7\%) type III flares, and that the three types appear to have no dependence on the flare duration, flare location, or solar cycle. Besides the main peak, the \lya\ emission of the three type flares also shows sub-peaks which can appear in the impulsive or gradual phase of the flare. It is found that the main-peak (for type I) and sub-peak (for type III) emissions of \lya\ that appear in the impulsive phase follow the Neupert effect in general. This indicates that such \lya\ emissions are related to the nonthermal electron beam heating. While the main-peak (for type III) and sub-peak (for type I) emissions of \lya\ that appear in the gradual phase are supposed to be primarily contributed by the thermal plasma that cools down.

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arXiv2020

Spectroscopic Observations of High-speed Downflows in a C1.7 Solar Flare

In this paper, we analyze the high-resolution UV spectra for a C1.7 solar flare (SOL2017-09-09T06:51) observed by the \textit{Interface Region Imaging Spectrograph} (\textit{IRIS}). {We focus on the spectroscopic observations at the locations where the cool lines of \ion{Si}{4} 1402.8 Å ($\sim$10$^{4.8}$ K) and \ion{C}{2} 1334.5/1335.7 Å ($\sim$10$^{4.4}$ K) reveal significant redshifts with Doppler velocities up to $\sim$150 km s$^{-1}$.} These redshifts appear in the rise phase of the flare, then increase rapidly, reach the maximum in a few minutes, and proceed into the decay phase. Combining the images from \textit{IRIS} and Atmospheric Imaging Assembly (AIA) on board the {\em Solar Dynamics Observatory} ({\em SDO}), we propose that the redshifts in the cool lines are caused by the downflows in the transition region and upper chromospheric layers, which likely result from a magnetic reconnection leading to the flare. In addition, the cool \ion{Si}{4} and \ion{C}{2} lines show gentle redshifts (a few tens of km s$^{-1}$) at some other locations, which manifest some distinct features from the above locations. This is supposed to originate from a different physical process.

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arXiv2020

Radiative Hydrodynamic Simulations of the Spectral Characteristics of Solar White-light Flares

As one of the most violent activities in the solar atmosphere, white-light flares (WLFs) are generally known for their enhanced white-light (or continuum) emission, which primarily originates in the solar lower atmosphere. However, we know little about how white-light emission is produced. In this study, we aim to investigate the response of the continua at 3600Å and 4250Å and also the H$α$ and Ly$α$ lines during WLFs modeled with radiative hydrodynamics simulations. We take non-thermal electron beams as the energy source for the WLFs in two different initial atmospheres and vary their parameters. Our results show that the model with non-thermal electron beam heating can clearly show enhancements in the continua at 3600Å and 4250Å as well as in the H$α$ and Ly$α$ lines. A larger electron beam flux, a smaller spectral index, or a penumbral initial atmosphere leads to a stronger emission increase at 3600Å, 4250Å and in the H$α$ line. For the Ly$α$ line, however, it is more preferably enhanced in a quiet-Sun initial atmosphere with a larger spectral index of the electron beam. It is also notable that the continua at 3600Å and 4250Å and the H$α$ line exhibit a dimming at the beginning of the heating and reach their peak emissions later than the peak time of the heating function, while the Ly$α$ line does not show such behaviors. These results can be served as a reference for analyzing future WLF observations.

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