arXiv subjects

Xiaodong Xu

Publications and source records attributed to Xiaodong Xu.

At least 145 records · Page 8Linked to original sources

arXiv2024

Semantic Similarity Score for Measuring Visual Similarity at Semantic Level

Semantic communication, as a revolutionary communication architecture, is considered a promising novel communication paradigm. Unlike traditional symbol-based error-free communication systems, semantic-based visual communication systems extract, compress, transmit, and reconstruct images at the semantic level. However, widely used image similarity evaluation metrics, whether pixel-based MSE or PSNR or structure-based MS-SSIM, struggle to accurately measure the loss of semantic-level information of the source during system transmission. This presents challenges in evaluating the performance of visual semantic communication systems, especially when comparing them with traditional communication systems. To address this, we propose a semantic evaluation metric -- SeSS (Semantic Similarity Score), based on Scene Graph Generation and graph matching, which shifts the similarity scores between images into semantic-level graph matching scores. Meanwhile, semantic similarity scores for tens of thousands of image pairs are manually annotated to fine-tune the hyperparameters in the graph matching algorithm, aligning the metric more closely with human semantic perception. The performance of the SeSS is tested on different datasets, including (1)images transmitted by traditional and semantic communication systems at different compression rates, (2)images transmitted by traditional and semantic communication systems at different signal-to-noise ratios, (3)images generated by large-scale model with different noise levels introduced, and (4)cases of images subjected to certain special transformations. The experiments demonstrate the effectiveness of SeSS, indicating that the metric can measure the semantic-level differences in semantic-level information of images and can be used for evaluation in visual semantic communication systems.

cs.CV↗

arXiv2024

When Could Abelian Fractional Topological Insulators Exist in Twisted MoTe$_2$ (and Other Systems)

Using comprehensive exact diagonalization calculations on $θ\approx 3.7 ^{\circ}$ twisted bilayer MoTe$_2$ ($t$MoTe$_2$), as well as idealized Landau level models also relevant for lower $θ$, we extract general principles for engineering fractional topological insulators (FTIs) in realistic situations. First, in a Landau level setup at $ν=1/3+1/3$, we investigate what features of the interaction destroy an FTI. For both pseudopotential interactions and realistic screened Coulomb interactions, we find that sufficient suppression of the short-range repulsion is needed for stabilizing an FTI. We then study $θ\approx 3.7 ^{\circ}$ $t$MoTe$_2$ with realistic band-mixing and anisotropic non-local dielectric screening. Our finite-size calculations only find an FTI phase at $ν=-4/3$ in the presence of a significant additional short-range attraction $g$ that acts to counter the Coulomb repulsion at short distances. We discuss how further finite-size drifts, dielectric engineering, Landau level character, and band-mixing effects may reduce the required value of $g$ closer towards the experimentally relevant conditions of $t$MoTe$_2$. Projective calculations into the $n=1$ Landau level, which resembles the second valence band of $θ\simeq 2.1^\circ$ $t$MoTe$_2$, do not yield FTIs for any $g$, suggesting that FTIs at low-angle $t$MoTe$_2$ for $ν=-8/3$ and $-10/3$ may be unlikely. While our study highlights the challenges, at least for the fillings considered, to obtaining an FTI with transport plateaus, even in large-angle $t$MoTe$_2$ where fractional Chern insulators are experimentally established, we also provide potential sample-engineering routes to improve the stability of FTI phases.

cond-mat.str-el↗

arXiv2024

Absence of $E_{2g}$ nematic instability and dominant $A_{1g}$ response in the kagome metal CsV$_3$Sb$_5$

Ever since the discovery of the charge density wave (CDW) transition in the kagome metal CsV$_3$Sb$_5$, the nature of its symmetry breaking is under intense debate. While evidence suggests that the rotational symmetry is already broken at the CDW transition temperature ($T_{\rm CDW}$), an additional electronic nematic instability well below $T_{\rm CDW}$ has been reported based on the diverging elastoresistivity coefficient in the anisotropic channel ($m_{E_{2g}}$). Verifying the existence of a nematic transition below $T_{\rm CDW}$ is not only critical for establishing the correct description of the CDW order parameter, but also important for understanding low-temperature superconductivity. Here, we report elastoresistivity measurements of CsV$_3$Sb$_5$ using three different techniques probing both isotropic and anisotropic symmetry channels. Contrary to previous reports, we find the anisotropic elastoresistivity coefficient $m_{E_{2g}}$ is temperature-independent, except for a step jump at $T_{\rm CDW}$. The absence of nematic fluctuations is further substantiated by measurements of the elastocaloric effect, which show no enhancement associated with nematic susceptibility. On the other hand, the symmetric elastoresistivity coefficient $m_{A_{1g}}$ increases below $T_{\rm CDW}$, reaching a peak value of 90 at $T^* = 20$ K. Our results strongly indicate that the phase transition at $T^*$ is not nematic in nature and the previously reported diverging elastoresistivity is due to the contamination from the $A_{1g}$ channel.

cond-mat.supr-con↗

arXiv2024

MnRhBi3: A Cleavable Antiferromagnetic Metal

Cleavable metallic antiferromagnets may be of use for low-dissipation spintronic devices; however, few are currently known. Here we present orthorhombic MnRhBi3 as one such compound and present a thorough study of its physical properties. Exfoliation is demonstrated experimentally, and the cleavage energy and electronic structure are examined by density functional theory calculations. It is concluded that MnRhBi3 is a van der Waals layered material that cleaves easily between neighboring Bi layers, and that the Bi atoms have lone pairs extending into the van der Waals gaps. A series of four phase transitions are observed below room temperature, and neutron diffraction shows that at least two of the transitions involve the formation of antiferromagnetic order. Anomalous thermal expansion points to a crystallographic phase transition and/or strong magnetoelastic coupling. This work reveals a complex phase evolution in MnRhBi3 and establishes this cleavable antiferromagnetic metal as an interesting material for studying the interplay of structure, magnetism, and transport in the bulk and ultrathin limits as well as the role of lone pair electrons in interface chemistry and proximity effects in van der Waals heterostructures.

cond-mat.mtrl-sci↗

arXiv2024

Plasmonic polarization sensing of electrostatic superlattice potentials

Plasmon polaritons are formed by coupling light with delocalized electrons. The half-light and half-matter nature of plasmon polaritons endows them with unparalleled tunability via a range of parameters, such as dielectric environments and carrier density. Therefore, plasmon polaritons are expected to be tuned when in proximity to polar materials since the carrier density is tuned by an electrostatic potential; conversely, the plasmon polariton response might enable the sensing of polarization. Here, we use infrared nano-imaging and nano-photocurrent measurements to investigate heterostructures composed of graphene and twisted hexagonal boron nitride (t-BN), with alternating polarization in a triangular network of moiré stacking domains. We observe that the carrier density and the corresponding plasmonic response of graphene are modulated by polar domains in t-BN. In addition, we demonstrate that the nanometer-wide domain walls of graphene moirés superlattices, created by the polar domains of t-BN, provide momenta to assist the plasmonic excitations. Furthermore, our studies establish that the plasmon of graphene could function as a delicate sensor for polarization textures. The evolution of polarization textures in t-BN under uniform electric fields is tomographically examined via plasmonic imaging. Strikingly, no noticeable polarization switching is observed under applied electric fields up to 0.23 V/nm, at variance with transport reports. Our nano-images unambiguously reveal that t-BN with triangular domains acts like a ferrielectric, rather than ferroelectric claimed by many previous studies.

cond-mat.mes-hall↗

arXiv2024

Rate Splitting Multiple Access-Enabled Adaptive Panoramic Video Semantic Transmission

In this paper, we propose an adaptive panoramic video semantic transmission (APVST) framework enabled by rate splitting multiple access (RSMA). The APVST framework consists of a semantic transmitter and receiver, utilizing a deep joint source-channel coding structure to adaptively extract and encode semantic features from panoramic frames. To achieve higher spectral efficiency and conserve bandwidth, APVST employs an entropy model and a dimension-adaptive module to control the transmission rate. Additionally, we take weighted-to-spherically-uniform peak signal-to-noise ratio (WS-PSNR) and weighted-to-spherically-uniform structural similarity (WS-SSIM) as distortion evaluation metrics for panoramic videos and design a weighted self-attention module for APVST. This module integrates weights and feature maps to enhance the quality of the immersive experience. Considering the overlap in the field of view when users watch panoramic videos, we further utilize RSMA to split the required panoramic video semantic streams into common and private messages for transmission. We propose an RSMA-enabled semantic stream transmission scheme and formulate a joint problem of latency and immersive experience quality by optimizing the allocation ratios of power, common rate, and channel bandwidth, aiming to maximize the quality of service (QoS) scores for users. To address the above problem, we propose a deep reinforcement learning algorithm based on proximal policy optimization (PPO) with high efficiency to handle dynamically changing environments. Simulation results demonstrate that our proposed APVST framework saves up to 20% and 50% of channel bandwidth compared to other semantic and traditional video transmission schemes, respectively. Moreover, our study confirms the efficiency of RSMA in panoramic video transmission, achieving performance gains of 13% and 20% compared to NOMA and OFDMA.

eess.IV↗

arXiv2024

Time-Domain Signatures of Distinct Correlated Insulators in a Moiré Superlattice

Among expanding discoveries of quantum phases in moiré superlattices, correlated insulators stand out as both the most stable and most commonly observed. Despite the central importance of these states in moiré physics, little is known about their underlying nature. Here, we use pump-probe spectroscopy to show distinct time-domain signatures of correlated insulators at fillings of one (v = -1) and two (v = -2) holes per moiré unit cell in the angle-aligned WSe2/WS2 system. Following photo-doping, we find that the disordering time of the v = -1 state is independent of excitation density (n_ex), as expected from the characteristic phonon response time associated with a polaronic state. In contrast, the disordering time of the v = -2 state scales with (n_ex)^-0.5, in agreement with plasmonic screening from free holons and doublons. These states display disparate reordering behavior dominated either by first order (v = -1) or second order (v = -2) recombination, suggesting the presence of Hubbard excitons and free carrier-like holons/doublons, respectively. Our work delineates the roles of electron-phonon (e-ph) versus electron-electron (e-e) interactions in correlated insulators on the moiré landscape and establishes non-equilibrium responses as mechanistic signatures for distinguishing and discovering quantum phases.

cond-mat.str-el↗

arXiv2024

Federated Contrastive Learning for Personalized Semantic Communication

In this letter, we design a federated contrastive learning (FedCL) framework aimed at supporting personalized semantic communication. Our FedCL enables collaborative training of local semantic encoders across multiple clients and a global semantic decoder owned by the base station. This framework supports heterogeneous semantic encoders since it does not require client-side model aggregation. Furthermore, to tackle the semantic imbalance issue arising from heterogeneous datasets across distributed clients, we employ contrastive learning to train a semantic centroid generator (SCG). This generator obtains representative global semantic centroids that exhibit intra-semantic compactness and inter-semantic separability. Consequently, it provides superior supervision for learning discriminative local semantic features. Additionally, we conduct theoretical analysis to quantify the convergence performance of FedCL. Simulation results verify the superiority of the proposed FedCL framework compared to other distributed learning benchmarks in terms of task performance and robustness under different numbers of clients and channel conditions, especially in low signal-to-noise ratio and highly heterogeneous data scenarios.

eess.SP↗

arXiv2024

Visualizing the microscopic origins of topology in twisted molybdenum ditelluride

In moiré materials with flat electronic bands and suitable quantum geometry, strong correlations can give rise to novel topological states of matter. The nontrivial band topology of twisted molybdenum ditelluride (tMoTe$_2$) -- responsible for its fractional quantum anomalous Hall (FQAH) states -- is predicted to arise from a layer-pseudospin skyrmion lattice. Tracing the layer polarization of wavefunctions within the moiré unit cell can thus offer crucial insights into the band topology. Here, we use scanning tunneling microscopy and spectroscopy (STM/S) to probe the layer-pseudospin skyrmion textures of tMoTe$_2$. We do this by simultaneously visualizing the moiré lattice structure and the spatial localization of its electronic states. We find that the wavefunctions associated with the topological flat bands exhibit a spatially-dependent layer polarization within the moiré unit cell. This is in excellent agreement with our theoretical modeling, thereby revealing a direct microscopic connection between the structural properties of tMoTe$_2$ and its band topology. Our work enables new pathways for engineering FQAH states with strain, as well as future STM studies of the intertwined correlated and topological states arising in gate-tunable devices.

cond-mat.mes-hall↗

arXiv2024

Continuously tunable uniaxial strain control of van der Waals heterostructure devices

Uniaxial strain has been widely used as a powerful tool for investigating and controlling the properties of quantum materials. However, existing strain techniques have so far mostly been limited to use with bulk crystals. Although recent progress has been made in extending the application of strain to two-dimensional van der Waals (vdW) heterostructures, these techniques have been limited to optical characterization and extremely simple electrical device geometries. Here, we report a piezoelectric-based \textit{in situ} uniaxial strain technique enabling simultaneous electrical transport and optical spectroscopy characterization of dual-gated vdW heterostructure devices. Critically, our technique remains compatible with vdW heterostructure devices of arbitrary complexity fabricated on conventional silicon/silicon dioxide wafer substrates. We demonstrate a large and continuously tunable strain of up to $-0.15\%$ at millikelvin temperatures, with larger strain values also likely achievable. We quantify the strain transmission from the silicon wafer to the vdW heterostructure, and further demonstrate the ability of strain to modify the electronic properties of twisted bilayer graphene. Our technique provides a highly versatile new method for exploring the effect of uniaxial strain on both the electrical and optical properties of vdW heterostructures, and can be easily extended to include additional characterization techniques.

physics.ins-det↗

arXiv2024

Direct magnetic imaging of fractional Chern insulators in twisted MoTe$_2$ with a superconducting sensor

In the absence of time reversal symmetry, orbital magnetization provides a sensitive probe of topology and interactions, with particularly rich phenomenology in Chern insulators where topological edge states carry large equilibrium currents. Here, we use a nanoscale superconducting sensor to map the magnetic fringe fields in twisted bilayers of MoTe$_2$, where transport and optical sensing experiments have revealed the formation of fractional Chern insulator (FCI) states at zero magnetic field. At a temperature of 1.6K, we observe oscillations in the local magnetic field associated with fillings $ν=-1,-2/3,-3/5,-4/7$ and $-5/9$ of the first moiré hole band, consistent with the formation of FCIs at these fillings. By quantitatively reconstructing the magnetization, we determine the local thermodynamic gaps of the most robust FCI state at $ν=-2/3$, finding $^{-2/3}Δ$ as large as 7 meV. Spatial mapping of the charge density- and displacement field-tuned magnetic phase diagram further allows us to characterize sample disorder, which we find to be dominated by both inhomogeneity in the effective unit cell area as well as inhomogeneity in the band edge offset and bound dipole moment. Our results highlight both the challenges posed by structural disorder in the study of twisted homobilayer moiré systems and the opportunities afforded by the remarkably robust nature of the underlying correlated topological states.

cond-mat.mes-hall↗

arXiv2024

End-to-End Generative Semantic Communication Powered by Shared Semantic Knowledge Base

Semantic communication has drawn substantial attention as a promising paradigm to achieve effective and intelligent communications. However, efficient image semantic communication encounters challenges with a lower testing compression ratio (CR) compared to the training phase. To tackle this issue, we propose an innovative semantic knowledge base (SKB)-enabled generative semantic communication system for image classification and image generation tasks. Specifically, a lightweight SKB, comprising class-level information, is exploited to guide the semantic communication process, which enables us to transmit only the relevant indices. This approach promotes the completion of the image classification task at the source end and significantly reduces the transmission load. Meanwhile, the category-level knowledge in the SKB facilitates the image generation task by allowing controllable generation, making it possible to generate favorable images in resource-constrained scenarios. Additionally, semantic accuracy is introduced as a new metric to validate the performance of semantic transmission powered by the SKB. Evaluation results indicate that the proposed method outperforms the benchmarks and achieves superior performance with minimal transmission overhead, especially in the low SNR regime.

cs.IT↗

arXiv2024

Topological flat bands in a family of multilayer graphene moiré lattices

Moiré materials host a wealth of intertwined correlated and topological states of matter, all arising from flat electronic bands with nontrivial quantum geometry. A prominent example is the family of alternating-twist magic-angle graphene stacks, which exhibit symmetry-broken states at rational fillings of the moiré band and superconductivity close to half filling. Here, we introduce a second family of twisted graphene multilayers made up of twisted sheets of $M$- and $N$-layer Bernal-stacked graphene flakes. Calculations indicate that applying an electric displacement field isolates a flat and topological moiré conduction band that is primarily localized to a single graphene sheet below the moiré interface. Phenomenologically, the result is a striking similarity in the hierarchies of symmetry-broken phases across this family of twisted graphene multilayers. Our results show that this family of structures offers promising new opportunities for the discovery of exotic new correlated and topological phenomena, enabled by using the layer number to fine tune the flat moiré band and its screening environment.

cond-mat.mes-hall↗

arXiv2024

MambaJSCC: Deep Joint Source-Channel Coding with Visual State Space Model

Lightweight and efficient deep joint source-channel coding (JSCC) is a key technology for semantic communications. In this paper, we design a novel JSCC scheme named MambaJSCC, which utilizes a visual state space model with channel adaptation (VSSM-CA) block as its backbone for transmitting images over wireless channels. The VSSM-CA block utilizes VSSM to integrate two-dimensional images with the state space, enabling feature extraction and encoding processes to operate with linear complexity. It also incorporates channel state information (CSI) via a newly proposed CSI embedding method. This method deploys a shared CSI encoding module within both the encoder and decoder to encode and inject the CSI into each VSSM-CA block, improving the adaptability of a single model to varying channel conditions. Experimental results show that MambaJSCC not only outperforms Swin Transformer based JSCC (SwinJSCC) but also significantly reduces parameter size, computational overhead, and inference delay (ID). For example, with employing an equal number of the VSSM-CA blocks and the Swin Transformer blocks, MambaJSCC achieves a 0.48 dB gain in peak-signal-to-noise ratio (PSNR) over SwinJSCC while requiring only 53.3% multiply-accumulate operations, 53.8% of the parameters, and 44.9% of ID.

cs.IT↗

arXiv2024

WDMoE: Wireless Distributed Large Language Models with Mixture of Experts

Large Language Models (LLMs) have achieved significant success in various natural language processing tasks, but how wireless communications can support LLMs has not been extensively studied. In this paper, we propose a wireless distributed LLMs paradigm based on Mixture of Experts (MoE), named WDMoE, deploying LLMs collaboratively across edge servers of base station (BS) and mobile devices in the wireless communications system. Specifically, we decompose the MoE layer in LLMs by deploying the gating network and the preceding neural network layer at BS, while distributing the expert networks across the devices. This arrangement leverages the parallel capabilities of expert networks on distributed devices. Moreover, to overcome the instability of wireless communications, we design an expert selection policy by taking into account both the performance of the model and the end-to-end latency, which includes both transmission delay and inference delay. Evaluations conducted across various LLMs and multiple datasets demonstrate that WDMoE not only outperforms existing models, such as Llama 2 with 70 billion parameters, but also significantly reduces end-to-end latency.

cs.IT↗

arXiv2024

sDAC -- Semantic Digital Analog Converter for Semantic Communications

In this paper, we propose a novel semantic digital analog converter (sDAC) for the compatibility of semantic communications and digital communications. Most of the current semantic communication systems are based on the analog modulations, ignoring their incorporation with digital communication systems, which are more common in practice. In fact, quantization methods in traditional communication systems are not appropriate for use in the era of semantic communication as these methods do not consider the semantic information inside symbols. In this case, any bit flip caused by channel noise can lead to a great performance drop. To address this challenge, sDAC is proposed. It is a simple yet efficient and generative module used to realize digital and analog bi-directional conversion. On the transmitter side, continuous values from the encoder are converted to binary bits and then can be modulated by any existing methods. After transmitting through the noisy channel, these bits get demodulated by paired methods and converted back to continuous values for further semantic decoding. The whole progress does not depend on any specific semantic model, modulation methods, or channel conditions. In the experiment section, the performance of sDAC is tested across different semantic models, semantic tasks, modulation methods, channel conditions and quantization orders. Test results show that the proposed sDAC has great generative properties and channel robustness.

cs.IT↗

arXiv2024

A Specific Task-oriented Semantic Image Communication System for substation patrol inspection

Intelligent inspection robots are widely used in substation patrol inspection, which can help check potential safety hazards by patrolling the substation and sending back scene images. However, when patrolling some marginal areas with weak signal, the scene images cannot be sucessfully transmissted to be used for hidden danger elimination, which greatly reduces the quality of robots'daily work. To solve such problem, a Specific Task-oriented Semantic Communication System for Imag-STSCI is designed, which involves the semantic features extraction, transmission, restoration and enhancement to get clearer images sent by intelligent robots under weak signals. Inspired by that only some specific details of the image are needed in such substation patrol inspection task, we proposed a new paradigm of semantic enhancement in such specific task to ensure the clarity of key semantic information when facing a lower bit rate or a low signal-to-noise ratio situation. Across the reality-based simulation, experiments show our STSCI can generally surpass traditional image-compression-based and channel-codingbased or other semantic communication system in the substation patrol inspection task with a lower bit rate even under a low signal-to-noise ratio situation.

cs.CV↗

arXiv2024

Local probe of bulk and edge states in a fractional Chern insulator

Fractional quantum Hall effect (FQHE) is a prime example of topological quantum many-body phenomena, arising from the interplay between strong electron correlation, topological order, and time reversal symmetry breaking. Recently, a lattice analog of FQHE at zero magnetic field has been observed, confirming the existence of a zero-field fractional Chern insulator (FCI). Despite this, the bulk-edge correspondence -- a hallmark of FCI featuring an insulating bulk with conductive edges -- has not been directly observed. In fact, this correspondence has not been visualized in any system for fractional states due to experimental challenges. Here we report the imaging of FCI edge states in twisted MoTe2 by employing a newly developed modality of microwave-impedance microscopy. By tuning the carrier density, we observe the system evolving between metallic and FCI states, the latter of which exhibits insulating bulk and conductive edges as expected from bulk-boundary correspondence. We also observe the evolution of edge states across the topological phase transition from an incompressible Chern insulator state to a metal and finally to a putative charge ordered insulating state as a function of interlayer electric field. The local measurement further reveals tantalizing prospects of neighboring domains with different fractional orders. These findings pave the way for research into topologically protected 1D interfaces between various anyonic states at zero magnetic field, such as topological entanglement entropy, Halperin-Laughlin interfaces, and the creation of non-abelian anyons.

cond-mat.str-el↗