arXiv subjects

Liang Wu

Publications and source records attributed to Liang Wu.

At least 73 records · Page 4Linked to original sources

arXiv2026

Observation of Room-temperature Charge Density Wave Correlations via Coherent Phonon Spectroscopy in Sn-doped Kagome Superconductor CsV$_3$Sb$_5$

In this work, we perform ultrafast time-resolved reflectivity measurements to track the evolution of charge density wave (CDW) correlations in Sn-doped Kagome superconductor CsV$_3$Sb$_{5-x}$Sn$_x$. By extracting the coherent phonon spectrum, we evidence robust signatures of CDW correlations at temperature and doping ranges far beyond the phase boundary of long-range CDW order. Remarkably, we unveil short-range CDW correlations survive up to room temperature in $x = 0.32$ Sn-doped CsV$_3$Sb$_5$, supported by synchrotron X-ray diffraction measurements. We point out the introduction of quenched disorder by Sn doping can pin the CDW and form static short-range CDW, which can explain the observed persistent CDW signatures. Our results thus corroborate the ubiquity and robustness of CDW correlations in Sn-doped CsV$_3$Sb$_5$ and provide new insights on the role of disorders on the CDW correlations in AV$_3$Sb$_5$ family.

cond-mat.str-el↗

arXiv2026

Revealing Rotational Symmetry Breaking Charge-density Wave Order in Kagome Superconductor (Rb, K)V$_3$Sb$_5$ by Ultrafast Pump-probe Experiments

The recently discovered Kagome superconductor AV$_3$Sb$_5$ (where A refers to K, Rb, Cs) has stimulated widespread research interest due to its interplay of non-trivial topology and unconventional correlated physics including charge-density waves (CDW) and superconductivity. The essential prerequisite to understanding the microscopic mechanisms of this complex electronic landscape is to unveil the configuration and symmetry of the charge-density wave order. As to now, little consensus has been made on what symmetry is broken. Herein, we clarify the microscopic structure and symmetry breaking of the CDW phase in RbV$_3$Sb$_5$ and KV$_3$Sb$_5$ by ultrafast time-resolved reflectivity. Our approach is based on extracting coherent phonon spectra induced by three-dimensional CDW and comparing them to calculated phonon frequencies via density-functional theory. The combination of these experimental results and calculations provides compelling evidence that the CDW structure of both compounds prevailing up to T$_{\text{CDW}}$ is the 2 $\times$ 2 $\times$ 2 staggered inverse Star-of-David pattern with interlayer $π$ phase shift, in which the six-fold rotational symmetry is broken. These observations thus corroborate six-fold rotational symmetry breaking throughout the CDW phase of RbV$_3$Sb$_5$ and KV$_3$Sb$_5$.

cond-mat.str-el↗

arXiv2026

Time-Certified and Efficient NMPC via Koopman Operator

Certifying and accelerating execution times of nonlinear model predictive control (NMPC) implementations are two core requirements. Execution-time certificate guarantees that the NMPC controller returns a solution before the next sampling time, and achieving faster worst-case and average execution times further enables its use in a wider set of applications. However, NMPC produces a nonlinear program (NLP) for which it is challenging to derive its execution time certificates. Our previous works, \citep{wu2025direct,wu2025time} provide data-independent execution time certificates (certified number of iterations) for box-constrained quadratic programs (BoxQP). To apply the time-certified BoxQP algorithm \citep{wu2025time} for state-input constrained NMPC, this paper i) learns a linear model via Koopman operator; ii) proposes a dynamic-relaxation construction approach yields a structured BoxQP rather than a general QP; iii) exploits the structure of BoxQP, where the dimension of the linear system solved in each iteration is reduced from $5N(n_u+n_x)$ to $Nn_u$ (where $n_u, n_x, N$ denote the number of inputs, states, and length of prediction horizon), yielding substantial speedups (when $n_x \gg n_u$, as in PDE control).

eess.SY↗

arXiv2026

Efficient and Robust p-type Transistor based on Ultra-wide-bandgap Semiconductor

The p-type transistor is an indispensable component of semiconductor technology, enabling complementary operation with n-channel transistors for computation, storage, and communication. Achieving both high robustness and high efficiency is highly desirable but challenging for p-type transistors due to limited semiconductors with reliable hole transport and their high activation energies. Here, we achieved a robust yet efficient p-type transistor by heterogeneously integrating an ultra-wide-bandgap semiconductor and a high-k dielectric layer through van der Waals integration. The p-type transistor employs a two-dimensional hole channel on hydrogenated diamond (bandgap 5.6 eV) combined with a high-k (30.5) SrTiO3 perovskite membrane. At room temperature, the transistor exhibits stable operation with a high on-current (~200 mA/mm), low subthreshold swing (70 mV/dec), high hole mobility (566 cm^2/Vs to 572 cm^2/Vs) and high on-off ratio (~10^9). Furthermore, tuning annealing temperature allows operation in either enhancement or depletion mode. The robust p-type transistor with high efficiency holds great potential for future power electronics, UV optoelectronics, and harsh-environment electronic applications.

cond-mat.mtrl-sci↗

arXiv2026

A Generalist Foundation Model for Total-body PET/CT Enables Diagnostic Reporting and System-wide Metabolic Profiling

Total-body PET/CT enables system-wide molecular imaging, but heterogeneous anatomical and metabolic signals, approximately 2 m axial coverage, and structured radiology semantics challenge existing medical AI models that assume single-modality inputs, localized fields of view, and coarse image-text alignment. We introduce SDF-HOLO (Systemic Dual-stream Fusion Holo Model), a multimodal foundation model for holistic total-body PET/CT, pre-trained on more than 10,000 patients. SDF-HOLO decouples CT and PET representation learning with dual-stream encoders and couples them through a cross-modal interaction module, allowing anatomical context to refine PET aggregation while metabolic saliency guides subtle morphological reasoning. To model long-range dependencies across the body, hierarchical context modeling combines efficient local windows with global attention. To bridge voxels and clinical language, we use anatomical segmentation masks as explicit semantic anchors and perform voxel-mask-text alignment during pre-training. Across tumor segmentation, low-dose lesion detection, and multilingual diagnostic report generation, SDF-HOLO outperforms strong task-specific and clinical-reference baselines while reducing localization errors and hallucinated findings. Beyond focal interpretation, the model enables system-wide metabolic profiling and reveals tumor-associated fingerprints of inter-organ metabolic network interactions, providing a scalable computational foundation for total-body PET/CT diagnostics and system-level precision oncology.

cs.CV↗

arXiv2026

Least-Squares Multi-Step Koopman Operator Learning for Model Predictive Control

MPC is widely used in real-time applications, but practical implementations are typically restricted to convex QP formulations to ensure fast and certified execution. Koopman-based MPC enables QP-based control of nonlinear systems by lifting the dynamics to a higher-dimensional linear representation. However, existing approaches rely on single-step EDMD. Consequently, prediction errors may accumulate over long horizons when the EDMD operator is applied recursively. Moreover, the multi-step prediction loss is nonconvex with respect to the single-step EDMD operator, making long-horizon model identification particularly challenging. This paper proposes a multi-step EDMD framework that directly learns the condensed multi-step state-control mapping required for Koopman-MPC, thereby bypassing explicit identification of the lifted system matrices and subsequent model condensation. The resulting identification problem admits a convex least-squares formulation. We further show that the problem decomposes across prediction horizons and state coordinates, enabling parallel computation and row-wise $\ell_1$-regularization for automatic dictionary pruning. A non-asymptotic finite-sample analysis demonstrates that, unlike one-step EDMD, the proposed method avoids error compounding and yields error bounds that depend only on the target multi-step mapping. Numerical examples validate improved long-horizon prediction accuracy and closed-loop performance.

eess.SY↗

arXiv2026

Sporadic Creutzfeldt Jakob disease presenting with cerebral atrophy following traumatic brain injury mimicking hydrocephalus a case report and literature review

Introduction Sporadic Creutzfeldt Jakob disease sCJD is a rapidly progressive neurodegenerative disease without effective treatment that usually results in death within one year. The recently applied methods have improved the accuracy of the disease diagnosis and the specific radiological findings provide the necessary information for differential diagnosis. Research question The research is aimed to provide a different perspective on the development of CJD and associated literature review. Materials and methods The study presents a case who presented cognitive deficits, gait instability, and urinary and fecal incontinence suffered from traumatic brain injury eight months ago before admission with cerebral ventricle dilation on CT images. Furthermore, studies describe relevant cases are also included. Results The patients symptoms got deteriorated. Further examinations, including 14-3-3 and tau proteins in the cerebrospinal fluid CSF, MRI, and EEG, confirmed the patients diagnosis of sCJD. He returned to the local hospital for the conservative treatment without effective medical intervention. Conclusion This case illustrates the diagnostic process of CJD and underscores the importance of distinguishing rare disorders from common conditions to achieve a comprehensive understanding of the disease.

q-bio.NC↗

arXiv2025

HunyuanOCR Technical Report

This paper presents HunyuanOCR, a commercial-grade, open-source, and lightweight (1B parameters) Vision-Language Model (VLM) dedicated to OCR tasks. The architecture comprises a Native Vision Transformer (ViT) and a lightweight LLM connected via an MLP adapter. HunyuanOCR demonstrates superior performance, outperforming commercial APIs, traditional pipelines, and larger models (e.g., Qwen3-VL-4B). Specifically, it surpasses current public solutions in perception tasks (Text Spotting, Parsing) and excels in semantic tasks (IE, Text Image Translation), securing first place in the ICDAR 2025 DIMT Challenge (Small Model Track). Furthermore, it achieves state-of-the-art (SOTA) results on OCRBench among VLMs with fewer than 3B parameters. HunyuanOCR achieves breakthroughs in three key aspects: 1) Unifying Versatility and Efficiency: We implement comprehensive support for core capabilities including spotting, parsing, IE, VQA, and translation within a lightweight framework. This addresses the limitations of narrow "OCR expert models" and inefficient "General VLMs". 2) Streamlined End-to-End Architecture: Adopting a pure end-to-end paradigm eliminates dependencies on pre-processing modules (e.g., layout analysis). This fundamentally resolves error propagation common in traditional pipelines and simplifies system deployment. 3) Data-Driven and RL Strategies: We confirm the critical role of high-quality data and, for the first time in the industry, demonstrate that Reinforcement Learning (RL) strategies yield significant performance gains in OCR tasks. HunyuanOCR is officially open-sourced on HuggingFace. We also provide a high-performance deployment solution based on vLLM, placing its production efficiency in the top tier. We hope this model will advance frontier research and provide a solid foundation for industrial applications.

cs.CV↗

arXiv2025

Electrical Modulation and Probing of Antiferromagnetism in Hybrid Multiferroic Heterostructures

The unique features of ultrafast spin dynamics and the absence of macroscopic magnetization in antiferromagnetic (AFM) materials provide a distinct route towards high-speed magnetic storage devices with low energy consumption and high integration density. However, these advantages also introduce challenges in probing and controlling AFM order, thereby restricting their practical applications. In this study, we demonstrate an all-electric control and probing of the AFM order in heavy metal (HM)/AFM insulator (AFMI) heterostructures on a ferroelectric substrate at room temperature (RT). The AFM order was detected by the anomalous Hall effect (AHE) and manipulated by the ferroelectric field effect as well as the piezoelectric effect in heterostructures of Pt/NiO/0.7Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_{3}$--0.3PbTiO$_{3}$ (PMN--PT). The non-volatile control of AFM order gives rise to a 33\% modulation of AHE, which is further evidenced by synchrotron-based X-ray magnetic linear dichroism (XMLD). Combined with the $in$-$situ$ piezoelectric response of AHE, we demonstrate that ferroelectric polarization contributes mainly to the control of the AFM order. Our results are expected to have broader implications for efficient spintronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Arbitrarily Small Execution-Time Certificate: What was Missed in Analog Optimization

Numerical optimization (solving optimization problems using digital computers) currently dominates but has three major drawbacks: high energy consumption, poor scalability, and lack of an execution time certificate. To address these challenges, this article explores the recent resurgence of analog computers, proposing a novel paradigm of arbitrarily small execution-time-certified analog optimization (solving optimization problems via analog computers). To achieve ultra-low energy consumption, this paradigm transforms optimization problems into ordinary differential equations (ODEs) and leverages the ability of analog computers to naturally solve ODEs (no need for time discretization) in physically real time. However, this transformation can fail if the optimization problem, such as the general convex nonlinear programs (NLPs) considered in this article, has no feasible solution. To avoid transformation failure and enable infeasibility detection, we introduce the homogeneous monotone complementarity problem formulation for convex NLPs. To achieve scalability and an execution time certificate, this paper introduces the Newton-based fixed-time-stable scheme for the transformed ODE, whose settling time $T_p$ can be prescribed by choosing the ODE's time coefficient as $k=\fracπ{2T_p}$. This equation certifies that the settling time (execution time) is independent of the dimension of the optimization problems and can be arbitrarily small if the analog computer allows.

math.OC↗

arXiv2025

Terahertz Landau level spectroscopy of Dirac fermions in millimeter-scale twisted bilayer graphene

Exotic electronic physics including correlated insulating states and fractional Chern insulators have been observed in twisted bilayer graphene in a magnetic field when the Fermi velocity vanishes, however a question remains as to the stability of these states which is controlled by the gap to the first excited state. Free-space terahertz magneto-optics can directly probe the gap to charge excitations which bounds the stability of electronic states, but this measurement has thus-far been inaccessible due to the micron size of twisted bilayer graphene samples, while the wavelength of terahertz light is up to a millimeter. Here we leverage advances in fabrication to create twisted bilayer graphene samples over 5 mm x 5 mm in size with a uniform twist angle and study the magnetic field dependence of the cyclotron resonance by a complex Faraday rotation experiment in p-doped large angle twisted bilayer graphene. These measurements directly probe charge excitations in inter-Landau level transitions and determine the Fermi velocity as a function of twist angle.

cond-mat.mes-hall↗

arXiv2025

A Time-certified Predictor-corrector IPM Algorithm for Box-QP

Minimizing both the worst-case and average execution times of optimization algorithms is equally critical in real-time optimization-based control applications such as model predictive control (MPC). Most MPC solvers have to trade off between certified worst-case and practical average execution times. For example, our previous work [1] proposed a full-Newton path-following interior-point method (IPM) with data-independent, simple-calculated, and exact $O(\sqrt{n})$ iteration complexity, but not as efficient as the heuristic Mehrotra predictor-corrector IPM algorithm (which sacrifices global convergence). This letter proposes a new predictor-corrector IPM algorithm that preserves the same certified $O(\sqrt{n})$ iteration complexity while achieving a $5\times$ speedup over [1]. Numerical experiments and codes that validate these results are provided.

math.OC↗

arXiv2025

A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control

This paper proposes a cascaded control framework for quadrotor trajectory tracking with formal safety guarantees. First, we design a controller consisting of an outer-loop position model predictive control (MPC) and an inner-loop nonlinear attitude control, enabling decoupling of position safety and yaw orientation. Second, since quadrotor safety constraints often involve high relative degree, we adopt high order control barrier functions (HOCBFs) to guarantee safety. To employ HOCBFs in the MPC formulation that has formal guarantees, we extend HOCBFs to sampled-data HOCBF (SdHOCBFs) by introducing compensation terms, ensuring safety over the entire sampling interval. We show that embedding SdHOCBFs as control-affine constraints into the MPC formulation guarantees both safety and optimality while preserving convexity for real-time implementations. Finally, comprehensive simulations are conducted to demonstrate the safety guarantee and high efficiency of the proposed method compared to existing methods.

eess.SY↗

arXiv2025

Artificial ferroelectric-like hysteresis in antiferroelectrics with non-uniform disorder

Antiferroelectrics exhibit unique double-hysteresis polarization loops, which have garnered significant attention due to their potential applications such as energy storage, electromechanical transduction, as well as synapse devices. However, numerous antiferroelectric materials have been reported to display signs of hysteresis loops resembling those of ferroelectric materials, and a comprehensive understanding remains elusive. In this work, we provide a phenomenological model that reproduces such widely observed artificial ferroelectric hysteresis with a superposition of numerous disordered antiferroelectric loops that have varying antiferroelectric-to-ferroelectric transition fields, particularly when these field ranges intersect. Experimentally, we realized such artificial ferroelectric-like hysteresis loops in the prototypical antiferroelectric PbZrO$_3$ and PbHfO$_3$ thin films, by introducing non-uniform local disorder (e.g., defects) via fine-tuning of the film growth conditions. These ferroelectric-like states are capable of persisting for several hours prior to transitioning back into the thermodynamically stable antiferroelectric ground state. Those results provide insights into the fundamental impact of disorder on the AFE properties and new possibilities of disorder-tailored functions.

cond-mat.mtrl-sci↗

arXiv2025

Persistent Fluctuating Superconductivity and Planckian Dissipation in Fe(Te,Se)

Increasingly intricate phase diagrams in new classes of superconductors host fascinating interactions between superconductivity, diverse quantum phases, and quantum critical dynamics. The native superfluids, however, often exhibit much lower density and much greater inhomogeneity than conventional superfluids. This may render the superconductivity susceptible to fluctuations that are ordinarily assumed to be frozen out far below the superconducting transition temperature $T_c$, calling into question the degree to which the superconducting state is fully coherent. In this work, we leverage terahertz spectroscopy to demonstrate strongly fluctuating superconductivity in topological compositions of the multiband iron-based superconductor Fe(Te,Se). These fluctuations are found to persist undiminished far below $T_c$ and converge upon the limit of Planckian dissipation above $T_c$. These results indicate that extended quantum fluctuations dominate the electrodynamics of both the superconducting and Planckian-dissipative precursor states of Fe(Te,Se), and demonstrate that the assumption of phase coherence must be rigorously validated in emerging classes of unconventional superconductors.

cond-mat.supr-con↗

arXiv2025

Coherent Phonon Pairs and Rotational Symmetry Breaking of Charge Density Wave Order in the Kagome Superconductor CsV$_3$Sb$_5$

In this work, we perform ultrafast time-resolved reflectivity measurements to study the symmetry breaking in the charge-density wave (CDW) phase of CsV$_3$Sb$_5$. By extracting the coherent phonon spectrum in the CDW phase of CsV$_3$Sb$_5$, we discover close phonon pairs near 1.3 THz and 3.1 THz, as well as a new mode at 1.84 THz. The 1.3 THz phonon pair and the 1.84 THz mode are observed up to the CDW transition temperature. Combining density-functional theory calculations, we point out these phonon pairs arise from the coexistence of Star-of-David and inverse Star-of-David distortions combined with six-fold rotational symmetry breaking. An anisotropy in the magnitude of transient reflectivity change is also revealed at the onset of CDW order. Our results thus indicate broken six-fold rotational symmetry in the charge-density wave state of CsV$_3$Sb$_5$, along with the absence of nematic fluctuation above T$_{\text{CDW}}$. Meanwhile, the measured coherent phonon spectrum in the CDW phase of CsV$_3$Sb$_{5-\text{x}}$Sn$_\text{x}$ with x = 0.03-0.04 matches with staggered inverse Star-of-David with interlayer $π$ phase shift. This CDW structure contrasts with undoped CsV$_3$Sb$_5$ and explains the evolution from phonon pair to a single mode at 1.3 THz by x = 0.03-0.04 Sn-doping.

cond-mat.mtrl-sci↗

arXiv2025

Joint Waveform Design for MIMO-OFDM DFRC Systems

Dual-functional radar-communication (DFRC) has attracted considerable attention. This paper considers the frequency-selective multipath fading environment and proposes DFRC waveform design schemes based on multiple-input and multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques. In the proposed waveform design schemes, the Cramer-Rao bound (CRB) of the radar system, the inter-stream interference (ISI) and the achievable rate of the communication system, are respectively considered as the performance metrics. In this paper, we focus on the performance trade-off between the radar system and the communication system, and the optimization problems are formulated. In the ISI minimization based waveform design scheme, the optimization problem is convex and can be easily solved. In the achievable rate maximization based waveform design scheme, we propose a water-filling (WF) and sequential quadratic programming (SQP) based algorithm to derive the covariance matrix and the precoding matrix. Simulation results validate the proposed DFRC waveform designs and show that the achievable rate maximization based scheme has a better performance than the ISI minimization based scheme.

cs.IT↗

arXiv2025

Etching-free dual-lift-off for direct patterning of epitaxial oxide thin films

Although monocrystalline oxide films offer broad functional capabilities, their practical use is hampered by challenges in patterning. Traditional patterning relies on etching, which can be costly and prone to issues like film or substrate damage, under-etching, over-etching, and lateral etching. In this study, we introduce a dual-lift-off method for direct patterning of oxide films, circumventing the etching process and associated issues. Our method involves an initial lift-off of amorphous Sr$_3$Al$_2$O$_6$ or Sr$_4$Al$_2$O$_7$ ($a$SAO) through stripping the photoresist, followed by a subsequent lift-off of the functional oxide thin films by dissolving the $a$SAO layer. $a$SAO functions as a ``high-temperature photoresist", making it compatible with the high-temperature growth of monocrystalline oxides. Using this method, patterned ferromagnetic La$_{0.67}$Sr$_{0.33}$MnO$_{3}$ and ferroelectric BiFeO$_3$ were fabricated, accurately mirroring the shape of the photoresist. Our study presents a straightforward, flexible, precise, environmentally friendly, and cost-effective method for patterning high-quality oxide thin films.

cond-mat.mtrl-sci↗