arXiv subjects

Z. Zheng

Publications and source records attributed to Z. Zheng.

At least 19 recordsLinked to original sources

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

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample.

astro-ph.CO↗

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

Learning quantum disentanglement scheduling from reduced states via modular hybrid policies

Quantum control with restricted state access is central to near-term quantum devices, where full wave-function information is unavailable. We study this problem through multiqubit disentanglement scheduling from partial observations, where a controller receives only two-qubit reduced density matrices and selects which qubit pair to disentangle at each step. We introduce a modular hybrid quantum--classical policy framework consisting of classical preprocessing, a parameterized quantum circuit as a compact nonlinear latent block, and classical postprocessing for pair-selection probabilities. Benchmarking 4-, 5-, and 6-qubit tasks, we find that preprocessing is the dominant factor governing performance under reduced-state observations, while the quantum module provides a conditional compact representation whose utility depends on the input features and model budget. We further identify a performance--efficiency trade-off across policy families and find that increasing circuit width is generally more useful than increasing depth. These results provide practical design principles for hybrid policies in reduced-information quantum control.

quant-ph↗

arXiv2025

DESI Emission-line Galaxies: Clustering Dependence on Stellar Mass and [OII] Luminosity

We measure the projected two-point correlation functions of emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey and model their dependence on stellar mass and [OII] luminosity. We select $\sim$180,000 ELGs with redshifts of $0.8 < z < 1.6$ and define 27 samples according to cuts in redshift and both galaxy properties. Following a framework that describes the conditional [OII] luminosity-stellar mass distribution as a function of halo mass, we simultaneously model the clustering measurements of all samples at fixed redshift. Based on the modeling result, most ELGs in our samples are classified as central galaxies, residing in halos of a narrow mass range with a typical median of $\sim$10$^{12.2-12.4}$ $h^{-1} M_\odot$. We observe a weak dependence of clustering amplitude on stellar mass, which is reflected in the model constraints and is likely a consequence of the 0.5 dex measurement uncertainty in the stellar mass estimates. The model shows a trend between galaxy bias and [OII] luminosity at high redshift ($1.2 < z < 1.6$) that is otherwise absent at lower redshifts.

astro-ph.GA↗

arXiv2024

A resolved Lyman-Alpha profile with doubly peaked emission at z~7

The epoch of reionization is a landmark in structure formation and galaxy evolution. How it happened is still not clear, especially regarding which population of objects was responsible for contributing the bulk of ionizing photons toward this process. Doubly-peaked Lyman-Alpha profiles in this epoch are of particular interest since they hold information about the escape of ionizing radiation and the environment surrounding the source. We wish to understand the escape mechanisms of ionizing radiation in Lyman-Alpha emitters during this time and the origin of a doubly-peaked Lyman-alpha profile as well as estimating the size of a potential ionized bubble. Using radiative transfer models, we fit the line profile of a bright Lyman-Alpha emitter at $z\sim 6.9$ using various gas geometries. The line modeling reveals significant radiation escape from this system. While the studied source reveals significant escape ($f_{esc}$(LyA) $\sim0.8$ as predicted by the best fitting radiative transfer model) and appears to inhabit an ionized bubble of radius $R_{b}\approx 0.8^{+0.5}_{-0.3}\,pMpc\left(\frac{t_{\rm age}}{10^{8}}\right)^{\frac{1}{3}}$.Radiative transfer modeling predicts the line to be completely redwards of the systemic redshift. We suggest the line morphology is produced by inflows, multiple components emitting Ly$\alpha$, or by an absorbing component in the red wing. We propose that CDFS-1's profile holds two red peaks produced by winds within the system. Its high $f_{esc}$(Lya) and the low-velocity offset from the systemic redshift suggest that the source is an active ionizing agent. Future observations will reveal whether a peak is present bluewards of the systemic redshift or if multiple components produce the profile.

astro-ph.GA↗

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

A lack of LAEs within 5Mpc of a luminous quasar in an overdensity at z=6.9: potential evidence of quasar negative feedback at protocluster scales

High-redshift quasars are thought to live in the densest regions of space which should be made evident by an overdensity of galaxies around them. However, campaigns to identify these overdensities through the search of Lyman Break Galaxies (LBGs) and Lyman $\alpha$ emitters (LAEs) have had mixed results. These may be explained by either the small field of view of some of the experiments, the broad redshift ranges targeted by LBG searches, and by the inherent large uncertainty of quasar redshifts estimated from UV emission lines, which makes it difficult to place the Ly-$\alpha$ emission line within a narrowband filter. Here we present a three square degree search ($\sim 1000$ pMpc) for LAEs around the $z=6.9$ quasar VIKJ2348-3054 using the Dark Energy CAMera (DECam), housed on the 4m Blanco telescope, finding 38 LAEs. The systemic redshift of VIK J2348--3054 is known from ALMA [CII] observations and place the Ly-$\alpha$ emission line of companions within the NB964 narrowband of DECam. This is the largest field of view LAE search around a $z>6$ quasar conducted to date. We find that this field is $\sim$ 10 times more overdense when compared to the Chandra Deep-Field South, observed previously with the same instrumental setup as well as several combined blank fields. This is strong evidence that VIKJ2348-3054 resides in an overdensity of LAEs over several Mpc. Surprisingly, we find a lack of LAEs within 5 physical Mpc of the quasar and take this to most likely be evidence of the quasar suppressing star formation in its immediate vicinity. This result highlights the importance of performing overdensity searches over large areas to properly assess the density of those regions of the Universe.

astro-ph.GA↗

arXiv2022

Theory of Optical Activity in Doped Systems with Application to Twisted Bilayer Graphene

We theoretically study the optical activity in a doped system and derive the optical activity tensor from a light wavevector-dependent linear optical conductivity. Although the light-matter interaction is introduced through the velocity gauge from a minimal coupling Hamiltonian, we find that the well-known ``false divergences'' problem can be avoided in practice if the electronic states are described by a finite band effective Hamiltonian, such as a few-band tight-binding model. The expression we obtain for the optical activity tensor is in good numerical agreement with a recent theory derived for an undoped topologically trivial gapped system. We apply our theory to the optical activity of a gated twisted bilayer graphene, with a detailed discussion of the dependence of the results on twist angle, chemical potential, gate voltage, and location of rotation center forming the twisted bilayer graphene.

cond-mat.mes-hall↗

arXiv2022

Ultrafast optical observation of spin-pumping induced dynamic exchange coupling in ferromagnetic semiconductor/metal bilayer

Spin angular momentum transfer in magnetic bilayers offers the possibility of ultrafast and low-loss operation for next-generation spintronic devices. We report the field- and temperature- dependent measurements on the magnetization precessions in Co$_2$FeAl/(Ga,Mn)As by time-resolved magneto-optical Kerr effect (TRMOKE). Analysis of the effective Gilbert damping and phase shift indicates a clear signature of an enhanced dynamic exchange coupling between the two ferromagnetic (FM) layers due to the reinforced spin pumping at resonance. The temperature dependence of the dynamic exchange-coupling reveals a primary contribution from the ferromagnetism in (Ga,Mn)As.

cond-mat.mtrl-sci↗

arXiv2022

VLBI imaging of the pre-coalescence SMBHB candidate SDSS J143016.05+230344.4

Context. Recently, SDSS J143016.05+230344.4 (J1430+2303) was reported to be a supermassive black hole binary (SMBHB) in the final coalescence phase. It is probably the first SMBHB coalescence event observable in human history. Radio observations of J1430+2303 before and after coalescence will provide a unique diagnosis of the energetics and environment of the SMBHB. Aims. We explore the radio emission from the galactic nucleus region that is closely related to the current X-ray and optical activities and helps to understand the state of black hole accretion and outflow before coalescence. Methods. Very long baseline interferometry (VLBI) imaging is the only method that offers milli-arcsecond-level high resolution that can exclude the contamination by diffuse emission on galactic scales. We observed J1430+2303 with the European VLBI Network at 1.7 GHz and with the Very Long Baseline Array at 1.6 and 4.9 GHz in late February and early March 2022. Results. A compact component is detected in all three VLBI images. It has a brightness temperature of > 10^8 K, an unresolved morphology with a size < 0.8 pc, and a flat radio spectrum. These observational features are inconsistent with large opening-angle outflows or winds, but indicate that this compact component might be a jet or a corona. Nearly 60% of the emission is resolved by VLBI and may come from remnant lobes of previous radio activities, the outer layers of a structured jet, or shocks formed by the disc winds in the narrow line region. Conclusions. Current VLBI images do not yet show signs of radio outbursts. Our observations provide pre-coalescence radio data that are an important reference for future comparative studies with the post-merger. In particular, further resolving the jet will pave the way for probing the dynamical features associated with inspiralling binary black holes.

astro-ph.GA↗

arXiv2022

Ultrafast enhancement of interfacial exchange coupling in ferromagnetic bilayer

Fast spin manipulation in magnetic heterostructures, where magnetic interactions between different materials often define the functionality of devices, is a key issue in the development of ultrafast spintronics. Although recently developed optical approaches such as ultrafast spin-transfer and spin-orbit torques open new pathways to fast spin manipulation, these processes do not fully utilize the unique possibilities offered by interfacial magnetic coupling effects in ferromagnetic multilayer systems. Here, we experimentally demonstrate ultrafast photo-enhanced interfacial exchange interactions in the ferromagnetic Co$_2$FeAl/(Ga,Mn)As system at low laser fluence levels. The excitation efficiency of Co$_2$FeAl with the (Ga,Mn)As layer is 30-40 times higher than the case with the GaAs layer at 5 K due to a photo-enhanced exchange coupling interaction via photoexcited charge transfer between the two ferromagnetic layers. In addition, the coherent spin precessions persist to room temperature, excluding the drive of photo-enhanced magnetization in the (Ga,Mn)As layer and indicating a proximity-effect-related optical excitation mechanism. The results highlight the importance of considering the range of interfacial exchange interactions in ferromagnetic heterostructures and how these magnetic coupling effects can be utilized for ultrafast, low-power spin manipulation.

cond-mat.mtrl-sci↗

arXiv2022

The First Large Absorption Survey in HI (FLASH): I. Science Goals and Survey Design

We describe the scientific goals and survey design of the First Large Absorption Survey in HI (FLASH), a wide field survey for 21-cm line absorption in neutral atomic hydrogen (HI) at intermediate cosmological redshifts. FLASH will be carried out with the Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope and is planned to cover the sky south of $δ\approx +40$deg at frequencies between 711.5 and 999.5MHz. At redshifts between $z = 0.4$ and $1.0$ (look back times of 4 - 8Gyr), the HI content of the Universe has been poorly explored due to the difficulty of carrying out radio surveys for faint 21-cm line emission and, at ultra-violet wavelengths, space-borne searches for Damped Lyman-$α$ absorption in quasar spectra. The ASKAP wide field of view and large spectral bandwidth, in combination with a radio-quiet site, will enable a search for absorption lines in the radio spectra of bright continuum sources over 80% of the sky. This survey is expected to detect at least several hundred intervening 21-cm absorbers, and will produce an HI-absorption-selected catalogue of galaxies rich in cool, star-forming gas, some of which may be concealed from optical surveys. Likewise, at least several hundred associated 21-cm absorbers are expected to be detected within the host galaxies of radio sources at $0.4 < z < 1.0$, providing valuable kinematical information for models of gas accretion and jet-driven feedback in radio-loud active galactic nuclei. FLASH will also detect OH 18-cm absorbers in diffuse molecular gas, megamaser OH emission, radio recombination lines, and stacked HI emission.

astro-ph.GA↗

arXiv2022

Study of filtered-x logarithmic recursive least $p$-power algorithm

For active impulsive noise control, a filtered-x recursive least $p$-power (FxRLP) algorithm is proposed by minimizing the weighted summation of the $p$-power of the \emph{a posteriori} errors. Since the characteristic of the target noise is investigated, the FxRLP algorithm achieves good performance and robustness. To obtain a better performance, we develop a filtered-x logarithmic recursive least $p$-power (FxlogRLP) algorithm which integrates the $p$-order moment with the logarithmic-order moment. Simulation results demonstrate that the FxlogRLP algorithm is superior to the existing algorithms in terms of convergence rate and noise reduction.

eess.SP↗

arXiv2020

Non-Gaussian Nature and Entanglement of Spontaneous Parametric Nondegenerate Triple-Photon Generation

How to prepare deterministically non-Gaussian entangled states is a fundamental question for continuous-variable quantum information technology. Here, we theoretically demonstrate through numerical methods that the triple-photon state generated by three-photon spontaneous parametric down-conversion is a pure super-Gaussian resource of non-Gaussian entanglement. Interestingly, the degree of entanglement between the modes of the triple-photon state is stronger than that corresponding to the two-mode squeezed vacuum state produced by a quadratic Hamiltonian with the same parameters. Furthermore, we propose a model to prepare two-mode non-Gaussian entangled states with tunable non-Gaussianity based on quadrature projection measurements.

quant-ph↗

arXiv2020

Scalable Interpretable Learning for Multi-Response Error-in-Variables Regression

Corrupted data sets containing noisy or missing observations are prevalent in various contemporary applications such as economics, finance and bioinformatics. Despite the recent methodological and algorithmic advances in high-dimensional multi-response regression, how to achieve scalable and interpretable estimation under contaminated covariates is unclear. In this paper, we develop a new methodology called convex conditioned sequential sparse learning (COSS) for error-in-variables multi-response regression under both additive measurement errors and random missing data. It combines the strengths of the recently developed sequential sparse factor regression and the nearest positive semi-definite matrix projection, thus enjoying stepwise convexity and scalability in large-scale association analyses. Comprehensive theoretical guarantees are provided and we demonstrate the effectiveness of the proposed methodology through numerical studies.

stat.ME↗