arXiv subjects

Yanhui Chen

Publications and source records attributed to Yanhui Chen.

At least 19 recordsLinked to original sources

arXiv2026

HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-governance procedures. We present HIRA, a training-free, on-premises retrieval-augmented cascade for document classification in regulated deployments that combines BM25 over OCR text, dense text embeddings, and image-level representations through validation-calibrated weighted reciprocal-rank fusion. Confident documents are classified directly by retrieval; uncertain or visually confusable documents are passed to a locally hosted LLM verifier, which receives the OCR text, retrieved exemplars, label descriptions, and confusion-specific terms. When the verifier remains uncertain, the document is sent to human review. Each correction is stored as a margin-weighted retrieval exemplar and updates a Dirichlet-smoothed confusion graph, letting the system improve without updating model weights. On a private 80-class trade-finance corpus, HIRA processes the full 30,233-document production stream while requesting human correction for only 1,945 documents (6.4%), improving Macro-F1 from 0.6218 to 0.8548. On the corrected Tobacco-3482 benchmark, HIRA reaches 0.9423 Macro-F1 with a locally hosted DeepSeek-R1-Distill-Qwen-32B verifier, 17.4 percentage points above the zero-shot LLM baseline, while invoking the verifier for only about 40% of documents and reducing LLM calls by approximately 60%. With 518 human corrections (24.8% of the pool), HIRA matches the fully labelled pool oracle, in which all 2,086 pool documents are indexed with their ground-truth labels. These results show that selective human feedback and retrieval-memory adaptation can be a practical alternative to repeated model retraining for long-tail document classification in regulated deployments.

cs.AI↗

arXiv2026

Diffusion Image Editing via Asynchronous Token Decoding

Text-guided diffusion image editing aims to modify semantic attributes of an image while preserving its identity, layout, and background. However, na\"ively switching the text condition during sampling often causes global drift, as denoising dynamics propagate changes across tokens and can disrupt unedited regions. To address this issue, we propose \textbf{A}synchronous \textbf{T}oken \textbf{D}ecoding \textbf{Edit} (ATDEdit), an inference-time framework that views each sampler step as a parallel update of a globally coupled token matrix and enables token-indexed condition switching with differentiated update policies. Instead of applying synchronous target-conditioned updates to all tokens, ATDEdit estimates editable locations using token-wise conditional surprisal and applies target-conditioned corrections to the selected token set. It supplies source key/value memory at keep-token positions and projects selected keep-token latent rows back to their source values; these operations promote background preservation but do not constitute a pixel-level invariance guarantee. This approach combines local editing and background preservation without external or user-provided spatial masks and without model fine-tuning. On PIE-Bench, ATDEdit achieves the strongest reported preservation metrics, including 27.44~dB PSNR and 0.055 LPIPS, while retaining competitive semantic alignment.

cs.CV↗

arXiv2026

LAMOST J052016.79+345651.7: An EW-type Binary with Emission Line Spectra and Circumstellar Material

LAMOST J052016.79+345651.7 was identified as an EW-type eclipsing binary by Chen et al. when studying the periodic variable stars based on the ZTF telescope. An orbital period of 0.3507818 days has been reported. Using the ZTF g, r, i band light curves, we reproduced the orbital period and obtained a phase folded diagram. The multi-band apparent magnitudes from Pan-STARRS, 2MASS, and WISE, the color indices, and the infrared excess in the WISE w4 band all indicate that LAMOST J0520 contains cold circumstellar material. All 19 LRS from LAMOST exhibit prominent Halpha emission lines, along with clear N II and S II emission lines, indicating that LAMOST J0520 contains optically thin, warm ionized gas with extremely low electron density. From the 19 spectra, an effective temperature of 6200 \pm 400 K can be obtained. Therefore, the emission lines likely originate from shock-driven outflows and mass ejection, while the infrared excess likely comes from dust formed as the outflows cool. We performed light curve fitting and evolutionary simulation study on LAMOST J0520 using PHOEBE and MESA, respectively. The phase shift of the fitted model can be uniquely determined, but the inclination and the fillout_{factor} are degenerate. Considering the angular momentum loss process, the evolutionary simulation from detached binaries to contact binaries can reflect the main evolutionary process of LAMOST J0520. When the orbital period of the evolutionary model is 0.351 days, the other parameters are generally consistent with the observed characteristics of LAMOST J0520. Considering mass loss, LAMOST J052016.79+345651.7 will evolve into a blue straggler star in the future. Future LAMOST medium resolution time-domain spectra of LAMOST J0520 may offer an opportunity to reveal more detailed physical processes.

astro-ph.SR↗

arXiv2026

Majorization-Guided Test-Time Adaptation for Vision-Language Models under Modality-Specific Shift

Vision--language models can face asymmetric visual and textual shifts at deployment. These shifts expose a multimodal failure mode in which an unreliable branch remains overconfident, dominates fusion, and causes entropy-based test-time adaptation to sharpen an incorrect prediction. We model this behavior as doubly stochastic posterior mixing and cast adaptation as constrained de-mixing. Majorization-Guided Multimodal Test-Time Adaptation (MG-MTTA) freezes both encoders and updates only a lightweight fusion module. Running-anchor consistency estimates relative branch drift, while cross-modal conflict regulates modality dominance before entropy sharpening. The analysis gives sufficient conditions for entropy reduction to preserve the clean decision and an explicit threshold at which a biased modality reverses the fused ranking. Across visual, textual, and joint shifts, MG-MTTA improves ImageNet top-1 accuracy from 57.97\% to 66.51\% under textual shift and from 21.68\% to 26.27\% under joint shift, while reducing wrong-more-confident failures. The largest gains occur under textual and joint shifts, where the two branches differ more in reliability. Project page: https://mg-mtta.github.io/.

cs.CV↗

arXiv2026

TransSplat: Unbalanced Semantic Transport for Language-Driven 3DGS Editing

Language-driven 3D Gaussian Splatting (3DGS) editing provides a more convenient approach for modifying complex scenes in VR/AR. Standard pipelines typically adopt a two-stage strategy: first editing multiple 2D views, and then optimizing the 3D representation to match these edited observations. Existing methods mainly improve view consistency through multi-view feature fusion, attention filtering, or iterative recalibration. However, they fail to explicitly address a more fundamental issue: the semantic correspondence between edited 2D evidence and 3D Gaussians. To tackle this problem, we propose TransSplat, which formulates language-driven 3DGS editing as a multi-view unbalanced semantic transport problem. Specifically, our method establishes correspondences between visible Gaussians and view-specific editing prototypes, thereby explicitly characterizing the semantic relationship between edited 2D evidence and 3D Gaussians. It further recovers a cross-view shared canonical 3D edit field to guide unified 3D appearance updates. In addition, we use transport residuals to suppress erroneous edits in non-target regions, mitigating edit leakage and improving local control precision. Qualitative and quantitative results show that, compared with existing 3D editing methods centered on enhancing view consistency, TransSplat achieves superior performance in local editing accuracy and structural consistency.

cs.CV↗

arXiv2026

CoCo-SAM3: Harnessing Concept Conflict in Open-Vocabulary Semantic Segmentation

SAM3 advances open-vocabulary semantic segmentation by introducing a prompt-driven mask generation paradigm. However, in multi-class open-vocabulary scenarios, masks generated independently from different category prompts lack a unified and inter-class comparable evidence scale, often resulting in overlapping coverage and unstable competition. Moreover, synonymous expressions of the same concept tend to activate inconsistent semantic and spatial evidence, leading to intra-class drift that exacerbates inter-class conflicts and compromises overall inference stability. To address these issues, we propose CoCo-SAM3 (Concept-Conflict SAM3), which explicitly decouples inference into intra-class enhancement and inter-class competition. Our method first aligns and aggregates evidence from synonymous prompts to strengthen concept consistency. It then performs inter-class competition on a unified comparable scale, enabling direct pixel-wise comparisons among all candidate classes. This mechanism stabilizes multi-class inference and effectively mitigates inter-class conflicts. Without requiring any additional training, CoCo-SAM3 achieves consistent improvements across eight open-vocabulary semantic segmentation benchmarks.

cs.CV↗

arXiv2026

LLM Framework for Discovering Major Mathematical Conjectures: AI's Quest for the Next Riemann Hypothesis

Major mathematical conjectures still depend heavily on expert intuition, so a unified method for the systematic generation and validation of conjectures with substantial mathematical potential remains unavailable. We present a three stage pipeline for major conjecture discovery, with region search from explicit local evidence modules, reflective validation for foundationality, novelty, and potential significance, and formal validation in Lean 4 and Mathlib. The objective is the discovery of mathematical problems with high problem taste, namely problems whose proofs could reorganize the language of a research area and provide durable help to human mathematical research. Experiments on twenty candidates showstable passage from natural language to formal checks, with twenty out of twenty candidates passing Lean parsing and type checking, twenty out of twenty candidates not directly absorbed by exact?,twenty out of twenty candidates not automatically discharged by aesop, and no explicit duplicates or near duplicates.

cs.AI↗

arXiv2026

Explanation-Guided Adversarial Training for Robust and Interpretable Models

Deep neural networks (DNNs) have achieved remarkable performance in many tasks, yet they often behave as opaque black boxes. Explanation-guided learning (EGL) methods steer DNNs using human-provided explanations or supervision on model attributions. These approaches improve interpretability but typically assume benign inputs and incur heavy annotation costs. In contrast, both predictions and saliency maps of DNNs could dramatically alter facing imperceptible perturbations or unseen patterns. Adversarial training (AT) can substantially improve robustness, but it does not guarantee that model decisions rely on semantically meaningful features. In response, we propose Explanation-Guided Adversarial Training (EGAT), a unified framework that integrates the strength of AT and EGL to simultaneously improve prediction performance, robustness, and explanation quality. EGAT generates adversarial examples on the fly while imposing explanation-based constraints on the model. By jointly optimizing classification performance, adversarial robustness, and attributional stability, EGAT is not only more resistant to unexpected cases, including adversarial attacks and out-of-distribution (OOD) scenarios, but also offer human-interpretable justifications for the decisions. We further formalize EGAT within the Probably Approximately Correct learning framework, demonstrating theoretically that it yields more stable predictions under unexpected situations compared to standard AT. Empirical evaluations on OOD benchmark datasets show that EGAT consistently outperforms competitive baselines in both clean accuracy and adversarial accuracy +37% while producing more semantically meaningful explanations, and requiring only a limited increase +16% in training time.

cs.LG↗

arXiv2026

LAMOST J113208.06-005052.3 and LAMOST J052957.56+344127.0: two new binaries with a hot white dwarf and a flaring companion star

Binaries contain rich physical information, and the study of binaries has always been a hot topic in stellar physics research. The stars LAMOST J1132 and LAMOST J0529 have not yet been recorded in the SIMBAD astronomical database. We have investigated their physical properties via methods such as spectral analysis, photometric analysis, and light curve analysis. Based on comprehensive analysis, we conclude that they are two newly discovered binary systems, each consisting of a hot white dwarf and a flaring companion star. Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectra indicate that both stars contain hot white dwarfs. The spectral fitting yields $T_{eff}$=53728$\pm$2467\,K, log$g$=7.98$\pm$0.08 for LAMOST J1132, and $T_{eff}$=47381$\pm$494\,K, log$g$=7.84$\pm$0.05 for LAMOST J0529. The weak neutral metal lines in the LAMOST spectra and the discrepancy between the Global Astrometric Interferometer for Astrophysics (GAIA) and LAMOST spectra both indicate that these two sources are likely binary systems. The relatively high flux values for both sources in the near-infrared and mid-infrared bands support our preliminary judgment. The color index in the near-infrared bands suggests that the companion star is K or M type for LAMOST J1132 and M type for LAMOST J0529. Light curve data from the Zwicky Transient Facility (ZTF) indicate that the companion stars of both sources are stars exhibiting flare activity. The eclipse probability is very low, indicating that these two sources are non-eclipsing binary systems. The physics of binaries is fascinating, and future data from LAMOST Medium Resolution Spectra are expected to enable the detection of magnetic fields in these two hot white dwarfs.

astro-ph.SR↗

arXiv2025

From Attribution to Action: Jointly ALIGNing Predictions and Explanations

Explanation-guided learning (EGL) has shown promise in aligning model predictions with interpretable reasoning, particularly in computer vision tasks. However, most approaches rely on external annotations or heuristic-based segmentation to supervise model explanations, which can be noisy, imprecise and difficult to scale. In this work, we provide both empirical and theoretical evidence that low-quality supervision signals can degrade model performance rather than improve it. In response, we propose ALIGN, a novel framework that jointly trains a classifier and a masker in an iterative manner. The masker learns to produce soft, task-relevant masks that highlight informative regions, while the classifier is optimized for both prediction accuracy and alignment between its saliency maps and the learned masks. By leveraging high-quality masks as guidance, ALIGN improves both interpretability and generalizability, showing its superiority across various settings. Experiments on the two domain generalization benchmarks, VLCS and Terra Incognita, show that ALIGN consistently outperforms six strong baselines in both in-distribution and out-of-distribution settings. Besides, ALIGN also yields superior explanation quality concerning sufficiency and comprehensiveness, highlighting its effectiveness in producing accurate and interpretable models.

cs.CV↗

arXiv2025

LAMOST J064137.77+045743.8: A New Binary of an A7-type Pulsating Subgiant and an M-type Red Dwarf

With the progressive release of data from numerous sky surveys, humanity has entered the era of astronomical big data. Multi-wavelength, multi-method research is playing an increasingly crucial role. Binaries account for a substantial fraction of all stellar systems and research into binaries is of fundamental importance. LAMOST J064137.77+045743.8 has not yet been recorded in the SIMBAD astronomical database. We conducted a comprehensive analysis of LAMOST J064137.77+045743.8 using multi-band spectroscopic, astrometric, and photometric data. The low-resolution spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) suggest that LAMOST J064137.77+045743.8 is a binary consisting of an A7-type subgiant star ($T_{\rm eff}$ $\sim$ 7500\,K and log\,$g$ $\sim$ 3.9) and a cool red dwarf star. Astrometric data from Globe Astrometric Interferometers for Astrophysics support the binary speculation with a Renormalized Unit Weight Error metric value of 1.9. Additional flux observations in the infrared bands further corroborate the presence of a red dwarf companion. The i-band flare detected by the Zwicky Transient Facility (ZTF) photometric observations bolsters the interpretation of an M-type red dwarf companion. The radial velocity variations in the H$\alpha$ lines from LAMOST medium-resolution spectra and the light curves from ZTF both support the classification of the A7 subgiant as a pulsating star. The binary either has a long orbital period, a non-eclipsing binary orbit, or extremely shallow eclipses. Future asteroseismology studies will further probe the internal physics of the A7 subgiants. Research on binaries is incredibly fascinating.

astro-ph.SR↗

arXiv2025

Giant spin Hall effects and topological surface states in ternary-layered MAX carbides Mn+1AlCn (M= Nb, Ta, n=1, 2, 3)

In this work, we report a systematic study of the electronic structures, band topology, and intrinsic spin Hall effect (SHE) of the layered MAX carbides Mn+1AlCn (M= Nb, Ta, n=1, 2, 3) and explore the correlation effects on the SHE. The results show that M3AlC2 and M4AlC3 (M= Nb, Ta) share similar Dirac-band-crossing features near the Fermi level (EF) and form nodal lines in the absence of spin-orbit coupling (SOC). When the SOC is included, the Dirac band crossings are fully gapped, resulting in nontrivial Z2 topological invariants (1;000) with a pair of surface states on the (001) plane. Remarkably, the multiple gapped Dirac points contribute to locally strong spin Berry curvatures, which lead to large spin Hall conductivities and a giant spin Hall angle up to ~ 60% for Ta3AlC2. Moreover, we also elucidate the impact of Hubbard U correction on SHC. Our findings indicate that Ta3AlC2 might represent an intriguing layered Z2 topological metal with superior charge-to-spin conversion efficiency.

cond-mat.mes-hall↗

arXiv2025

A preliminary cosmological analysis of stellar population synthesis of galaxies released by LAMOST LRS DR11

The evolution of the universe together with the galaxies is one of the fundamental issues that we humans are most interested in. Both the observations of tidal streams from SDSS and the theory of $\Lambda$CDM support the hierarchical merging theory. The study of high redshift celestial bodies contributes to a more in-depth study of cosmology. The LAMOST low resolution search catalog DR11 v1.0 has released 11,939,296 spectra, including 11,581,542 stars, 275,302 galaxies, and 82,452 quasars, and so on. The data of 28,780 stellar population synthesis of galaxies and some high redshift quasars are used to do a preliminary statistical research. We selected the data with small errors for analysis and obtained some basic statistical conclusions. Older galaxies have relatively larger stellar velocity dispersions. The larger the metallicity, the greater the stellar velocity dispersion. These statistical results are reasonable and consistent with previous work. Because the stellar velocity dispersion is driven by the total mass of a galaxy at the first order and more massive galaxies have older ages and greater metallicities. The spectra of high redshift quasars show clear Gunn-Peterson trough and Lyman-$\alpha$ forest. The identified emission lines and high redshift celestial spectra released by LAMOST can be used for cosmological research.

astro-ph.GA↗

arXiv2025

Mode identification revisit and asteroseismology of the DAV star TIC 231277791

White dwarfs are the final stage for most low and intermediate mass stars, which plays an important role in understanding stellar evolution and galactic history. Here we performed an asteroseismological analysis on TIC 231277791 based on 10 independent modes reported by Romero et al. Two groups of modes were identified with frequency splitting: mode identification$\_{1}$ with one $l$\,=\,1, $m$\,=\,0 mode, two $l$\,=\,2, $m$\,=\,0 modes, and three $l$\,=\,1 or 2, $m$\,=\,0 modes, and mode identification$\_{2}$ wtih one $l$\,=\,1, $m$\,=\,0 mode, three $l$\,=\,2, $m$\,=\,0 modes, and one $l$\,=\,1 or 2, $m$\,=\,0 mode. The rotation period is derived to be 41.64\,$\pm$\,2.73\,h for TIC 231277791. We established a large sample (7,558,272) of DAV star models using the White Dwarf Evolution Code (\texttt{WDEC}; 2018, v16), resulting of optimal models with model$\_{1}$ (mode identification$\_{1}$): $M_\mathrm{*}$\,=\,0.570\,$\pm$\,0.005\,$M_\mathrm{\odot}$, $T_\mathrm{eff}$\,=\,11300\,$\pm$\,10\,K, -log($M_\mathrm{H}/M_\mathrm{*}$)\,=\,9.15\,$\pm$\,0.01, -log($M_\mathrm{He}/M_\mathrm{*}$)\,=\,4.94\,$\pm$\,0.01, and $\sigma_{\textup{RMS}}$\,=\,0.06\,s, and model$\_{2}$ (mode identification$\_{2}$): $M_\mathrm{*}$\,=\,0.720\,$\pm$\,0.005\,$M_\mathrm{\odot}$, $T_\mathrm{eff}$\,=\,11910\,$\pm$\,10\,K, -log($M_\mathrm{H}/M_\mathrm{*}$)\,=\,6.11\,$\pm$\,0.01, -log($M_\mathrm{He}/M_\mathrm{*}$)\,=\,3.09\,$\pm$\,0.01, and $\sigma_{\textup{RMS}}$\,=\,0.04\,s. The central oxygen abundances are 0.71 (optimal model$\_{1}$) and 0.72 (optimal model$\_{2}$), respectively, which are consistent with the results of stellar structure and evolution theory.

astro-ph.SR↗

arXiv2024

Variable white dwarfs in TMTS: Asteroseismological analysis of a ZZ Ceti star, TMTS J17184064+2524314

The Tsinghua University-Ma Huateng Telescope for Survey (TMTS) has been constantly monitoring the northern sky since 2020 in search of rapidly variable stars. To find variable white dwarfs (WDs), the TMTS catalog is cross-matched with the WD catalog of Gaia EDR3, resulting in over 3000 light curves of WD candidates. The WD TMTS J17184064+2524314 (hereafter J1718) is the second ZZ~Ceti star discovered among these common sources. Based on the light curves from TMTS, follow-up photometric observations, and TESS, 10 periods and 3 combination periods are detected. A rotation period of $25.12\pm0.18$ hr is derived, according to the identified rotational splitting. Our spectroscopic observation indicates that this WD belongs to DA type with $T_{\rm eff}=11,670\pm604$ K, log $g=8.16\pm0.36$, $M = 0.70\pm0.23$ M$_{\odot}$, and age=$0.51\pm0.34$ Gyr. Based on core-parameterized asteroseismological model grids ($\geqslant$ 14 million), we derive a best-fit solution of $T_{\rm eff}=11,640\pm20$ K, log $g=8.267\pm0.008$, and $M = 0.750\pm0.005$ M$_{\odot}$ for J1718, consistent with the spectral fitting results. For this WD, the corresponding carbon and oxygen abundances in the core are 0.43 and 0.57, respectively. The distance derived from the intrinsic luminosity given by asteroseismology is $64\pm15$ pc, in accord with the distance of $70.1\pm0.2$ pc from Gaia DR3 within the uncertainties.

astro-ph.SR↗

arXiv2023

Properties and Asteroseismological analysis of a new ZZ ceti discovered by TMTS

Tsinghua university-Ma Huateng Telescope for Survey (TMTS) aims to discover rapidly evolving transients by monitoring the northern sky. The TMTS catalog is cross-matched with the white dwarf (WD) catalog of Gaia EDR3, and light curves of more than a thousand WD candidates are obtained so far. Among them, the WD TMTS J23450729+5813146 (hereafter J2345) is one interesting common source. Based on the light curves from the TMTS and follow-up photometric observations, periods of 967.113 s, 973.734 s, 881.525 s, 843.458 s, 806.916 s and 678.273 s are identified. In addition, the TESS observations suggest a 3.39 h period but this can be attributed to the rotation of a comoving M dwarf located within 3". The spectroscopic observation indicates that this WD is DA type with Teff = 11778+/-617K,log g = 8.38+/-0.31,mass=0.84+/-0.20Msun and age=0.704+/-0.377 Gyrs. Asteroseismological analysis reveals a global best-fit solution of Teff =12110+/-10K and mass=0.760+/-0.005Msun,consistent with the spectral fitting results, and Oxygen and Carbon abundances in the core center are 0.73 and 0.27, respectively. The distance derived from the intrinsic luminosity given by asteroseismology is 93 parsec, which is in agreement with the distance of 98 parsec from Gaia DR3. Additionally, kinematic study shows that this WD is likely a thick disk star. The mass of its zero-age main-sequence mass is estimated to be 3.08 Msun and has a main-sequence plus cooling age of roughly 900 Myrs.

astro-ph.SR↗

arXiv2022

Asteroseismology of the DAV star L19-2

L19-2 is a DAV star, which has been intermittently observed from 1976 to 2013. Five independent pulsation modes of 350\,s, 192\,s, 143\,s, 118\,s, and 113\,s are identified. The five modes can be used to constrain the fitting models. The rates of period change can be obtained through the O-C method for modes of 192\,s and 113\,s, which can be used to study the evolution effect of DAV stars. Using the \texttt{WDEC} (2018 version), a large sample DAV star models are evolved. The theoretical modes are calculated and used to fit the observed modes. After fine model fittings, we obtain an optimal model with an absolute difference of $\Phi$ = 0.06\,s. By parameterizing the core oxygen profile, the \texttt{WDEC} (2018 version) procedure can greatly reduce the fitting error of asteroseismological model. According to our optimal model, the distance obtained through the model luminosity is only 1\% different from that reported by the Gaia Data Release 2. The L19-2 is a massive and hot DAV star with relatively a thick H atmosphere and a thick He layer. The stellar parameters and the rates of period change of our optimal model are a little modifications to that of the previous work. Our optimal model has a large central oxygen abundance. The central oxygen abundance is strongly correlated with the previous physical process of stellar evolution. A lot of asteroseismological work on white dwarfs have an opportunity to explore the progenitor stars.

astro-ph.SR↗

arXiv2020

Asteroseismology of the DAV star R808

The DAV star R808 was observed by 13 different telescopes for more than 170 hours in April 2008 on the WET run XCOV26. 25 independent pulsation frequencies were identified by this data set. We assumed 19 $m$ = 0 modes and performed an asteroseismological study on those 19 modes. We evolve grids of DAV star models by \texttt{WDEC} adopting the element diffusion scheme with pure and screened Coulomb potential effect. The core compositions are from white dwarf models evolved by \texttt{MESA}, which are thermal nuclear burning results. Our best fitting model is from the screened Coulomb potential scenario, which has parameters of log($M_{\rm He}/M_{\rm *}$) = -2.4, log($M_{\rm H}/M_{\rm *}$) = -5.2, $T_{\rm eff}$ = 11100\,K, $M_{\rm *}$ = 0.710\,$M_{\odot}$, log$g$ = 8.194, and $σ_{RMS}$ = 2.86\,s. The value of $σ_{RMS}$ is the smallest among the four existing asteroseismological work. The average period spacing is 46.299\,s for $l$ = 1 modes and 25.647\,s for $l$ = 2 modes. The other 6 observed modes can be fitted by $m$ $\neq$ 0 components of some modes for our best fitting model. Fitting the 25 observed modes, we obtain a $σ_{RMS}$ value of 2.59\,s. Considering the period spacings, we also assume, that at least in one case, we detect an $l$ = 2 trapped mode.

astro-ph.SR↗