arXiv subjects

Xiaodong Xu

Publications and source records attributed to Xiaodong Xu.

At least 109 records · Page 6Linked to original sources

arXiv2025

Observing the Birth of Rydberg Exciton Fermi Polarons on a Moire Fermi Sea

The optical spectra of two-dimensional (2D) semiconductors are dominated by tightly bound excitons and trions. In the low doping limit, trions are often described as three-body quasiparticles consisting of two electrons and one hole or vice versa. However, trions are more rigorously understood as quasiparticles arising from the interaction between an exciton and excitation of the Fermi sea - referred to as exciton Fermi polaron. Here we employ pump-probe spectroscopy to directly observe the formation of exciton Fermi polarons in a model system composed of a WSe2 monolayer adjacent to twisted bilayer graphene (tBLG). Following the pump-injection of Rydberg excitons in WSe2, a time-delayed probe pulse tracks the development of Rydberg exciton Fermi polarons as interactions with localized carriers in the tBLG moire superlattice evolve. Both the exciton Fermi polaron relaxation rate and binding energy are found to increase with electron or hole density. Our findings provide insight into the optical response of fundamental excitations in 2D Van der Waals systems and reveal how many-body interactions give rise to emergent quasiparticles.

cond-mat.mes-hall↗

arXiv2025

Van der Waals waveguide quantum electrodynamics probed by infrared nano-photoluminescence

Atomically layered van der Waals (vdW) materials exhibit remarkable properties, including highly-confined infrared waveguide modes and the capacity for infrared emission in the monolayer limit. Here, we engineered structures that leverage both of these nano-optical functionalities. Specifically, we encased a photoluminescing atomic sheet of MoTe2 within two bulk crystals of WSe2, forming a vdW waveguide for the embedded light-emitting monolayer. The modified electromagnetic environment offered by the WSe2 waveguide alters MoTe2 spontaneous emission, a phenomenon we directly image with our interferometric nano-photoluminescence technique. We captured spatially-oscillating nanoscale patterns prompted by spontaneous emission from MoTe2 into waveguide modes of WSe2 slabs. We quantify the resulting Purcell-enhanced emission rate within the framework of a waveguide quantum electrodynamics (QED) model, relating the MoTe2 spontaneous emission rate to the measured waveguide dispersion. Our work marks a significant advance in the implementation of all-vdW QED waveguides.

physics.optics↗

arXiv2025

Spinless and spinful charge excitations in moiré Fractional Chern Insulators

Fractionally charged elementary excitations, the quasi-electron and quasi-hole, are one of the hallmarks of the fractional Chern insulator (FCI). In this work, we observe that spontaneous spin polarization in twisted MoTe$_2$ leads to multiple species of low-energy quasi-particles distinguished by their spin quantum numbers. We perform large-scale exact diagonalization (ED) calculations to investigate the nature of these excitations and develop a method to extract their fundamental energetic properties. Focusing on $θ= 3.7^{\circ}$ and filling factor $ν= -2/3$ relevant to recent experiments, we show that spin-preserving (spinless) charge excitations have smaller gap than spin-flipping (spinful) excitations both with and without band mixing. This result is in qualitative agreement with the measured magnetic field dependence of the transport gaps. Beyond the spinless and spinful quasi-particle gaps, we extract the full quasi-electron and quasi-hole ``band structure'' and find significant dispersion with emergent magnetic translation symmetry -- a fundamental departure from the immobile excitations of the quantum Hall fluid. Our results establish a framework for computing the properties of novel elementary excitations in FCIs.

cond-mat.str-el↗

arXiv2025

ICDM: Interference Cancellation Diffusion Models for Wireless Semantic Communications

Diffusion models (DMs) have recently achieved significant success in wireless communications systems due to their denoising capabilities. The broadcast nature of wireless signals makes them susceptible not only to Gaussian noise, but also to unaware interference. This raises the question of whether DMs can effectively mitigate interference in wireless semantic communication systems. In this paper, we model the interference cancellation problem as a maximum a posteriori (MAP) problem over the joint posterior probability of the signal and interference, and theoretically prove that the solution provides excellent estimates for the signal and interference. To solve this problem, we develop an interference cancellation diffusion model (ICDM), which decomposes the joint posterior into independent prior probabilities of the signal and interference, along with the channel transition probablity. The log-gradients of these distributions at each time step are learned separately by DMs and accurately estimated through deriving. ICDM further integrates these gradients with advanced numerical iteration method, achieving accurate and rapid interference cancellation. Extensive experiments demonstrate that ICDM significantly reduces the mean square error (MSE) and enhances perceptual quality compared to schemes without ICDM. For example, on the CelebA dataset under the Rayleigh fading channel with a signal-to-noise ratio (SNR) of $20$ dB and signal to interference plus noise ratio (SINR) of 0 dB, ICDM reduces the MSE by 4.54 dB and improves the learned perceptual image patch similarity (LPIPS) by 2.47 dB.

cs.IT↗

arXiv2025

Giant elastoresistance in magic-angle twisted bilayer graphene

Strongly correlated and topological phases in moiré materials are exquisitely sensitive to lattice geometry at both atomic and superlattice length scales. Twist angle, pressure, and strain directly modify the lattice, and thus act as highly effective tuning parameters. Here we examine electrical transport in twisted bilayer graphene subjected to continuous uniaxial strain. Near the magic angle ($\approx 1.1^{\circ}$), devices exhibit a pronounced elastoresistance that depends on band filling and temperature, with a gauge factor more than two orders of magnitude larger than that of conventional metals. In selected doping regimes the elastoresistance exhibits a Curie-Weiss-like temperature divergence. We discuss possible microscopic origins, including nematic fluctuations and enhanced electronic entropy from fluctuating isospin moments. Our work establishes uniaxial strain as a versatile probe of correlated physics in a moiré material.

cond-mat.mes-hall↗

arXiv2025

Efficient Gaussian Process Classification-based Physical-Layer Authentication with Configurable Fingerprints for 6G-Enabled IoT

The future 6G-enabled IoT will facilitate seamless global connectivity among ubiquitous wireless devices, but this advancement also introduces heightened security risks such as spoofing attacks. Physical-Layer Authentication (PLA) has emerged as a promising, inherently secure, and energy-efficient technique for authenticating IoT terminals. Nonetheless, the direct application of state-of-the-art PLA schemes to 6G-enabled IoT encounters two major hurdles: inaccurate channel fingerprints and the inefficient utilization of prior fingerprint information. To tackle these challenges, we leverage Reconfigurable Intelligent Surfaces (RISs) to enhance fingerprint accuracy. Additionally, we integrate active learning and Gaussian Processes (GPs) to propose an Efficient Gaussian Process Classification (EGPC)-based PLA scheme, aiming for reliable and lightweight authentication. Following Bayes' theorem, we model configurable fingerprints using GPs and employ the expectation propagation method to identify unknown fingerprints. Given the difficulty of obtaining sufficient labeled fingerprint samples to train PLA models, we propose three fingerprint selection algorithms. These algorithms select unlabeled fingerprints and query their identities using upper-layer authentication mechanisms. Among these methods, the optimal algorithm reduces the number of training fingerprints needed through importance sampling and eliminates the requirement for PLA model retraining through joint distribution calculation. Simulations results reveal that, in comparison with non-RIS-based approaches, the RIS-aided PLA framework decreases the authentication error rate by 98.69%. In addition, our designed fingerprint selection algorithms achieve a reduction in the authentication error rate of up to 86.93% compared to baseline active learning schemes.

eess.SP↗

arXiv2025

Optical control of orbital magnetism in magic angle twisted bilayer graphene

Flat bands in graphene-based moiré structures host a wide range of emerging strongly correlated and topological phenomena. Optically probing and controlling them can reveal important information such as symmetry and dynamics, but have so far been challenging due to the small energy gap compared to optical wavelengths. Here, we report near infrared optical control of orbital magnetism and associated anomalous Hall effects (AHE) in a magic angle twisted bilayer graphene (MATBG) on monolayer WSe$_2$ device. We show that the properties of the AHE, such as hysteresis and amplitude, can be controlled by light near integer moiré fillings, where spontaneous ferromagnetism exists. By modulating the light helicity, we observe periodic modulation of the transverse resistance in a wide range of fillings, indicating light induced orbital magnetization through a large inverse Faraday effect. At the transition between metallic and AHE regimes, we also reveal large and random switching of the Hall resistivity, which are attributed to optical control of percolating cluster of magnetic domains. Our results open the door to optical manipulation of correlation and topology in MATBG and related structures.

cond-mat.str-el↗

arXiv2025

A Survey of Secure Semantic Communications

Semantic communication (SemCom) is regarded as a promising and revolutionary technology in 6G, aiming to transcend the constraints of ``Shannon's trap" by filtering out redundant information and extracting the core of effective data. Compared to traditional communication paradigms, SemCom offers several notable advantages, such as reducing the burden on data transmission, enhancing network management efficiency, and optimizing resource allocation. Numerous researchers have extensively explored SemCom from various perspectives, including network architecture, theoretical analysis, potential technologies, and future applications. However, as SemCom continues to evolve, a multitude of security and privacy concerns have arisen, posing threats to the confidentiality, integrity, and availability of SemCom systems. This paper presents a comprehensive survey of the technologies that can be utilized to secure SemCom. Firstly, we elaborate on the entire life cycle of SemCom, which includes the model training, model transfer, and semantic information transmission phases. Then, we identify the security and privacy issues that emerge during these three stages. Furthermore, we summarize the techniques available to mitigate these security and privacy threats, including data cleaning, robust learning, defensive strategies against backdoor attacks, adversarial training, differential privacy, cryptography, blockchain technology, model compression, and physical-layer security. Lastly, this paper outlines future research directions to guide researchers in related fields.

cs.CR↗

arXiv2025

Engineering robust strain transmission in van der Waals heterostructure devices

Atomically thin van der Waals materials provide a highly tunable platform for exploring emergent quantum phenomena in solid state systems. Due to their remarkable mechanical strength, one enticing tuning knob is strain. However, the weak strain transfer of graphite and hBN, which are standard components of high-qualityvdW devices, poses fundamental challenges for high-strain experiments. Here, we investigate strain transmission in less-explored orthorhombic crystals and find robust transmission up to several percent at cryogenic temperatures. We further show that strain can be efficiently transferred through these crystals to other 2D materials in traditional heterostructure devices. Using this capability, we demonstrate in-situ strain and gate control of the optical properties of monolayer WS2 utilizing the high-\k{appa} dielectric insulator Bi2SeO5 as a substrate. These results enable the exploration of combined cryo-strain and gate tuning in a variety of layered systems such as moiré heterostructures, air-sensitive 2D magnets and superconductors, and any gated 2D device.

cond-mat.mes-hall↗

arXiv2025

Observation of High-Temperature Dissipationless Fractional Chern Insulator

The fractional quantum anomalous Hall effect has recently been experimentally observed in zero-field fractional Chern insulators (FCI). However, an outstanding challenge is the presence of a substantial longitudinal resistance $R_{xx}$ (a few k$Ω$), even though the anomalous Hall resistance $R_{xy}$ is quantized. This dissipative behavior is likely linked to imperfect sample quality. Here, we report transport measurements of a drastically improved twisted $\text{MoTe}_2$ bilayer device, which exhibits quantized $R_{xy}$ and vanishing $R_{xx}$ for the $-2/3$ state, marking a dissipationless FCI. Contrary to fractional quantum Hall states where the energy gap increases with magnetic field, we find that the thermal activation gap of the observed FCI states decreases rapidly as the magnetic field rises from zero, then plateaus above a few teslas. This observation is attributed to the interplay between spin and charge gaps. Due to the spontaneous ferromagnetism, the spin gap dominates at low field, while the charge gap becomes appreciable once the magnetic field freezes spin fluctuations. For the $-2/3$ state, we estimate the spin and FCI gap of about 55 and 20 K, respectively. Our results provide insights into the energy scale of FCI and offer a pathway for quantum engineering of exotic correlated topological states.

cond-mat.mes-hall↗

arXiv2025

Intelligent Joint Security and Delay Determinacy Performance Guarantee Strategy in RIS-Assisted IIoT Communication Systems

With the advancement of the Industrial Internet of Things (IIoT), IIoT services now exhibit diverse Quality of Service (QoS) requirements in terms of delay, determinacy, and security, which pose significant challenges for alignment with existing network resources. Reconfigurable Intelligent Surface (RIS), a key enabling technology for IIoT, not only optimizes signal propagation and enhances network performance but also ensures secure communication and deterministic delays to mitigate threats such as data leakage and eavesdropping. In this paper, we conduct a deterministic delay analysis under a specified decoding error rate for RIS-assisted IIoT communication systems using Stochastic Network Calculus (SNC). We propose an on-demand joint strategy to maximize delay determinacy while guaranteeing secure transmission performance. This is achieved by jointly optimizing the transmit power, channel blocklength (CBL) at the user end, and the phase shift matrix at the RIS. Furthermore, we introduce a State Interdependence-Driven Parameterized Deep Q-Network (SID-PDQN) algorithm to intelligently enforce on-demand performance guarantees. Simulation results demonstrate that the proposed SID-PDQN algorithm significantly enhances network performance compared to baseline methods such as DQN, Dueling-DQN, and DDPG.

eess.SP↗

arXiv2025

Magnetoelectric Control of Helical Light Emission in a Moiré Chern Magnet

Magnetoelectric effects and their coupling to light helicity are important for both fundamental science and applications in sensing, communication, and data storage. Traditional approaches require complex device architectures, involving separate spin-injection, ferromagnetic, and optically active layers. Recently, the emergence of 2D semiconductor moiré superlattices with flat Chern bands and strong light-matter interactions has established a simple yet powerful platform for exploring the coupling between photon, electron, and spin degrees of freedom. Here, we report efficient current control of spontaneous ferromagnetism and associated helicity of light emission in moiré MoTe2 bilayer - a system which hosts a rich variety of topological phases, including newly discovered zero-field fractional Chern insulators. We show that the current control is effective over a wide range of doping of the first moiré Chern band, implying the uniformity of the Berry curvature distribution over the flat band. By setting the system into the anomalous Hall metal phase, a current as small as 10nA is sufficient to switch the magnetic order, a substantial improvement over both conventional spin torque architectures and other moiré systems. The realized current control of ferromagnetism leads to continuous tuning of trion photoluminescence helicity from left to right circular via spin/valley Hall torque at zero magnetic field. Our results pave the way for topological opto-spintronics based on semiconductors with synthetic flat Chern bands.

cond-mat.mes-hall↗

arXiv2025

Continual Learning-Aided Super-Resolution Scheme for Channel Reconstruction and Generalization in OFDM Systems

Channel reconstruction and generalization capability are of equal importance for developing channel estimation schemes within deep learning (DL) framework. In this paper, we exploit a novel DL-based scheme for efficient OFDM channel estimation where the neural networks for channel reconstruction and generalization are respectively designed. For the former, we propose a dual-attention-aided super-resolution neural network (DA-SRNN) to map the channels at pilot positions to the whole time-frequency channels. Specifically, the channel-spatial attention mechanism is first introduced to sequentially infer attention maps along two separate dimensions corresponding to two types of underlying channel correlations, and then the lightweight SR module is developed for efficient channel reconstruction. For the latter, we introduce continual learning (CL)-aided training strategies to make the neural network adapt to different channel distributions. Specifically, the elastic weight consolidation (EWC) is introduced as the regularization term in regard to loss function of channel reconstruction, which can constrain the direction and space of updating the important weights of neural networks among different channel distributions. Meanwhile, the corresponding training process is provided in detail. By evaluating under 3rd Generation Partnership Project (3GPP) channel models, numerical results verify the superiority of the proposed channel estimation scheme with significantly improved channel reconstruction and generalization performance over counterparts.

cs.LG↗

arXiv2025

Hidden States and Dynamics of Fractional Fillings in tMoTe2 Moiré Superlattices

The fractional quantum anomalous Hall (FQAH) effect was recently discovered in twisted MoTe2 bilayers (tMoTe2). Experiments to date have revealed Chern insulators from hole doping at v = -1, -2/3, -3/5, and -4/7 (per moiré unit cell). In parallel, theories predict that, between v = -1 and -3, there exist exotic quantum phases, such as the coveted fractional topological insulators (FTI), fractional quantum spin Hall (FQSH) states, and non-abelian fractional states. Here we employ transient optical spectroscopy on tMoTe2 to reveal nearly 20 hidden states at fractional fillings that are absent in static optical sensing or transport measurements. A pump pulse selectively excites charge across the correlated or pseudo gaps, leading to the disordering (melting) of correlated states. A probe pulse detects the subsequent melting and recovery dynamics via exciton and trion sensing. Besides the known states, we observe additional fractional fillings between v = 0 and -1 and a large number of states on the electron doping side (v > 0). Most importantly, we observe new states at fractional fillings of the Chern bands at v = -4/3, -3/2, -5/3, -7/3, -5/2, and -8/3. These states are potential candidates for the predicted exotic topological phases. Moreover, we show that melting of correlated states occurs on two distinct time scales, 2-4 ps and 180-270 ps, attributed to electronic and phonon mechanisms, respectively. We discuss the differing dynamics of the electron and hole doped states from the distinct moiré conduction and valence bands.

cond-mat.str-el↗

arXiv2025

Efficient Semantic-aware Encryption for Secure Communications in Intelligent Connected Vehicles

Semantic communication (SemCom) significantly improves inter-vehicle interactions in intelligent connected vehicles (ICVs) within limited wireless spectrum. However, the open nature of wireless communications introduces eavesdropping risks. To mitigate this, we propose the Efficient Semantic-aware Encryption (ESAE) mechanism, integrating cryptography into SemCom to secure semantic transmission without complex key management. ESAE leverages semantic reciprocity between source and reconstructed information from past communications to independently generate session keys at both ends, reducing key transmission costs and associated security risks. Additionally, ESAE introduces a semantic-aware key pre-processing method (SA-KP) using the YOLO-v10 model to extract consistent semantics from bit-level diverse yet semantically identical content, ensuring key consistency. Experimental results validate ESAE's effectiveness and feasibility under various wireless conditions, with key performance factors discussed.

cs.CR↗

arXiv2025

Visualizing Field-free Deterministic Magnetic Switching of all-van der Waals Spin-Orbit Torque System Using Spin Ensembles in Hexagonal Boron Nitride

Recently, optically active spin defects embedded in van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science and quantum physics. Taking advantage of excellent solid-state integrability, this new class of spin defects can be arranged in controllable nanoscale proximity of target materials in vdW heterostructures, showing great promise for improving spatial resolution and field sensitivity of current sensing technologies. Building on this state-of-the-art measurement platform, here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching of room-temperature two-dimensional magnet Fe3GaTe2 in an all-vdW spin-orbit torque (SOT) system. By visualizing SOT-driven variations of nanoscale Fe3GaTe2 magnetic stray field profile under different conditions, we have revealed how the observed magnetic switching evolves from deterministic to indeterministic behavior due to the interplay between out-of-plane spins, in-plane spins and Joule heating. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights on material design, testing, and evaluation of next-generation vdW spintronic devices.

cond-mat.mes-hall↗

arXiv2024

Ferromagnetism and Topology of the Higher Flat Band in a Fractional Chern Insulator

The recent observation of the fractional quantum anomalous Hall effect in moiré fractional Chern insulators provides an opportunity to investigate zero magnetic field anyons. To potentially realize non-Abelian anyons, one approach is to engineer higher flat Chern bands that mimic higher Landau levels. Here, we investigate the interaction, topology, and ferromagnetism of the second moiré miniband in twisted MoTe2 bilayers. At half filling of the second miniband, we observe spontaneous ferromagnetism and an incipient Chern insulator state. The Chern numbers of the top two moiré flat bands exhibit opposite signs for twist angles above 3.1°, but share the same sign near 2.6°, consistent with theoretical predictions. In the 2.6° device, increasing magnetic field induces a topological phase transition via band crossing between opposite valleys, resulting in an emergent state with Chern number C = -2. Additionally, an insulating state at half filling of the second valley-polarized band suggests a charge-ordered state is favored over the fractional Chern insulator state. These findings lay a foundation for understanding the higher flat Chern bands, crucial for the discovery of non-Abelian fractional Chern insulators.

cond-mat.mes-hall↗

arXiv2024

A Survey of Machine Learning-based Physical-Layer Authentication in Wireless Communications

To ensure secure and reliable communication in wireless systems, authenticating the identities of numerous nodes is imperative. Traditional cryptography-based authentication methods suffer from issues such as low compatibility, reliability, and high complexity. Physical-Layer Authentication (PLA) is emerging as a promising complement due to its exploitation of unique properties in wireless environments. Recently, Machine Learning (ML)-based PLA has gained attention for its intelligence, adaptability, universality, and scalability compared to non-ML approaches. However, a comprehensive overview of state-of-the-art ML-based PLA and its foundational aspects is lacking. This paper presents a comprehensive survey of characteristics and technologies that can be used in the ML-based PLA. We categorize existing ML-based PLA schemes into two main types: multi-device identification and attack detection schemes. In deep learning-based multi-device identification schemes, Deep Neural Networks are employed to train models, avoiding complex processing and expert feature transformation. Deep learning-based multi-device identification schemes are further subdivided, with schemes based on Convolutional Neural Networks being extensively researched. In ML-based attack detection schemes, receivers utilize intelligent ML techniques to set detection thresholds automatically, eliminating the need for manual calculation or knowledge of channel models. ML-based attack detection schemes are categorized into three sub-types: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Additionally, we summarize open-source datasets used for PLA, encompassing Radio Frequency fingerprints and channel fingerprints. Finally, this paper outlines future research directions to guide researchers in related fields.

cs.CR↗