arXiv subjects

Xiaodong Xu

Publications and source records attributed to Xiaodong Xu.

At least 37 records · Page 2Linked to original sources

arXiv2026

Semantic-based Internet of Embodied Intelligence: Visions and Frontiers

Recent advances in generative artificial intelligence (AI) and embodied intelligence (EI) enable autonomous agents to interact with the physical world. However, scaling these systems into networks of multiple agents, namely the Internet of EI (IoEI), faces critical bottlenecks. These include the overhead of massive multimodal data transmission and the decoupling of logical reasoning from physical constraints. To address these challenges, we envision the Semantic-based IoEI (SIoEI), which leverages semantic information as a unified metric throughout the agent lifecycle. We systematically define four key dimensions of EI: perception, intelligence, control, and communication. We further elaborate how semantic empowerment revolutionizes environmental perception, cognition and task planning, action generation and robust control, and communication and networking. We also present a case study to verify that, the semantic-empowered end-to-end process significantly improves channel robustness and reduces end-to-end latency for EI. Finally, we outline critical open research directions for the SIoEI paradigm.

eess.SP↗

arXiv2026

Effective Depth in Joint Source-Channel Coding: An Implicit Equilibrium Analysis

A fundamental design question in deep joint source-channel coding (Deep JSCC) remains insufficiently explored: given a channel signal-to-noise ratio (SNR), what effective computation depth is required for semantic reconstruction? Existing Deep JSCC systems typically employ fixed-depth neural architectures selected through empirical hyperparameter tuning, which may lead to unnecessary computation under favorable channel conditions and insufficient refinement under severe channel noise. This paper proposes \emph{Implicit-JSCC}, an implicit equilibrium framework in which semantic encoding and decoding are formulated as fixed-point equilibrium processes. The effective encoder and decoder depths are determined by residual-based solver convergence rather than manually predefined layer numbers, while parameter sharing across equilibrium iterations enables depth-independent parameter complexity. To analyze the resulting effective-depth behavior, we develop a Gaussian-process-inspired kernel evolution framework that models equilibrium iterations as an effective-depth propagation process. Since channel noise is injected between the encoder and decoder, the analysis tracks channel-induced representation perturbations across receiver-side equilibrium iterations and derives a theory-guided depth--SNR relationship. After offline calibration of the system-specific parameters, the resulting model characterizes the required receiver-side refinement depth under different SNRs. Extensive experiments show that Implicit-JSCC achieves competitive reconstruction performance while enabling residual-based adaptive inference and controllable computation--quality tradeoffs. The depth--SNR model further provides a characterization of the SNR-dependent refinement depth required to reach a prescribed perturbation tolerance.

eess.SP↗

arXiv2026

Multiple closely spaced transitions and multi-band Hall response in clean ScV$_6$Sn$_6$

The kagome metal ScV$_6$Sn$_6$ has attracted attention as a platform for exploring the interplay between charge density wave (CDW) order and symmetry-breaking phenomena, including a recently reported intermediate phase and a low-field Hall anomaly that has been attributed to an anomalous Hall effect (AHE). The interpretation of both observations has been limited by the modest sample quality achieved by previous growth procedures, which produced crystals with in-plane residual resistivity ratios (RRR) of at most $\approx$9. Here, we report a simple modification of the flux growth procedure that yields ScV$_6$Sn$_6$ single crystals with RRR exceeding 50, more than five times the previous highest reported value, and use this expanded mobility range to revisit both the symmetry and the magnetotransport of the CDW phase. We resolve a sequence of closely spaced transitions in the immediate vicinity of $T_{CDW}$ that emerges above a sharp threshold of RRR $\approx 4$, and demonstrate through elastoresistivity that the intermediate phase breaks the three-fold rotational symmetry of the parent lattice. We examine the Hall response from both the parent samples across the full RRR range as well as Cr-doped samples, and conclude it is quantitatively inconsistent with an intrinsic AHE and is instead explained by ordinary multi-band transport involving small, high-mobility pockets identified through quantum oscillations. These results refine the symmetry-breaking landscape of ScV$_6$Sn$_6$ and establish systematic mobility tuning as a diagnostic for disentangling an intrinsic AHE from multi-band Hall contributions in kagome CDW systems.

cond-mat.str-el↗

arXiv2026

Lightweight Multi-Vehicle Collaborative Perception Acceleration with Fusion Position Adjustment

Multi-vehicle collaborative perception (MvCP) is considered as a key technology to facilitate automated driving (AD), where real-time MvCP under limited resources is significant for reliable AD. In this paper, we formulate a lightweight acceleration scheme for intermediate-fusion (IF) MvCP, which can adapt to both situations of limited computation and communication resources. We provide a relaxed definition conditional additivity and analyze the conditional additivity for various DNN linear layers. On this basis, we focus on the IF-MvCP based on additive feature fusion, and derive the MvCP precision consistency of the forward and backward feature fusion position (FP) adjustments among linear layers. Through experiments, we further validate the precision consistency of the FP adjustment method. Moreover, we propose an FP adjustment among linear layers (FALL) scheme for MvCP acceleration without precision loss theoretically. Simulation results show that the proposed FALL can reduce MvCP latency by up to 74.8% under limited communication resources and by up to 30.3% under limited computation resources.

cs.DC↗

arXiv2026

Electrically Programmable Correlated Topology and Magnetism in a Moiré Trilayer

Strong electron-electron interactions underlie a wide range of quantum many-body phenomena, including magnetism, superconductivity, and charge fractionalization. A central goal is to achieve in situ control over lattice geometry, bandwidth, and band topology within a single platform. Here we realize such an electrically programmable quantum many-body system in an alternating twisted trilayer MoTe$_2$, where an out-of-plane displacement field continuously modifies the layer polarization, effective lattice, and topology of the moiré bands. At zero displacement field, the system realizes a triangular lattice hosting a correlated insulator at one hole per moiré unit cell ($ν= -1$). Doping this state produces strongly asymmetric magnetic responses: double-exchange-like ferromagnetism for $|ν| > 1$, and signatures of spin polarons and antiferromagnetism for $|ν| < 1$. At large displacement field, interlayer hybridization reconstructs the electronic structure into a honeycomb lattice with a flat Chern band, supporting integer and fractional Chern insulators. Magneto-optical measurements further reveal the signatures of gap closure and Landau-level formation from a spin-polarized Fermi surface near the crossover between the two regimes. These results establish a unified, electrically tunable platform in which correlated magnetism and topological states emerge from a single controllable band structure.

cond-mat.mes-hall↗

arXiv2026

SA-RA-JSCC: SNR-Adaptive and Semantic-Rate-Aware Joint Source-Channel Coding

In joint source-channel coding (JSCC)-based semantic communication systems, achieving stable and reliable image semantic transmission under channel constraints remains a key challenge. In most channel adaptation modules, the signal-to-noise ratio (SNR) is often injected into each layer of a channel-adaptation model in an independent and layer-wise manner, which undermines global coordination across layers. Therefore, consistent noise-robust representations may fail to be learned throughout the model. To address this problem, we propose SA-RA-JSCC, a novel channel-adaptive JSCC model. SA-RA-JSCC maps SNR into a unified semantic vector in the feature space and then applies a one-shot global reweighting to the encoded features, thereby enabling globally consistent and learnable channel adaptation. Moreover, in order to further enhance the anti-channel capability of semantic information, a semantic-rate-aware module is introduced, enabling the adaptive policy to respond simultaneously to fluctuations in channel quality and changes in semantic-rate constraints, thereby enhancing global network coordination and channel adaptivity. Extensive experiment results across multiple channels and datasets demonstrate that SA-RA-JSCC significantly outperforms existing semantic communication models in terms of reconstruction metrics such as PSNR and MS-SSIM, exhibiting stronger robustness across a broad range of SNR regimes.

cs.IT↗

arXiv2026

Switching Chern number by sliding and gating in alternately twisted tetralayer MoTe2

Switching the bulk Chern number in topological materials is of central importance for the design of topological electronic devices. Motivated by recent observations of integer and fractional quantum anomalous Hall effects in twisted transition metal dichalcogenides (tTMDs), we realize the switching of valley Chern number through sliding and gating in alternately twisted tetralayer (ATT) MoTe$_{2}$. Using large-scale density functional theory (DFT) calculations, we show that the Chern number of the first $K$-valley moiré band evolves from $+1$ to $-1$ under the interlayer sliding. Furthermore, an applied electric field can switch the valley Chern number from $-1$ to $+1$. Based on the developed continuum model, we reveal that these switching behaviors are caused by the sliding- and gate-dependent intralayer moiré potential distributions across the layers. Our results establish ATT MoTe$_{2}$ as a promising platform for engineering moiré band topologies through the design of moiré potentials with sliding in multilayer moiré systems.

cond-mat.mtrl-sci↗

arXiv2026

STCC: A Unified Source-Channel Semantic Token Coding Framework for Semantic Communications

Deep Joint Source-Channel Coding (JSCC) has emerged as a promising paradigm for overcoming the ``cliff effect" in wireless communications. However, existing Deep JSCC frameworks operate directly on raw analog data such as image pixels rather than the discrete semantic tokens that foundation models require. Moreover, traditional systems employ fixed, hand-designed constellations that treat all tokens equally, leading to catastrophic random errors under channel noise. In this paper, the Semantic Token Codebook Communication (STCC) is proposed as a unified source-channel semantic token coding framework designed to transmit the discrete semantic tokens of foundation models over noisy channels. The core of STCC is the Semantic Token Codec (STC). It accepts discrete tokens as input, which maintains compatibility with foundation models while employing a residual multiple layer perceptron, i.e., MLP-based encoder that learns geometrically structured constellations optimized with a triple-loss objective. This learned mapping forces the channel topology to align with the semantic embedding space, ensuring that channel noise results in topological errors rather than random corruption. This phenomenon is theoretically and empirically characterized, identifying ``Semantic Drift" in symbolic modalities and ``Structural Distortion" in perceptual modalities, where errors shift predictions to semantically or structurally similar tokens. Extensive experiments demonstrate that STCC significantly outperforms traditional systems in low-SNR regimes, effectively converting channel noise into semantic variations without requiring receiver-side modification.

cs.IT↗

arXiv2026

Agentic AI-Enhanced Semantic Communications: Foundations, Architecture, and Applications

Semantic communications (SemCom), as one of the key technologies for 6G, is shifting networks from bit transmission to semantic information exchange. On this basis, introducing agentic artificial intelligence (AI) with perception, memory, reasoning, and action capabilities provides a practicable path to intelligent communications. This paper provides a systematic exposition of how agentic AI empowers SemCom from the perspectives of research foundations, system architecture, and application scenarios. We first provide a comprehensive review of existing studies by agent types, covering embedded agents, large language model (LLM)/large vision model (LVM) agents, and reinforcement learning (RL) agents. Additionally, we propose a unified agentic AI-enhanced SemCom framework covering the application layer, the semantic layer, and the cloud-edge collaboration layer, forming a closed loop from intent to encoding to transmission to decoding to action to evaluation. We also present several typical scenarios, including multi-vehicle collaborative perception, multi-robot cooperative rescue, and agentic operations for intellicise (intelligent and concise) networks. Furthermore, we introduce an agentic knowledge base (KB)-based joint source-channel coding case study, AKB-JSCC, where the source KB and channel KB are built by LLM/LVM agents and RL agents, respectively. Experimental results show that AKB-JSCC achieves higher information reconstruction quality under different channel conditions. Finally, we discuss future evolution and research directions, providing a reference for portable, verifiable, and controllable research and deployment of agentic SemCom.

eess.SY↗

arXiv2026

Semantic Forwarding and Codebook-Enhanced Model Division Multiple Access for Satellite-Terrestrial Networks

Satellite-terrestrial communications are severely constrained by high path loss, limited spectrum resources, and time-varying channel conditions, rendering conventional bit-level transmission schemes inefficient and fragile, particularly in low signal-to-noise ratio (SNR) regimes. Semantic communication has emerged as a promising paradigm to address these challenges by prioritizing task-relevant information over exact bit recovery. In this paper, we propose a semantic forwarding-based semantic communication (SFSC) framework optimized for satellite-terrestrial networks. Specifically, we develop a vector-quantized joint semantic coding and modulation scheme, in which the semantic encoder and semantic codebook are jointly optimized to shape the constellation symbol distribution, improving channel adaptability and semantic compression efficiency. To mitigate noise accumulation and reduce on-board computational burden, we introduce a satellite semantic forwarding mechanism, enabling relay satellites to forward signals directly at the semantic level without full decoding and re-encoding. Furthermore, we design a channel-aware semantic reconstruction scheme based on feature-wise linear modulation (FiLM) to fuse the received SNR with semantic features, enhancing robustness under dynamic channel conditions. To support multi-user access, we further propose a codebook split-enhanced model division multiple access (CS-MDMA) method to improve spectral efficiency. Simulation results show that the proposed SFSC framework achieves a peak signal-to-noise ratio (PSNR) gain of approximately 7.9 dB over existing benchmarks in the low-SNR regime, demonstrating its effectiveness for robust and spectrum-efficient semantic transmission in satellite-terrestrial networks.

cs.IT↗

arXiv2026

SIDMA: Semantic Interleave Division Multiple Access Communication System

Multiple Access (MA) technology has consistently served as the core driving force behind the evolution of mobile communications. As a promising paradigm for next-generation communications, Semantic Communication explores entirely new semantic spatial resources by mining the deep meaning of information. However, the inherent spatial correlation and importance heterogeneity of semantic features often cause semantic collisions and semantic collapse in multi-user concurrent transmission scenarios. To address these challenges, this paper proposes a Semantic Interleaved Division Multiple Access (SIDMA) technique. By utilizing a permutation operator to perform structural whitening on semantic features and combining it with an Importance-aware Power Allocation (ImpPA) module for differentiated protection, SIDMA scatters core features across the interleaving domain and adaptively optimizes power levels based on real-time channel conditions. Simulation results demonstrate that, compared with traditional MA techniques and advanced semantic multiple access schemes including Orthogonal-Model Division Multiple Access (OMDMA), Deep Multiple Access (DeepMA), and Shared Embedding (SE), the proposed SIDMA exhibits superior reconstruction fidelity and scalability in multi-user concurrent transmissions, effectively enhancing the communication quality and robustness in resource-constrained environments.

cs.IT↗

arXiv2026

A cryogenic apparatus for coupling two-dimensional materials to a confocal multimode optical cavity

Two-dimensional van der Waals materials exhibit a variety of correlated electron phases, and optical driving offers a promising route toward manipulating them. For example, cavity-enhanced, continuous-wave (CW) Raman excitation has been suggested as a way to coherently and superradiantly populate phonons or charge density waves via material excitons. A steady-state phonon population may be sustained with sufficiently strong electron-phonon coupling to drive novel collective response. We describe an apparatus built to meet the requirements of such an experimental program: Namely, an ultrahigh-vacuum system housing a length-tunable confocal Fabry-Pérot cavity with an intracavity sample, both cryogenically cooled and stabilized against vibrations. A four-axis nanopositioner aligns the sample and supports electrical leads for sample carrier density modulation and transport measurements. Transmission through the multimode cavity enables in situ sample imaging for alignment; the sample is a transition metal dichalcogenide in this work. Operating near the confocal geometry concentrates the optical field into a localized supermode that substantially enhances light-matter coupling. This enhancement is preserved despite the millimeter-scale cavity length, which provides room for sample alignment and exchange.

quant-ph↗

arXiv2026

Important Bit Prefix M-ary Quadrature Amplitude Modulation for Semantic Communications

M-ary Quadrature Amplitude Modulation (MQAM) is a commonly used channel modulation technology in wireless communication systems. To achieve dedicated channel modulation for semantic communication (SemCom), we propose an Important-Bit-Prefixed MQAM (IBP-MQAM) scheme and derive its approximate expression of important symbol error rate (ISER) and unimportant symbol error rate (USER). By extracting and quantifying text semantics using Latent Dirichlet Allocation (LDA), we verify that IBP-MQAM achieves improved performance over MQAM in SemCom scenarios and further analyze the effects of key system parameters.

eess.SP↗

arXiv2026

Secure Intellicise Wireless Network: Agentic AI for Coverless Semantic Steganography Communication

Semantic Communication (SemCom), leveraging its significant advantages in transmission efficiency and reliability, has emerged as a core technology for constructing future intellicise (intelligent and concise) wireless networks. However, intelligent attacks represented by semantic eavesdropping pose severe challenges to the security of SemCom. To address this challenge, Semantic Steganographic Communication (SemSteCom) achieves ``invisible'' encryption by implicitly embedding private semantic information into cover modality carriers. The state-of-the-art study has further introduced generative diffusion models to directly generate stega images without relying on original cover images, effectively enhancing steganographic capacity. Nevertheless, the recovery process of private images is highly dependent on the guidance of private semantic keys, which may be inferred by intelligent eavesdroppers, thereby introducing new security threats. To address this issue, we propose an Agentic AI-driven SemSteCom (AgentSemSteCom) scheme, which includes semantic extraction, digital token controlled reference image generation, coverless steganography, semantic codec, and optional task-oriented enhancement modules. The proposed AgentSemSteCom scheme obviates the need for both cover images and private semantic keys, thereby boosting steganographic capacity while reinforcing transmission security. The simulation results on open-source datasets verify that, AgentSemSteCom achieves better transmission quality and higher security levels than the baseline scheme.

cs.CR↗

arXiv2026

Ballistic Exciton Flow Driven by Intertwined Exciton-Electron Orders in a Moiré Superlattice

Moiré superlattices of transition-metal dichalcogenides (TMDs) host strongly interacting Bose-Fermi mixtures in which bosonic excitons coexist with correlated electron lattices. Using ultrafast, time- and energy-resolved photoluminescence (PL) and reflectance microscopy, we show that strong exciton-electron and exciton-exciton repulsion can enable collective ballistic exciton transport in a WSe$_2$/WS$_2$ heterobilayer. The ballistic transport is energy-selective: repulsive interactions drive excitons into a higher moiré exciton band, where enhanced intersite hopping enables rapid spatial expansion. Correspondingly, the exciton mean-squared displacement (MSD) exhibits a quadratic time dependence ($\propto t^2$). This ballistic expansion is enhanced at fractional electron fillings where the electrons form generalized Wigner-crystal (GWC) orders. Afterwards, the system transitions into a mixed electron-exciton Mott state as Auger recombination and density depletion conclude the ballistic expansion. A one-dimensional Bose-Fermi Hubbard model solved using density-matrix renormalization group (DMRG) qualitatively reproduces the measured exciton transport and time-dependent response. It further confirms that strong cross-species interactions allow the electron crystal to perforate the exciton Mott background, accelerating its melting and enhancing exciton motion. Our results establish moiré TMDs as highly tunable platforms for realizing strongly interacting Bose-Fermi mixtures, which we employ here to demonstrate real-time control of intertwined bosonic and electronic order and to establish a route to the exciton insulator-fluid transition.

cond-mat.str-el↗

arXiv2026

IPRU: Input-Perturbation-based Radio Frequency Fingerprinting Unlearning for LAWNs

Radio Frequency Fingerprinting (RFF) is a key technology for identity authentication in wireless networks. However, due to the rapid dynamics of Autonomous Aerial Vehicles (AAVs) in low-altitude wireless networks, RFF models require parameter updates to maintain authentication performance, posing a major challenge to existing schemes. Conventional retraining approaches for handling departed or compromised AAVs are computationally prohibitive and risk retaining polluted features, which compromises both authentication security and user privacy. To address these limitations, we propose an Input-Perturbation-based RFF Unlearning (IPRU) scheme. By optimizing a universal Fingerprint Forget Vector (FFV) as a lightweight input perturbation, IPRU successfully erases the fingerprints of target AAVs without modifying the RFF model parameters, achieving an effective balance between efficient unlearning and preserved authentication performance. A combinatorial optimization strategy further enables multi-AAV forgetting on demand. The simulation results demonstrate that IPRU achieves 1.41% unlearning accuracy, 99.41% remaining accuracy, and 100% resistance to membership inference attack, while running 5.79X faster than retraining and 2.1X faster than the baseline scheme.

eess.SP↗

arXiv2026

Van Hove Singularity-Driven Topological Magnetism in Twisted MoTe2

Van Hove singularities (vHSs) strongly amplify electron interactions and can stabilize correlated phases in topological bands. Here we report signatures of topological magnetism in large-angle twisted bilayer MoTe2 driven by the interplay of vHSs, strong correlations, and valley topology. In a 4.8 degree device, electrostatic tuning to a vHS produces a spontaneous anomalous Hall hot spot near nu = -1. Combined transport and reflective magnetic circular dichroism measurements indicate that this regime is not governed by magnetization alone, but instead emerges from a correlated intervalley-coherent antiferromagnetic state that evolves with doping into a canted phase. With increasing magnetic field, the Hall response develops an additional finite-field component consistent with a topological Hall effect from a noncoplanar spin texture, before transitioning into a C = -1 Chern insulator. Our results establish tunable vHSs in moire topological bands as a route to chiral magnetism and engineering topological phase transitions.

cond-mat.mes-hall↗

arXiv2026

Record magnetoresistance, enhanced superconductivity, and fermiology in WTe2

The diverse electronic properties of transition metal chalcogenides can be very sensitive to crystal imperfections. A new crystal growth technique, known as horizontal flux transport, offers a route to improved crystal quality. By refining this technique and applying it to the topological semimetal WTe2, we achieved crystals with an order of magnitude less disorder as determined by electrical transport and scanning tunneling microscopy measurements. At low temperatures these crystals exhibit the largest magnetoresistance reported in a metal. Exfoliated monolayers show quantum oscillations for the first time in the electrostatically doped metallic states, enabling determination of band degeneracies and the valley splitting induced by an electric field. Moreover, they exhibit a gated superconducting dome with a greatly enhanced critical temperature approaching 1.8 K. This advance opens up new avenues for employing WTe2 in topological electronics and gated superconducting devices, and promises comparable breakthroughs with other chalcogenides.

cond-mat.supr-con↗