arXiv subjects

Ke Wang

Publications and source records attributed to Ke Wang.

At least 127 records · Page 7Linked to original sources

arXiv2026

MADCrowner: Margin Aware Dental Crown Design with Template Deformation and Refinement

Dental crown restoration is one of the most common treatment modalities for tooth defect, where personalized dental crown design is critical. While computer-aided design (CAD) systems have notably enhanced the efficiency of dental crown design, extensive manual adjustments are still required in the clinic workflow. Recent studies have explored the application of learning-based methods for the automated generation of restorative dental crowns. Nevertheless, these approaches were challenged by inadequate spatial resolution, noisy outputs, and overextension of surface reconstruction. To address these limitations, we propose \totalframework, a margin-aware mesh generation framework comprising CrownDeformR and CrownSegger. Inspired by the clinic manual workflow of dental crown design, we designed CrownDeformR to deform an initial template to the target crown based on anatomical context, which is extracted by a multi-scale intraoral scan encoder. Additionally, we introduced \marginseg, a novel margin segmentation network, to extract the cervical margin of the target tooth. The performance of CrownDeformR improved with the cervical margin as an extra constraint. And it was also utilized as the boundary condition for the tailored postprocessing method, which removed the overextended area of the reconstructed surface. We constructed a large-scale intraoral scan dataset and performed extensive experiments. The proposed method significantly outperformed existing approaches in both geometric accuracy and clinical feasibility.

cs.CV↗

arXiv2026

A Generalist Model Including Evolved Star Mass and Age

Determining precise stellar ages and masses for evolved giants is crucial for Galactic archaeology but challenged by spectral degeneracies. Gaia's low-resolution XP spectra offer a unique opportunity to infer these parameters on a massive scale using data-driven methods. We extend a transformer-based astronomical foundation model to evolved stars, establishing a unified framework to simultaneously predict atmospheric parameters ($T_{\mathrm{eff}}$, $\log g$, $[\mathrm{M}/\mathrm{H}]$) and evolutionary labels (mass, age) with physical consistency. Treating spectra as token sequences, we integrated mass and age into the model's vocabulary. The model is trained on Gaia XP spectra cross-matched with the APOGEE DR17 DistMass catalog. Our generative approach enables flexible input handling, including spectral inpainting and parameter-to-spectrum generation. On an independent test set, the model achieves a prediction scatter of $σ\approx 0.114 \, M_{\odot}$ for mass and $σ\approx 1.334$ Gyr for age. Beyond numerical accuracy, it successfully reproduces the giant branch's mass-luminosity relation and autonomously disentangles interstellar extinction from intrinsic temperature variations without explicit physical priors. It also robustly recovers missing spectral data and estimates reliable uncertainties. Validating that foundation models can internalize stellar physics from data, this physically-aware, probabilistic framework offers a powerful tool for unraveling Milky Way history using large-scale spectroscopic surveys.

astro-ph.SR↗

arXiv2026

From Solver to Tutor: Evaluating the Pedagogical Intelligence of LLMs with KMP-Bench

Large Language Models (LLMs) show significant potential in AI mathematical tutoring, yet current evaluations often rely on simplistic metrics or narrow pedagogical scenarios, failing to assess comprehensive, multi-turn teaching effectiveness. In this paper, we introduce KMP-Bench, a comprehensive K-8 Mathematical Pedagogical Benchmark designed to assess LLMs from two complementary perspectives. The first module, KMP-Dialogue, evaluates holistic pedagogical capabilities against six core principles (e.g., Challenge, Explanation, Feedback), leveraging a novel multi-turn dialogue dataset constructed by weaving together diverse pedagogical components. The second module, KMP-Skills, provides a granular assessment of foundational tutoring abilities, including multi-turn problem-solving, error detection and correction, and problem generation. Our evaluations on KMP-Bench reveal a key disparity: while leading LLMs excel at tasks with verifiable solutions, they struggle with the nuanced application of pedagogical principles. Additionally, we present KMP-Pile, a large-scale (150K) dialogue dataset. Models fine-tuned on KMP-Pile show substantial improvement on KMP-Bench, underscoring the value of pedagogically-rich training data for developing more effective AI math tutors.

cs.CL↗

arXiv2026

Mean Effects on Critical Well-Posedness for Majda-Biello Systems on the Torus

This paper studies how the mean of the initial data $u_0$ affects the critical indices concerning local well-posedness for the following Majda-Biello systems: \[ \left\{\begin{aligned} & u_t + u_{xxx} + vv_x = 0 , \\ & v_t + αv_{xxx} + (uv)_x = 0 , \\ & (u,v) \mid_{t=0} = (u_0, v_0) \in H^s(\mathbb{T}) \times H^s(\mathbb{T}), \end{aligned}\right. \qquad x \in \mathbb{T}, \, t\in \mathbb{R}, \] where $\mathbb{T}$ refers to the periodic torus and the dispersion coefficient $α$ is restricted in $(0,4] \setminus \{1\}$ which corresponds to resonant cases. Previously, under the zero-mean assumption on $u_0$, Oh (Int. Math. Res. Not., (18):3516-3556, 2009) determined the critical indices $s^{*}(α)$ of the Sobolev regularity of the initial data for $C^3$ local well-posedness. In particular, Oh showed that \[ s^{*}(α) = \left\{ \begin{array}{lll} 1, & \text{for $α$ such that $\sqrt{12/α- 3} \in \mathbb{Q}$ }, \\ \frac12, & \text{for a.e. $α$ such that $\sqrt{12/α- 3} \notin \mathbb{Q}$ }. \end{array}\right. \] In this paper, by allowing the mean of $u_0$ to be non-zero, we find that the critical index $s^{*}(α)$ can be lowered from $1$ to $\frac12$ when $\sqrt{12/α- 3} \in \mathbb{Q}$. For other values of $α$, except in a set of zero measure, we also justify the critical index $s^{*}(α)$ to be $\frac12$ regardless of the mean of $u_0$. By subtracting the mean from $u_0$, the original Majda-Biello systems are slightly modified to contain first-order terms but with zero-mean initial data. The key ingredient in our proof is to introduce a refined Diophantine approximation theory to capture the essential resonance effect for the perturbed dispersive structure caused by these additional first-order terms.

math.AP↗

arXiv2026

From Reliability to Security: How RIS-Assisted Adaptive SM and SSK Enhances Wireless Systems

This paper proposes two novel wireless transmission schemes, namely reconfigurable intelligent surface (RIS)-assisted received adaptive spatial modulation (RASM) scheme and RIS-assisted received adaptive space shift keying (RASSK) scheme, designed to enhance spectral efficiency (SE) and physical layer security (PLS). In both proposed schemes, transmitting bits are dynamically mapped at receive antennas by leveraging the characteristics of the RIS in each time slot, which enables the enhancement of signal-to-noise ratio (SNR) at specific selected antennas with nearly few power, thus leading to a reliable and green wireless communication. Unlike conventional fixed-antenna RIS-RSM/GSSK, the term ``adaptive'' indicates the number of active antennas dynamically changes per symbol, conveying extra spatial information to break existing spectral efficiency bottlenecks.This adaptive approach facilitates the conveyance of extra bits to the receiver, which means it needs less cost of radio-frequency chains at transmitter while improving SE. Besides, the proposed schemes offer an inherent PLS security advantage, as the eavesdropper is unable to completely detect signals reflected from the RIS. To comprehensively evaluate the performance of the proposed RASM and RASSK schemes, this paper presents a detailed analytical performance of their spectral efficiency, detection complexity, bit error rate, and secrecy rate, which are accompanied by insightful findings and conclusions. Simulation and analytical results demonstrate the superiority of the proposed schemes, showcasing their improved error performance and robustness against wiretapping, while also highlighting the potential of the RASM and RASSK schemes for future wireless applications.

cs.IT↗

arXiv2026

Layer-polarized Transport via Gate-defined 1D and 0D PN Junctions in Double Bilayer Graphene

We fabricate twisted double bilayer graphene devices with zero twist angle and a set of local top and bottom gates aligned perpendicularly to each other. A 1D PN junction can be electrostatically defined when the gate voltages applied to the top gates are the same but different on the bottom gates. Resistance peaks are observed at finite doping instead of at the charge neutrality points, exhibiting an unconventional broken-cross shape that arises from layer polarization of the P and N region, which can be further enhanced with finite magnetic fields. A 0D point junction (PJ) can be electrostatically defined by applying different gate voltages to the top and bottom gates, such that the P and N sides of the device are connected at a single point in the center of the device. As finite magnetic field B increases, the quantum Hall (QH) states are selectively brought into contact or away from each other depending on their layer polarization, leading to unconventional quantum oscillations which characterize the layer-polarized band-crossing. Our work provides new insights into understanding band-structure evolution and layer polarization in twisted bilayers and paves the way for new device functionality based on manipulating layer-polarized electronic states.

cond-mat.mes-hall↗

arXiv2026

Linear filament and nested cluster evolution tomography (LANCET) I. Capture the evolution of dense gas in 14-parsec filament G316.8

A dynamic view of mass assembly is essential for understanding the formation of massive stars and clusters. Interpreting evolutionary diagnostics from Galactic-wide surveys, however, requires careful control of distance and environmental variations. The G316.8 filament provides an ideal laboratory: a 14-pc nearly linear structure composed of three contiguous subregions with comparable molecular gas reservoirs (~10,000 $M_\odot$ each) but spanning a clear evolutionary sequence from an infrared dark cloud (young) through a massive young stellar object (intermediate) to an HII region (evolved). As part of the Linear filament and nested cluster evolution tomography (LANCET) project, we mapped the full filament with the Atacama Compact Array at 1.3 mm, achieving 0.08 pc resolution over 17.1 pc$^2$. Combined with Herschel and APEX/ArTéMiS data, we derived high-resolution temperature and column-density maps. We quantify structural evolution using dense-fragment statistics, column-density PDFs, and $Δ$-variance analysis. From young to evolved regions, the maximum fragment mass increases from 8 to 490 $M_\odot$, while the dense-gas mass fraction ($>0.5$ g cm$^{-2}$) rises from 0.4% to 9.6%. The N-PDF develops a secondary power-law tail and the $Δ$-variance slope becomes progressively shallower, indicating ongoing assembly of dense sub-parsec structures. Our further ALMA 12m continuum and spectral line data will extend this dynamic scenarios down to 800 AU scale.

astro-ph.GA↗

arXiv2026

Kekulé Superconductivity in Twisted Magic Angle Bilayer Graphene

While it has been one of the most important new physics discoveries in the last decade, the nature of superconductivity in the twisted graphene family remains an unsolved problem. Motivated by recent scanning tunneling experiments that report Kekulé ordering in moiré graphene superconductors, we develop a microscopic theory of this superconductivity for the twisted bilayer system. The pairing we find is an intra-valley, finite-momentum pair-density wave (PDW) that intrinsically carries a Kekulé modulation. This state exhibits four salient features: (i) spontaneous breaking of $C_3$ rotation symmetry, producing nematic order (ii)with triplet pairing; and (iii) a quasiparticle density of states that evolves from a V-shaped profile to a fully gapped, U-shaped spectrum as the attraction increases which is accompanied by (iv) systematic behavior of the temperature dependent zero bias conductance. These features align with key experimental signatures. We find, as well, that with only modest interaction strengths, the state is near to a BEC-like phase, consistent with the observed extremely short coherence lengths. Taken together, these results identify a microscopic intra-valley Kekulé PDW as a compelling candidate for unconventional superconductivity in the twisted graphene family.

cond-mat.supr-con↗

arXiv2026

Flux Pumped Kerr-Free Parametric Amplifier

We propose a flux-pumped superconducting parametric amplifier based on symmetrically threaded superconducting quantum interference devices (SQUIDs) that achieves a Kerr-free operating point under suitable drive conditions. Eliminating the Kerr nonlinearity is advantageous for quantum-limited amplification, as it mitigates unwanted distortions in squeezing and prevents degradation of both gain and quantum efficiency in the high-gain strong drive regime. By replacing the central junction in the symmetrically threaded SQUIDs (STS) configuration with a linear inductor, we find that the Kerr-nonlinearity can be eliminated and the effective Hamiltonian reduces to that of a degenerate parametric amplifier (DPA), up to higher-order corrections in the zero-point fluctuations of the superconducting phase operator. We show that the deviations from ideal DPA behavior introduced by these higher-order terms are significantly weaker than those associated with a Kerr nonlinearity. Consequently, the STS design can be driven strongly while maintaining near-quantum-limited performance at the Kerr-free point. Our analysis predicts phase-preserving gain and efficiency approaching the quantum limit, with robust operation demonstrated up to 25 dB of gain.

quant-ph↗

arXiv2026

Stochastic Design of Active RIS-Assisted Satellite Downlinks under Interference, Folded Noise, and EIRP Constraints

Active reconfigurable intelligent surfaces (RISs) can mitigate the double-fading loss of passive reflection in satellite downlinks. However, their gains are limited by random co-channel interference, gain-dependent amplifier noise, and regulatory emission constraints. This paper develops a stochastic reliability framework for active RIS-assisted satellite downlinks by modeling the desired and interfering channels, receiver noise, and RIS amplifier noise as random variables. The resulting instantaneous signal-to-interference-plus-noise ratio (SINR) model explicitly captures folded cascaded amplifier noise and reveals a finite high-gain SINR ceiling. To guarantee a target outage level, we formulate a chance-constrained max-SINR design that jointly optimizes the binary RIS configuration and a common amplification gain. The chance constraint is handled using a sample-average approximation (SAA) with a violation budget. The resulting feasibility problem is solved as a mixed-integer second-order cone program (MISOCP) within a bisection search over the SINR threshold. Practical implementation is enforced by restricting the gain to an admissible range determined by small-signal stability and effective isotropic radiated power (EIRP) limits. We also derive realization-wise SINR envelopes based on eigenvalue and l1-norm bounds, which provide interpretable performance limits and fast diagnostics. Monte Carlo results show that these envelopes tightly bound the simulated SINR, reproduce the predicted saturation behavior, and quantify performance degradation as interference increases. Overall, the paper provides a solver-ready, reliability-targeting design methodology whose achieved reliability is validated through out-of-sample Monte Carlo testing under realistic randomness and hardware constraints.

eess.SP↗

arXiv2026

Ferroelectric Quantum Point Contact in Twisted Transition Metal Dichalcogenides

In twisted transition metal dichalcogenides (tTMDs), atomic reconstruction gives rise to moiré domains with alternating ferroelectric polarization, whose domain size and overall electric dipole moment are tunable by an out-of-plane electric field. Previous transport measurements in Hall bar devices have successfully demonstrated the overall ferroelectric behavior of tTMDs from a collective ensemble of ferroelectric moiré domains. To locally probe a single ferroelectric moiré domain, we fabricate and study mesoscopic quantum transport via a gate-defined twisted molybdenum disulfide (tMoS2) quantum point contact (QPC). The local property of a single moiré domain is invulnerable to long-range disorder and twist-angle inhomogeneity, resulting in an unusually long conductance plateau with large electrical hysteresis. The comparison between local and global measurements confirms that antiferroelectricity can emerge from alternating polarization of individual ferroelectric domains. Using a QPC as a single charge sensor, we characterize the nature and time scale of different domain evolution mechanisms with single atomic dipole resolution. Our findings shed new light on the microscopic ferroelectric behavior and dynamics within a single tTMD moiré domain, paving the way toward more advanced ferroelectric quantum devices with tunable local Hamiltonian, such as ferroelectric tTMD quantum dots (QDs).

cond-mat.mes-hall↗

arXiv2026

Surface-State-Driven Anomalous Hall Effect in Altermagnetic MnTe Films

Altermagnets have recently emerged as a new class of magnetic materials that combine compensated magnetic order with spin-split electronic band structures. In this work, we employ molecular beam epitaxy to grow MnTe thin films with controlled thickness on InP(111)A substrates. By performing angle-resolved photoemission spectroscopy measurements, we observe a large spin splitting of ~230 meV for bulk bands well below the Fermi level and identify surface states that cross the Fermi level. Electrical transport measurements reveal that a robust anomalous Hall (AH) effect persists down to 2 K and an AH sign reversal occurs near 175 K. By systematically tuning film thickness, growth conditions, and interfacial structure, we demonstrate that the AH response in MnTe films originates from the Berry curvature of surface states rather than from bulk bands. Our first-principles calculations reveal that this surface-state-driven AH effect is imprinted by the bulk altermagnetic order and remains unchanged for terminations with opposite Mn magnetic orientations. Our results establish a unique surface transport probe of bulk altermagnetism, demonstrate interface engineering as an effective route to generate and control the AH effect in altermagnets, and provide a unified understanding of the AH response in altermagentic MnTe films.

cond-mat.mtrl-sci↗

arXiv2026

Analysis of singular subspaces under random perturbations

We present a comprehensive analysis of singular vector and singular subspace perturbations in the signal-plus-noise matrix model with random Gaussian noise. Assuming a low-rank signal matrix, we extend the Davis-Kahan-Wedin theorem in a fully generalized manner, applicable to any unitarily invariant matrix norm, building on previous results by O'Rourke, Vu, and the author. Our analysis provides fine-grained insights, including $\ell_\infty$ bounds for singular vectors, $\ell_{2, \infty}$ bounds for singular subspaces, and results for linear and bilinear functions of singular vectors. Additionally, we derive $\ell_{2,\infty}$ bounds on perturbed singular vectors, taking into account the weighting by their corresponding singular values. Finally, we explore practical implications of these results in the Gaussian mixture model and the submatrix localization problem.

math.ST↗

arXiv2026

Repetitive Penrose process in Kerr-de Sitter black holes

Recently, references [1,2] found that the repetitive Penrose process cannot extract all the extractable rotational energy of a Kerr black hole, and reference [3] found that the repetitive electric Penrose process cannot extract all the electrical energy of a Reissner-Nordström (RN) black hole. This suggests that a law analogous to the third law of thermodynamics exists for the repetitive Penrose process. In this paper, we intend to study the repetitive Penrose process in the Kerr-de Sitter (Kerr-dS) black hole. We will explore influences of the cosmological parameter on the repetitive Penrose process. The results show that, in addition to a similar third law of thermodynamics, the Kerr-dS black hole yields a higher energy return on investment (EROI) and single-extraction energy capability compared to the Kerr black hole. Specifically, the larger the cosmological parameter, the stronger the EROI and the single-extraction energy capability. Furthermore, we also find that at a lower decay radius, the Kerr black hole exhibits a higher energy utilization efficiency (EUE) and more extracted energy after the repetitive Penrose process is completed. However, at a higher decay radius, the situation is reversed, i.e., the Kerr-dS black hole exhibits a higher EUE and more extracted energy, which is due to the existence of stopping condition of the iteration.

gr-qc↗

arXiv2026

Repetitive Penrose Process in Accelerating Kerr Black Holes

This paper investigates the repetitive Penrose process in accelerating Kerr black holes and explores the influence of the acceleration factor on the repetitive Penrose process. After a brief review of accelerating Kerr black holes, we study the fundamental equations of the Penrose process in this spacetime, examine the stopping conditions required for the repetitive Penrose process, and obtain corresponding numerical results. The conclusions indicate that, apart from the third law of thermodynamics similar to previous cases, accelerating Kerr black holes exhibit stronger energy extraction capabilities compared to Kerr black holes during the repetitive Penrose process. Moreover, in prior studies, the energy utilization efficiency was difficult to exceed $50\%$. However, in accelerating Kerr black holes, when the decay radius is relatively small, the energy utilization efficiency can exceed $50\%$, indicating that the reduced extractable energy primarily transforms into extracted energy rather than irreducible mass. On the other hand, when the initial value of the acceleration factor is large, the extractable energy can decrease to nearly zero, which also differs from the case of Kerr black holes in previous studies.

gr-qc↗

arXiv2026

Fuzzy dark matter soliton as gravitational lens

The Schrödinger-Poisson (SP) equations predict fuzzy dark matter (FDM) solitons. Given the FDM mass $\sim10^{-20}\rm~{eV}/c^2$, the FDM soliton in the Milky Way is massive $\sim 10^7~M_{\odot}$ but diffuse $\sim 10{\rm~pc}$. Therefore, such FDM soliton can serve as a gravitational lens for gravitational waves (GWs) with frequency $\sim10^{-8}{\rm~Hz}$. In this paper, we investigate its gravitational lensing effects by numerical simulation of the propagation of GWs through it. We find that the maximum magnification factor of GWs is very small $\sim10^{-4}$, but the corresponding magnification zone is huge $\sim6{\rm~pc}$ for FDM with mass equal to $8\times10^{-21}\rm~{eV}/c^2$. Consequently, this small magnification factor compounding over such large magnification zone results in a small antisotropy of $\sim10^{-4}$ over a large solid angle in the GW background. That level of antisotropy is out of the sensitivity, $<20\%$, of the pulsar timing arrays today.

gr-qc↗

arXiv2026

FullStack-Agent: Enhancing Agentic Full-Stack Web Coding via Development-Oriented Testing and Repository Back-Translation

Assisting non-expert users to develop complex interactive websites has become a popular task for LLM-powered code agents. However, existing code agents tend to only generate frontend web pages, masking the lack of real full-stack data processing and storage with fancy visual effects. Notably, constructing production-level full-stack web applications is far more challenging than only generating frontend web pages, demanding careful control of data flow, comprehensive understanding of constantly updating packages and dependencies, and accurate localization of obscure bugs in the codebase. To address these difficulties, we introduce FullStack-Agent, a unified agent system for full-stack agentic coding that consists of three parts: (1) FullStack-Dev, a multi-agent framework with strong planning, code editing, codebase navigation, and bug localization abilities. (2) FullStack-Learn, an innovative data-scaling and self-improving method that back-translates crawled and synthesized website repositories to improve the backbone LLM of FullStack-Dev. (3) FullStack-Bench, a comprehensive benchmark that systematically tests the frontend, backend and database functionalities of the generated website. Our FullStack-Dev outperforms the previous state-of-the-art method by 8.7%, 38.2%, and 15.9% on the frontend, backend, and database test cases respectively. Additionally, FullStack-Learn raises the performance of a 30B model by 9.7%, 9.5%, and 2.8% on the three sets of test cases through self-improvement, demonstrating the effectiveness of our approach. The code is released at https://github.com/mnluzimu/FullStack-Agent.

cs.SE↗

arXiv2026

MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs

Language models deployed in real-world systems often require post-hoc updates to incorporate new or corrected knowledge. However, editing such models efficiently and reliably-without retraining or forgetting previous information-remains a major challenge. Existing methods for lifelong model editing either compromise generalization, interfere with past edits, or fail to scale to long editing sequences. We propose MEMOIR, a novel scalable framework that injects knowledge through a residual memory, i.e., a dedicated parameter module, while preserving the core capabilities of the pre-trained model. By sparsifying input activations through sample-dependent masks, MEMOIR confines each edit to a distinct subset of the memory parameters, minimizing interference among edits. At inference, it identifies relevant edits by comparing the sparse activation patterns of new queries to those stored during editing. This enables generalization to rephrased queries by activating only the relevant knowledge while suppressing unnecessary memory activation for unrelated prompts. Experiments on question answering, hallucination correction, and out-of-distribution generalization benchmarks for LLaMA-3 and Mistral backbones demonstrate that MEMOIR achieves state-of-the-art performance across reliability, generalization, and locality metrics, scaling to thousands of sequential edits with minimal forgetting.

cs.CL↗