arXiv subjects

Q. Hao

Publications and source records attributed to Q. Hao.

At least 19 recordsLinked to original sources

arXiv2026

The SPT-3G+ receiver design

We present the thermo-mechanical design of the cryostat and camera optics for SPT-3G+, a new receiver being developed for the South Pole Telescope (SPT). The receiver consists of 14 detector arrays of 90/150 GHz dichroic polarization-sensitive pixels, totaling 24,080 transition-edge sensor detectors. Each detector array lies at the end of an optics tube, each approximately 240 mm in diameter and 772 mm in length, which are arranged in a hexagonal close-packed configuration to achieve a 4 degree diameter field of view. Each optics tube contains four anti-reflection coated lenses fabricated from different materials (alumina, silicon, and nylon) that are designed to also provide infrared filtering that reduces the radiative loading on the cryogenic stages. The optics and detectors are cooled by a combination of a pulse tube cooler for the 40 K and 4 K stages, and a dilution refrigerator for the 1 K and 100 mK stages. Thermal modeling predicts the heat load to be less than 26 W and 1 W for the 40 K and 4 K stages, respectively. The 1,550 kg cryostat has a 1.1 meter diameter at the vacuum window, which is located near the telescope Gregorian focus, and 1.75 meters in height and length. Fabrication of the cryostat will begin in 2026, with installation on the SPT scheduled for the 2028-29 austral summer, ahead of the 2029 winter observing season.

astro-ph.IM↗

arXiv2026

SPT-3G+: A Cosmic Microwave Background Experiment for the South Pole Telescope

SPT-3G+ is the next survey receiver planned to be installed in early 2029 on the 10-meter South Pole Telescope (SPT). This new receiver will feature 6,020 polarization-sensitive dichroic pixels with transition-edge sensors observing in frequency bands centered at 90 GHz and 150 GHz. The 24,080 detectors in the SPT-3G+ receiver will be cooled to 100 mK by a dilution refrigerator and read out using microwave SQUID multiplexing. The optical design of the receiver enables a 4 degree diameter field of view, which is broken up into 14 individual optics tubes each containing cryogenic alumina, silicon, and nylon lenses. These technology choices will allow the SPT-3G+ receiver to improve on the mapping speed of the currently operating SPT-3G receiver by nearly an order of magnitude. Once deployed, the SPT-3G+ receiver will observe for 6-years an area overlapping with the BICEP survey to achieve a combined (90 GHz and 150 GHz) CMB map depth of 0.5 uK-arcmin. Data from these observations will be used to create unprecedentedly deep CMB lensing maps, discover new galaxy clusters, and detect astrophysical transients. The lensing map produced by SPT-3G+ will be used to remove or "delens" foreground B modes, where large-scale structure gravitationally lenses the CMB and converts E modes into B-mode polarization, with the goal of revealing inflationary B modes. Together with data from the BICEP Array as part of the South Pole Observatory, SPT-3G+ data will be used to constrain the tensor-to-scalar ratio $r$ with a goal of achieving a measurement of $\sigma(r) = 0.001$

astro-ph.CO↗

arXiv2026

Statistics of Solar Filament Mass based on CHASE Sun-as-a-star Spectroscopic Observations

Filaments are cool and dense plasmas suspended in the hot corona of the Sun and other stars. Accurately estimating their masses is of great significance for understanding subsequent eruptions and induced space weather effects, but it remains hindered by their intrinsic geometric uncertainties, particularly in spatially unresolved stellar observations. To test and calibrate the methods for estimating the masses of stellar filaments, we conduct a statistical Sun-as-a-star analysis of solar filaments, utilizing full-disk H$\alpha$ spectroscopic observations from the Chinese H$\alpha$ Solar Explorer (CHASE). A total of 1346 filaments, covering a period from January 2024 to October 2025, are identified via a machine-learning segmentation model. We construct their virtual sun-as-a-star spectra by spatially integrating the filament regions and then obtain their optical parameters by cloud-model fitting. Upon correcting projection effects, we establish a representative three-dimensional morphological scaling of length, apparent width, and line-of-sight depth ($L:W_{\rm app}:D_{\rm LOS} \approx 4.5:1:1.7$), with a median filament depth of about 8000 km. Interestingly, the Sun-as-a-star estimated mass shows high consistency with the resolved intrinsic mass across the full sample, with a log-space regression slope of 1.07. As the first large-sample Sun-as-a-star study of solar filaments, our results provide empirical constraints on filament geometries and masses, offering a critical reference for estimating stellar filament masses based on H$\alpha$ spectroscopy.

astro-ph.SR↗

arXiv2026

A Modern ConvNet for Solar Filament Detection

Automated solar filament detection using deep learning faces several challenges. Semantic segmentation of solar filaments is a complicated multiscale feature extraction task with long-tail distribution. Furthermore, a large-scale, highly complete, and finely detailed dataset has become mandatory for providing abundant information. To address these challenges, we present a series of machine learning approaches to develop a solar filament detection workflow that performs superbly. First, we manually annotated a small-scale solar filament dataset based on H$\alpha$ spectra called MHAS. Next, we developed the Multiscale ORiented DENdritic (MORDEN) model, a semantic segmentation model focusing on multiscale feature extraction. We also introduced the Dense Conditional Random Field (DenseCRF) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) methods for post-processing. Using the proposed workflow, we generated a large-scale, high-quality dataset called AHAS. Experimental results demonstrate that MORDEN outperforms several existing solar filament semantic segmentation models with open access. DenseCRF has been demonstrated to effectively capture fine edge details. We also evaluated the effects of data scaling and the reliability of DBSCAN and found that both approaches yield satisfactory performance. Multiple visualization results substantiate our quantitative findings. Our work provides a foundation for maximizing the potential of deep learning models for solar filament detection.

astro-ph.SR↗

arXiv2026

Explainable AI for Solar Flare Prediction: Quantitative Magnetic Field Analysis of Model-Focused Regions

Solar flares are intense energy release events in the solar atmosphere that may pose significant space weather hazards, which makes developing reliable prediction models essential. Although deep learning methods, particularly convolutional neural networks (CNNs), demonstrate strong predictive performance when using solar magnetograms, their scientific credibility is undermined by a lack of physical interpretability. Explainable artificial intelligence (XAI) offers a potential solution. However, current XAI studies in solar flare prediction are largely qualitative and lack systematic, theory-based, quantitative validation. We present a quantitative XAI framework that can decipher the physical basis of CNN-based solar flare prediction models. Using gradient-weighted class activation mapping (Grad-CAM), we identify model-focused regions (MFRs) in solar magnetograms. Then, we perform two key analyses to evaluate the predictive capability of magnetic parameters derived from MFRs and to quantitatively characterize their magnetic complexity. Our results reveal a strong physical correlation between MFRs and flare occurrence. Specifically, magnetic features extracted from MFRs demonstrate high predictive power for flares. Flare-producing active regions are characterized by magnetically complex configurations that are dominated by a single polarity rather than by balanced or purely unipolar structures. This finding is consistent with established physical theories of magnetic systems prone to flares. Our results suggest that CNNs can learn physically meaningful representations when trained on large-scale observations. Integrating XAI with quantitative magnetic field analysis improves the physical interpretability of deep learning-based flare prediction models, making them useful tools for prediction and modeling investigation in solar physics.

astro-ph.SR↗

arXiv2026

Inversion of CHASE H$\alpha$ Spectral Line during Solar Flares Based on RADYN Dataset via Deep Learning

Solar flares represent one of the most intense forms of solar activity. Understanding the evolution of physical parameters in the solar atmosphere during flares is key to studying flare mechanisms and improving prediction capabilities. However, directly measuring quantities such as electron number density, temperature, and plasma velocity remains difficult. Here, we introduce a novel fully connected neural network, trained on synthetic data from the Radiative Hydrodynamics Code (RADYN) simulations, to perform rapid inversion of physical parameters from H$\alpha$ spectral profiles. The spectral data were processed to align with the observational resolution of the CHASE satellite, enabling seamless application of the model to real-world observations. Results demonstrate a high degree of consistency with RADYN simulations, achieving low errors under diverse flare conditions. Furthermore, we applied the developed model to analyze CHASE observations of a class X7.1 solar flare on October 1, 2024. The results reveal reasonable spatial and temporal evolution of key parameters throughout different flare phases. This work demonstrates the potential of deep learning techniques for fast and reliable spectral inversion, providing new tools for solar flare diagnostics based on H$\alpha$ data.

astro-ph.SR↗

arXiv2026

An Improved HDBSCAN-based Detection and Tracking Method for Solar Active Regions in Magnetograms

Solar active regions (ARs) are the primary source of solar eruptions and space weather. Accurate detection and tracking of ARs is crucial for understanding their evolution and predicting solar activities. In the previous work, based on the density-based spatial clustering of applications with noise (DBSCAN) approach, we proposed the DBSCAN-based solar active region detection (DSARD) framework. To overtake its limitations, in this paper we applied the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) approach to the detection of solar active regions, which is called the HDBSCAN-based solar active region detection and tracking (HARDAT) method. This enables the algorithm to handle multi-density magnetic structures dynamically, eliminating the need for fixed thresholds. Consequently, the algorithm can detect diffuse and small ARs more effectively while preserving morphological integrity. We have also developed a solar differential rotation based tracking algorithm that integrates physical motion models and Hamming distance similarity metrics to achieve robust multi-object tracking. Additionally, we propose a novel polarity inversion line extraction method that uses support vector classification, which offers superior generalization for complex AR boundaries. Processing line-of-sight magnetograms from SOHO/MDI (1996--2011) and SDO/HMI (2010--2024) and evaluating them against the National Oceanic and Atmospheric Administration (NOAA) and DSARD catalogues demonstrates that HARDAT is superior in terms of sensitivity, accuracy, and stability of detection and tracking. This is particularly evident when resolving clustered ARs and maintaining identity continuity. HARDAT therefore offers a comprehensive solution for the long-term analysis of AR evolution and space weather prediction.

astro-ph.SR↗

arXiv2025

Simultaneous Superconducting and Topological Properties in Mg-Li Electrides at High Pressures

Electrides as a unique class of emerging materials exhibit fascinating properties and hold important significance for understanding the matter under extreme conditions, which is characterized by valence electrons localized into the interstitial space as quasi-atoms (ISQs). In this work, using crystal structure prediction and first-principles calculations, we identified seven stable phases of Mg-Li that are electride with novel electronic properties under high pressure. Among them, MgLi10 is a semiconductor with a band gap of 0.22 eV; and Pm-3m MgLi is superconductor with a superconducting transition temperature of 22.8 K. The important role played by the localization degree of ISQ in the superconducting transition temperature of these electrides is revealed by systematic comparison of Mg-Li with other Li-rich electride superconductors. Furthermore, we proved that Pm-3m MgLi and Pnma MgLi also have distinct topological behavior with metallic surface states and the non-zero $Z_2$ invariant. The simultaneous coexistence of superconductivity, electronic band topology and electride property in the same structure of Pm-3m MgLi and Pnma MgLi demonstrates the feasibility of realizing multi-quantum phases in a single material, which will stimulate further research in these interdisciplinary fields.

cond-mat.mtrl-sci↗

arXiv2024

Developing an Automated Detection, Tracking and Analysis Method for Solar Filaments Observed by CHASE via Machine Learning

Studies on the dynamics of solar filaments have significant implications for understanding their formation, evolution, and eruption, which are of great importance for space weather warning and forecasting. The H$α$ Imaging Spectrograph (HIS) onboard the recently launched Chinese H$α$ Solar Explorer (CHASE) can provide full-disk solar H$α$ spectroscopic observations, which bring us an opportunity to systematically explore and analyze the plasma dynamics of filaments. The dramatically increased observation data require automate processing and analysis which are impossible if dealt with manually. In this paper, we utilize the U-Net model to identify filaments and implement the Channel and Spatial Reliability Tracking (CSRT) algorithm for automated filament tracking. In addition, we use the cloud model to invert the line-of-sight velocity of filaments and employ the graph theory algorithm to extract the filament spine, which can advance our understanding of the dynamics of filaments. The favorable test performance confirms the validity of our method, which will be implemented in the following statistical analyses of filament features and dynamics of CHASE/HIS observations.

astro-ph.SR↗

arXiv2024

Statistical Analyses of Solar Prominences and Active Region Features in 304 Å Filtergrams detected via Deep Learning

Solar active regions (ARs) are areas on the Sun with very strong magnetic fields where various activities take place. Prominences are one of the typical solar features in the solar atmosphere, whose eruptions often lead to solar flares and coronal mass ejections (CMEs). Therefore, studying their morphological features and their relationship with solar activity is useful in predicting eruptive events and in understanding the long-term evolution of solar activities. A huge amount of data have been collected from various ground-based telescopes and satellites. The massive data make human inspection difficult. For this purpose, we developed an automated detection method for prominences and ARs above the solar limb based on deep learning techniques. We applied it to process the 304 Ådata obtained by SDO/AIA from 2010 May 13 to 2020 December 31. Besides the butterfly diagrams and latitudinal migrations of the prominences and ARs during solar cycle 24, the variations of their morphological features (such as the locations, areas, heights, and widths) with the calendar years and the latitude bands were analyzed. Most of these statistical results based on our new method are in agreement with previous studies, which also guarantees the validity of our method. The N-S asymmetry indices of the prominences and ARs show that the northern hemisphere dominates in solar cycle 24, except for 2012--2015, and 2020 for ARs. The high-latitude prominences show much stronger N-S asymmetry that the northern hemisphere is dominant in $\sim$2011 and $\sim$2015 and the southern hemisphere is dominant during 2016--2019.

astro-ph.SR↗

arXiv2023

The FAST all sky HI survey (FASHI): The first release of catalog

The FAST All Sky HI survey (FASHI) was designed to cover the entire sky observable by the Five-hundred-meter Aperture Spherical radio Telescope (FAST), spanning approximately 22000 square degrees of declination between -14 deg and +66 deg, and in the frequency range of 1050-1450 MHz, with the expectation of eventually detecting more than 100000 HI sources. Between August 2020 and June 2023, FASHI had covered more than 7600 square degrees, which is approximately 35% of the total sky observable by FAST. It has a median detection sensitivity of around 0.76 mJy/beam and a spectral line velocity resolution of ~6.4 km/s at a frequency of ~1.4 GHz. As of now, a total of 41741 extragalactic HI sources have been detected in the frequency range 1305.5-1419.5 MHz, corresponding to a redshift limit of z<0.09. By cross-matching FASHI sources with the Siena Galaxy Atlas (SGA) and the Sloan Digital Sky Survey (SDSS) catalogs, we found that 16972 (40.7%) sources have spectroscopic redshifts and 10975 (26.3%) sources have only photometric redshifts. Most of the remaining 13794 (33.0%) HI sources are located in the direction of the Galactic plane, making their optical counterparts difficult to identify due to high extinction or high contamination of Galactic stellar sources. Based on current survey results, the FASHI survey is an unprecedented blind extragalactic HI survey. It has higher spectral and spatial resolution and broader coverage than the Arecibo Legacy Fast ALFA Survey (ALFALFA). When completed, FASHI will provide the largest extragalactic HI catalog and an objective view of HI content and large-scale structure in the local universe.

astro-ph.GA↗

arXiv2021

Fast digital refocusing and depth of field extended Fourier ptychography microscopy

Fourier ptychography microscopy (FPM), sharing its roots with synthetic aperture technique and phase retrieval method, is a recently developed computational microscopic super-resolution technique. By turning on the light-emitting diode (LED) elements sequentially and acquiring the corresponding images that contain different spatial frequencies, FPM can achieve a wide field-of-view (FOV), high-spatial-resolution imaging, and phase recovery simultaneously. Conventional FPM assumes that the sample is sufficiently thin and strictly in focus. Nevertheless, even for a relatively thin sample, the non-planar distribution characteristics and the non-ideal position/posture of the sample will cause all or part of FOV to be defocused. In this paper, we proposed a fast digital refocusing and depth-of-field (DOF) extended FPM strategy by taking the advantages of image lateral shift caused by sample defocusing and varied-angle illuminations. The lateral shift amount is proportional to the defocus distance and the tangent of the illumination angle. Instead of searching the optimal defocus distance in optimization strategy, which is time-consuming, the defocus distance of each subregion of the sample can be precisely and quickly obtained by calculating the relative lateral shift amounts corresponding to different oblique illuminations. And then, the digital refocusing strategy rooting in the Fresnel propagator is integrated into the FPM framework to achieve the high-resolution and phase information reconstruction for each part of the sample, which means the DOF the FPM is effectively extended. The feasibility of the proposed method in fast digital refocusing and FOV extending is verified in the actual experiments with the USAF chart and biological samples.

physics.optics↗

arXiv2020

Spectral Diagnostics of Solar Photospheric Bright Points

By use of the high-resolution spectral data and the broadband imaging obtained with the Goode Solar Telescope at the Big Bear Solar Observatory on 2013 June 6, the spectra of three typical photospheric bright points (PBPs) have been analyzed. Based on the H$α$ and Ca II 8542 Åline profiles, as well as the TiO continuum emission, for the first time, the non-LTE semi-empirical atmospheric models for the PBPs are computed. The attractive characteristic is the temperature enhancement in the lower photosphere. The temperature enhancement is about 200 -- 500 K at the same column mass density as in the atmospheric model of the quiet-Sun. The total excess radiative energy of a typical PBP is estimated to be 1$\times$10$^{27}$ - 2$\times$10$^{27}$ ergs, which can be regarded as the lower limit energy of the PBPs. The radiation flux in the visible continuum for the PBPs is about 5.5$\times$10$^{10}$ ergs cm$^{-2}$ s$^{-1}$. Our result also indicates that the temperature in the atmosphere above PBPs is close to that of a plage. It gives a clear evidence that PBPs may contribute significantly to the heating of the plage atmosphere. Using our semi-empirical atmospheric models, we estimate self-consistently the average magnetic flux density $B$ in the PBPs. It is shown that the maximum value is about one kilo-Gauss, and it decreases towards both higher and lower layers, reminding us of the structure of a flux tube between photospheric granules.

astro-ph.SR↗

arXiv2018

Transition from circular-ribbon to parallel-ribbon flares associated with a bifurcated magnetic flux rope

Magnetic flux ropes play a key role in triggering solar flares in the solar atmosphere. In this paper, we investigate the evolution of active region NOAA 12268 within 36 hours from 2015 January 29 to 30, during which a flux rope was formed and three M-class and three C-class flares were triggered without coronal mass ejections. During the evolution of the active region, the flare emission seen in the H$α$ and ultraviolet wavebands changed from a circular shape (plus an adjacent conjugated ribbon and a remote ribbon) to three relatively straight and parallel ribbons. Based on a series of reconstructed nonlinear force-free fields, we find sheared or twisted magnetic field lines and a large-scale quasi-separatrix layer (QSL) associated with 3D null points in a quadrupolar magnetic field. These features always existed and constantly evolved during the two days. The twist of the flux rope was gradually accumulated that eventually led to its instability. Around the flux rope, there were some topological structures, including a bald patch, a hyperbolic flux tube and a torus QSL. We discuss how the particular magnetic structure and its evolution produce the flare emission. In particular, the bifurcation of the flux rope can explain the transition of the flares from circular to parallel ribbons. We propose a two-stage evolution of the magnetic structure and its associated flares. In the first stage, sheared arcades under the dome-like large-scale QSL were gradually transformed into a flux rope through magnetic reconnection, which produced the circular ribbon flare. In the second stage, the flux rope bifurcated to form the three relatively straight and parallel flare ribbons.

astro-ph.SR↗

arXiv2018

Automated Detection Methods for Solar Activities and an Application for Statistic Analysis of Solar Filament

With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order to derive the features of interest in the observations. A number of automated detection methods and algorithms have been developed for solar activities, based on the image processing and machine learning techniques. In this paper, after briefly reviewing some automated detection methods, we describe our efficient and versatile automated detection method for solar filaments. It is able not only to recognize filaments, determine the features such as the position, area, spine, and other relevant parameters, but also to trace the daily evolution of the filaments. It is applied to process the full disk H-alpha data observed in nearly three solar cycles, and some statistic results are presented.

astro-ph.SR↗

arXiv2017

A Circular White-Light Flare with Impulsive and Gradual White-Light Kernels

White-light flares are the flares with emissions visible in the optical continuum. They are thought to be rare and pose the most stringent requirements in energy transport and heating in the lower atmosphere. Here we present a nearly circular white-light flare on 2015 March 10 that was well observed by the Optical and Near-infrared Solar Eruption Tracer and Solar Dynamics Observatory. In this flare, there appear simultaneously both impulsive and gradual white-light kernels. The generally accepted thick-target model would be responsible for the impulsive kernels but not sufficient to interpret the gradual kernels. Some other mechanisms including soft X-ray backwarming or downward-propagating Alfven waves, acting jointly with electron beam bombardment, provide a possible interpretation. However, the origin of this kind of white-light kernels is still an open question that induces more observations and researches in the future to decipher it.

astro-ph.SR↗

arXiv2017

Can the temperature of Ellerman Bombs be more than 10000K?

Ellerman bombs (EBs) are small brightening events in the solar lower atmosphere. By original definition, the main EB's characteristic is the two emission bumps in both wings of chromospheric lines, such as H$α$ and Ca II 8542 Å lines. Up to now, most authors found that the temperature increase of EBs around the temperature minimum region is in the range of 600K-3000K. However, with recent IRIS observations, some authors proposed that the temperature increase of EBs could be more than 10000K. Using non-LTE semi-empirical modeling, we investigate the line profiles, continuum emission and the radiative losses for the EB models with different temperature increases, and compare them with observations. Our result indicates that if the EB maximum temperature attains more than 10000K around the temperature minimum region, then the resulted H$α$ and Ca II 8542 Å line profiles and the continuum emission would be much stronger than that of EB observations. Moreover, due to the high radiative losses, the high temperature EB would have a very short lifetime, which is not comparable with the observations. Thus, our study does not support the proposal that the EB temperatures are higher than 10000K.

astro-ph.SR↗

arXiv2017

Material supply and magnetic configuration of an active region filament

It is important to study the fine structures of solar filaments with high-resolution observations since it can help us understand the magnetic and thermal structures of the filaments and their dynamics. In this paper, we study a newly-formed filament located inside the active region NOAA 11762, which was observed by the 1.6 m New Solar Telescope (NST) at Big Bear Solar Observatory (BBSO) from 16:40:19 UT to 17:07:58 UT on 2013 June 5. As revealed by the H$α$ filtergrams, cool material is seen to be injected into the filament spine with a speed of 5--10 km s$^{-1}$. At the source of the injection, brightenings are identified in the chromosphere, which is accompanied by magnetic cancellation in the photosphere, implying the importance of magnetic reconnection in replenishing the filament with plasmas from the lower atmosphere. Counter-streamings are detected near one endpoint of the filament, with the plane-of-the-sky speed being 7--9 km s$^{-1}$ in the H$α$ red-wing filtergrams and 9--25 km s$^{-1}$ in the blue-wing filtergrams. The observations are indicative of that this active region filament is supported by a sheared arcade without magnetic dips, and the counter-streamings are due to unidirectional flows with alternative directions, rather than due to the longitudinal oscillations of filament threads as in many other filaments.

astro-ph.SR↗