arXiv subjects

Jianxing Zhang

Publications and source records attributed to Jianxing Zhang.

At least 19 recordsLinked to original sources

arXiv2026

A Uniform Census of Variable Stars in M101 Based on HST/ACS Photometry

We present a homogeneous HST/ACS F555W/F814W time-series census of variable stars in two M101 disk fields, using a uniform multi-band reduction and reproducible variable-selection workflow for nearby SN-host galaxies. Supplementary archival F555W epochs are used only to refine selected long-period solutions. Candidates are selected with Lomb-Scargle period searches, Fourier light-curve modeling, two-band consistency statistics, artificial-star-test photometric corrections, and mode-aware Cepheid refinement. The final catalog contains 1417 variable-star candidates, including 1102 secure fundamental-mode and 78 secure first-overtone classical Cepheids. Of these secure Cepheids, 420 are newly identified relative to the Shappee & Stanek catalog. The catalog also contains luminous candidates outside the classical Cepheid locus. We release the catalog and source-level two-band light curves for studies of Cepheid physics, stellar variability, and distance-scale applications.

astro-ph.SR↗

arXiv2026

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through unknown degradations with a x4 scaling factor while ensuring the models remain executable on mobile devices. The objective is to develop effective and efficient network designs or solutions that achieve state-of-the-art real-world image super-resolution performance. The track of the challenge evaluates performance using a weighted combination of image quality assessment (IQA) score and speedup ratios. The competition attracted 108 registrants, with 16 teams achieving a valid score in the final ranking. This collaborative effort advances the performance of mobile real-world image super-resolution while offering an in-depth overview of the latest trends in the field.

cs.CV↗

arXiv2026

Discovery of an Extremely Luminous Type II Cepheid in the Andromeda Giant Stellar Stream: Evidence for a Hierarchical Triple with an Inner Binary Merger

We report the discovery of LAMOST J0041+3948, the most luminous post-AGB Type II Cepheid (TIIC) known, located in the Andromeda Giant Stellar Stream. Its spectral energy distribution (SED) exhibits a strong near-infrared excess, indicating the presence of a circumbinary dusty disk and hence binarity. SED fitting yields an effective temperature of $T_{\rm eff}=6738_{-262}^{+234}\,$K and a post-AGB luminosity of $\log(L/L_{\odot})=4.32_{-0.08}^{+0.07}$. Comparison with theoretical evolutionary tracks suggests a ~$2.0$-$4.0\,M_{\odot}$ progenitor when accounting for a possible scattered-light contribution. ZTF Light curves reveal a pulsation period of 89d that lies close to the period-luminosity relation for long-period RV Tauri stars. Follow-up spectroscopy reveals clear $s$-process enrichment and signatures consistent with an accretion disk around the companion. The inferred progenitor is significantly younger and more massive than a typical stream member, suggesting that an additional mechanism such as a stellar merger is required. We propose a formation channel in which the present post-AGB binary descends from a hierarchical triple system. In this scenario, the inner binary merged after the system was displaced to its current location by the galaxy merger event, and the resulting massive merger remnant subsequently evolved into the extremely luminous post-AGB star observed today.

astro-ph.SR↗

arXiv2025

PerTouch: VLM-Driven Agent for Personalized and Semantic Image Retouching

Image retouching aims to enhance visual quality while aligning with users' personalized aesthetic preferences. To address the challenge of balancing controllability and subjectivity, we propose a unified diffusion-based image retouching framework called PerTouch. Our method supports semantic-level image retouching while maintaining global aesthetics. Using parameter maps containing attribute values in specific semantic regions as input, PerTouch constructs an explicit parameter-to-image mapping for fine-grained image retouching. To improve semantic boundary perception, we introduce semantic replacement and parameter perturbation mechanisms during training. To connect natural language instructions with visual control, we develop a VLM-driven agent to handle both strong and weak user instructions. Equipped with mechanisms of feedback-driven rethinking and scene-aware memory, PerTouch better aligns with user intent and captures long-term preferences. Extensive experiments demonstrate each component's effectiveness and the superior performance of PerTouch in personalized image retouching. Code Pages: https://github.com/Auroral703/PerTouch.

cs.CV↗

arXiv2025

Classification for 969 double-mode RR Lyrae stars from Zwicky Transient Facility

RR Lyrae (RRL) variable stars are cornerstone distance indicators. In particular, double-mode RR Lyrae (RRd) stars enable period--luminosity relations (PLRs) that are less sensitive to metallicity, reducing systematic biases in distance measurements. However, their utility has been limited by a global sample of only $\sim$3,000 objects. We develop an automated RRd-screening pipeline and apply it to a cross-matched sample between the Gaia DR3 RRL catalog and ZTF DR22 time-series photometry. The workflow combines Lomb--Scargle period searches, iterative pre-whitening, period-ratio constraints that suppress $\sim$1-day sampling aliases, and amplitude-based quality cuts, enabling large-scale RRd star screening. We produce two ZTF-based catalogs: (i) 39,322 reliable single-mode RRL (40.5\% of the cross-matched set) and (ii) 969 RRd stars. Among the RRd stars, 614 objects are newly identified, substantially enlarging this previously scarce sample; the catalog achieves an estimated completeness of 47.7\%. The PLR derived from the newly discovered RRd stars agrees with the LMC-based relation, though with larger uncertainties. Incorporating these stars will help tighten the RRd PLR and improve distance measurements. Looking ahead, systematic RRd searches with upcoming surveys such as the Legacy Survey of Space and Time (LSST) and the China Space Station Telescope (CSST) should further extend high-accuracy distances across the Local Group and strengthen their cosmological applications.

astro-ph.SR↗

arXiv2025

A Detailed Analysis of the Milky Way Warp Based on Classical Cepheids

Classical Cepheids (CCs) are important probes for the large-scale warp structure of the Milky Way. Using Gaia DR3 CCs, we establish an optimal time-dependent warp model, where the warp height increases with radius following a power-law, the line of nodes (LONs) exhibit linear twisting with radius, following a leading spiral pattern, and the LONs undergo prograde evolution over time. Structurally, we identify significant warp features in the $5-9$ kpc region of the Galactic disk, where the warp model performs better than the flat model. Beyond 15 kpc, the model with the second Fourier term does not fit the observations well, whereas the model with twisted LONs better matches the data. Kinematically, we derived expressions for the vertical velocities using direct differentiation and then calculated the precession rates for each CC. Our results intuitively indicate a nearly uniform and low warp precession rate of $ω= 4.86 \pm (0.88)_{stat} \pm (2.14)_{sys}$ km s$^{-1}$ kpc$^{-1}$ beyond 12.5 kpc, in agreement with classical kinematic estimates. Based on these findings, we propose a simple yet comprehensive time-dependent warp model, $Z_{w}(t) = 0.00019R^{3.08}\sin(ϕ- (3.87R-41.79 + 4.86t))$, which provides a unified framework for describing both the geometric and kinematic evolution of the Galactic warp. We analyzed the impact of the adopted solar vertical velocity on the inferred warp precession rate and confirmed the reliability of the measured precession rate. In addition, we found that extinction treatment affects the warp amplitude in the inner disk, while its influence on the outer disk warp structure and the precession rate is negligible.

astro-ph.GA↗

arXiv2025

A search of periodic variable stars in the LMC by JWST photometry

Based on high-resolution near-infrared photometric data from the James Webb Space Telescope (JWST) targeting the Large Magellanic Cloud (LMC), this study attempts to evaluate the feasibility and sensitivity limits of variable star detection in crowded stellar fields. Through light curve analysis, we identified a total of 304 periodic variable stars, including 71 EW-type eclipsing binaries, 7 EA-type eclipsing binaries, 177 rotational variables, 38 $δ$ Scuti (DSCT) stars, and 12 RR Lyrae stars. Period--luminosity relations (PLRs) were derived for EW-type eclipsing binaries, DSCT stars, and RR Lyrae stars. The PLRs for EW-type and RR Lyrae stars are in good agreement with previous studies, while the PLR zero point for DSCT stars appears systematically fainter by approximately 0.15--0.30 mag. Our PLRs exhibit low dispersion and are minimally affected by crowding. We analyzed the capability of JWST archival data to detect low-amplitude variables and found that only stars with amplitudes greater than approximately 0.05 mag can be reliably detected. Through simulations, we quantified how increasing the number of photometric epochs improves the detectability of low-amplitude, low signal-to-noise ratio variables. Despite current limitations in observational cadence, JWST demonstrates unique advantages in detecting short-period eclipsing binaries, rotational variables, and high-amplitude pulsators. Its exceptional spatial resolution enables high-precision PLR calibrations, offering new opportunities for future studies in variable star astrophysics and extragalactic distance measurements.

astro-ph.SR↗

arXiv2025

NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results

This paper provides a review of the NTIRE 2025 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on generating natural, realistic outputs while maintaining identity consistency. Its goal is to advance state-of-the-art solutions for perceptual quality and realism, without imposing constraints on computational resources or training data. The track of the challenge evaluates performance using a weighted image quality assessment (IQA) score and employs the AdaFace model as an identity checker. The competition attracted 141 registrants, with 13 teams submitting valid models, and ultimately, 10 teams achieved a valid score in the final ranking. This collaborative effort advances the performance of real-world face restoration while offering an in-depth overview of the latest trends in the field.

cs.CV↗

arXiv2025

Period--Luminosity Relations for Double-mode $δ$ Sct Stars

Previous studies of the Period--Luminosity relations (PLRs) of Delta Scuti ($δ$ Sct) stars have focused on those with a single pulsation mode. However, for $δ$ Sct stars with many different pulsation modes, classifying a single mode is difficult. In this study, an all-sky dataset is constructed using double-mode $δ$ Sct stars from ZTF and OGLE, and is used to determine F-mode and 1O-mode PLRs for eight single bands and six Wesenheit bands. In the $W1$ band, the PLR dispersion is about 0.171 mag and the total zero point error is 1\%. Our results show that to accurately classify the 1O modes of $δ$ Sct stars requires authentication based on multiple modes. Classification based on amplitude alone leads to impure 1O-mode $δ$ Sct stars and significant deviations in the PLRs. We compare the PLRs of the different sequences in the Petersen diagram and find that they are consistent after a strict criterion filtering, suggesting that their evolutionary state is similar. In addition, we find a weak period--metallicity relation for double-mode $δ$ Sct stars, unlike double-mode RR Lyrae stars. As distance tracers, large-amplitude F-mode $δ$ Sct and double-mode $δ$ Sct stars are the most suitable of the $δ$ Sct family.

astro-ph.SR↗

arXiv2024

The rotation properties of $δ$ Sct and $γ$ Dor stars

Based on the LAMOST spectroscopy and TESS time-series photometry, we have obtained a main-sequence star sample of $δ$ Scuti and $γ$ Doradus stars. The sample includes 1534 $δ$ Sct stars, 367 $γ$ Dor stars, 1703 $δ$ Sct$| γ$ Dor stars, 270 $γ$ Dor$| δ$ Sct stars, along with 105 '$δ$ Sct candidates' and 32 '$γ$ Dor candidates'. After correcting for projection effects, we derived the equatorial rotational velocity distribution for $δ$ Sct and $γ$ Dor stars and compared it with that of normal stars. The rotational velocity distributions of $δ$ Sct and $γ$ Dor stars are extremely similar, with the only difference potentially due to the rotational variable stars that have not been completely removed. In contrast, the rotational velocity distribution of normal stars is more dispersed compared to pulsating stars. Additionally, the peak rotational velocity of the pulsating stars is about 10 km s$^{-1}$ higher than that of normal stars. Unlike the normal stars, which show a monotonic increase in peak velocity with mass between 1.8 and 2.5 $M_{\odot}$, the rotational velocity distribution of $δ$ Sct stars does not exhibit a strong mass dependence. We also found that normal stars accelerate during the late main-sequence evolutionary phase, while $δ$ Sct stars decelerate. Furthermore, there may still be unclassified stars with diverse rotational properties in the normal star sample compared to the $δ$ Sct stars, which is likely to be an important contributor to the broader dispersion observed in its rotational velocity distribution. The photometric amplitude in $δ$ Sct stars is modulated with rotational velocity, with high-amplitude stars typically rotating slowly and low-amplitude stars showing a broad distribution of rotational velocities.

astro-ph.SR↗

arXiv2024

Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey

This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is to upscale RAW Bayer images by 2x, considering unknown degradations such as noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. The performance of the top-5 submissions is reviewed and provided here as a gauge for the current state-of-the-art in RAW Image Super-Resolution.

cs.CV↗

arXiv2023

Bridging Data-Driven and Knowledge-Driven Approaches for Safety-Critical Scenario Generation in Automated Vehicle Validation

Automated driving vehicles~(ADV) promise to enhance driving efficiency and safety, yet they face intricate challenges in safety-critical scenarios. As a result, validating ADV within generated safety-critical scenarios is essential for both development and performance evaluations. This paper investigates the complexities of employing two major scenario-generation solutions: data-driven and knowledge-driven methods. Data-driven methods derive scenarios from recorded datasets, efficiently generating scenarios by altering the existing behavior or trajectories of traffic participants but often falling short in considering ADV perception; knowledge-driven methods provide effective coverage through expert-designed rules, but they may lead to inefficiency in generating safety-critical scenarios within that coverage. To overcome these challenges, we introduce BridgeGen, a safety-critical scenario generation framework, designed to bridge the benefits of both methodologies. Specifically, by utilizing ontology-based techniques, BridgeGen models the five scenario layers in the operational design domain (ODD) from knowledge-driven methods, ensuring broad coverage, and incorporating data-driven strategies to efficiently generate safety-critical scenarios. An optimized scenario generation toolkit is developed within BridgeGen. This expedites the crafting of safety-critical scenarios through a combination of traditional optimization and reinforcement learning schemes. Extensive experiments conducted using Carla simulator demonstrate the effectiveness of BridgeGen in generating diverse safety-critical scenarios.

cs.LG↗

arXiv2023

Double-mode RR Lyrae star -- robust distance and metallicity indicators

RR Lyrae (RR Lyr) stars are a well-known and useful distance indicator for old stellar populations such as globular clusters and dwarf galaxies. Fundamental-mode RR Lyr (RRab) stars are commonly used to measure distances, and the accuracy of the determined distance is strongly constrained by metallicity. Here, we investigate the metallicity dependence in the period-luminosity (PL) relation of double-mode RR Lyr (RRd) stars. We find and establish a linear relation between metallicity and period or period ratio for RRd stars. This relation can predict the metallicity as accurately as the low-resolution spectra. Based on this relation, we establish a metallicity-independent PL relation for RRd stars. Combining the distance of the Large Magellanic Cloud and Gaia parallaxes, we calibrate the zero point of the derived PL relation to an error of 0.022 mag. Using RRd stars, we measure the distances of globular clusters and dwarf galaxies with an accuracy of 2-3% and 1-2%, respectively. In the future, RRd stars could anchor galaxy distances to an accuracy of 1.0% and become an independent distance ladder in the Local Group.

astro-ph.SR↗

arXiv2023

The use of double-mode RR Lyrae stars as robust distance and metallicity indicators

RR Lyrae stars are one of the primary distance indicators for old stellar populations such as globular clusters, dwarf galaxies and galaxies. Typically, fundamental-mode RR Lyr stars are used for distance measurements, and their accuracy is strongly limited by the dependence of absolute magnitudes on metallicity, in both the optical and infrared bands. Here, we report the discovery of a period-(period ratio)-metallicity relation for double-mode RR Lyr stars, which can predict metallicity as accurately as the low-resolution spectra. With theoretical and observational evidence, we propose that the period-luminosity relation of double-mode RR Lyr stars is not affected by the metallicity. Combining the Large Magellanic Cloud distance and Gaia parallaxes, we calibrate the zero point of the period-luminosity relation to an error of 0.022 mag, which means that in the best case double-mode RR Lyr stars can anchor galaxy distances to an accuracy of 1.0%. For four globular clusters and two dwarf galaxies, we obtain distances using double-mode RR Lyr stars with a distance accuracy of 2-3% and 1-2%, respectively. With future telescopes such as the China Space Station Telescope and the Vera C. Rubin Observatory, double-mode RR Lyr stars will be established as an independent distance ladder in the near-field universe.

astro-ph.SR↗

arXiv2022

Improving Classification Model Performance on Chest X-Rays through Lung Segmentation

Chest radiography is an effective screening tool for diagnosing pulmonary diseases. In computer-aided diagnosis, extracting the relevant region of interest, i.e., isolating the lung region of each radiography image, can be an essential step towards improved performance in diagnosing pulmonary disorders. Methods: In this work, we propose a deep learning approach to enhance abnormal chest x-ray (CXR) identification performance through segmentations. Our approach is designed in a cascaded manner and incorporates two modules: a deep neural network with criss-cross attention modules (XLSor) for localizing lung region in CXR images and a CXR classification model with a backbone of a self-supervised momentum contrast (MoCo) model pre-trained on large-scale CXR data sets. The proposed pipeline is evaluated on Shenzhen Hospital (SH) data set for the segmentation module, and COVIDx data set for both segmentation and classification modules. Novel statistical analysis is conducted in addition to regular evaluation metrics for the segmentation module. Furthermore, the results of the optimized approach are analyzed with gradient-weighted class activation mapping (Grad-CAM) to investigate the rationale behind the classification decisions and to interpret its choices. Results and Conclusion: Different data sets, methods, and scenarios for each module of the proposed pipeline are examined for designing an optimized approach, which has achieved an accuracy of 0.946 in distinguishing abnormal CXR images (i.e., Pneumonia and COVID-19) from normal ones. Numerical and visual validations suggest that applying automated segmentation as a pre-processing step for classification improves the generalization capability and the performance of the classification models.

eess.IV↗

arXiv2021

COVID-19 Detection from Chest X-ray Images using Imprinted Weights Approach

The COVID-19 pandemic has had devastating effects on the well-being of the global population. The pandemic has been so prominent partly due to the high infection rate of the virus and its variants. In response, one of the most effective ways to stop infection is rapid diagnosis. The main-stream screening method, reverse transcription-polymerase chain reaction (RT-PCR), is time-consuming, laborious and in short supply. Chest radiography is an alternative screening method for the COVID-19 and computer-aided diagnosis (CAD) has proven to be a viable solution at low cost and with fast speed; however, one of the challenges in training the CAD models is the limited number of training data, especially at the onset of the pandemic. This becomes outstanding precisely when the quick and cheap type of diagnosis is critically needed for flattening the infection curve. To address this challenge, we propose the use of a low-shot learning approach named imprinted weights, taking advantage of the abundance of samples from known illnesses such as pneumonia to improve the detection performance on COVID-19.

eess.IV↗

arXiv2020

Computer-aided Tumor Diagnosis in Automated Breast Ultrasound using 3D Detection Network

Automated breast ultrasound (ABUS) is a new and promising imaging modality for breast cancer detection and diagnosis, which could provide intuitive 3D information and coronal plane information with great diagnostic value. However, manually screening and diagnosing tumors from ABUS images is very time-consuming and overlooks of abnormalities may happen. In this study, we propose a novel two-stage 3D detection network for locating suspected lesion areas and further classifying lesions as benign or malignant tumors. Specifically, we propose a 3D detection network rather than frequently-used segmentation network to locate lesions in ABUS images, thus our network can make full use of the spatial context information in ABUS images. A novel similarity loss is designed to effectively distinguish lesions from background. Then a classification network is employed to identify the located lesions as benign or malignant. An IoU-balanced classification loss is adopted to improve the correlation between classification and localization task. The efficacy of our network is verified from a collected dataset of 418 patients with 145 benign tumors and 273 malignant tumors. Experiments show our network attains a sensitivity of 97.66% with 1.23 false positives (FPs), and has an area under the curve(AUC) value of 0.8720.

eess.IV↗

arXiv2018

Excitonic Complexes and Optical Gain in Two-Dimensional Molybdenum Ditelluride Well below Mott Transition

Strong Coulomb interaction in 2D materials provides unprecedented opportunities for studying many key issues of condensed matter physics, such as co-existence and mutual conversions of excitonic complexes, fundamental optical processes associated with their conversions, and their roles in the celebrated Mott transition. Recent lasing demonstrations in 2D materials raise important questions about the existence and origin of optical gain and possible roles of excitonic complexes. While lasing occurred at extremely low densities dominated by various excitonic complexes, optical gain was observed in the only experiment at densities several orders of magnitude higher, exceeding the Mott density. Here, we report a new gain mechanism involving charged excitons or trions well below the Mott density in 2D molybdenum ditelluride. Our combined experimental and modeling study not only reveals the complex interplays of excitonic complexes well below the Mott transition, but also provides foundation for lasing at extremely low excitation levels, important for future energy efficient photonic devices.

cond-mat.mes-hall↗