arXiv subjects

Kun Yang

Publications and source records attributed to Kun Yang.

At least 181 records · Page 10Linked to original sources

arXiv2023

Spin-selective magneto-conductivity in WSe$_2$

Material systems that exhibit tunable spin-selective conductivity are key components of spintronic technologies. Here we demonstrate a novel type of spin-selective transport, based on the unusual Landau level (LL) sequence observed in bilayer WSe$_2$ under large applied magnetic fields. We find that the conductivity depends strongly on the relative iso-spin ordering between conducting electrons in a partially filled LL and the localized electrons of lower energy filled LLs, with conductivity observed to be almost completely suppressed when the spin-ratio and field-tuned Coulomb energy exceed a critical threshold. Switching between "on/off" states is achievable through either modulation of the external magnetic or electric fields, with many-body interaction driving a collective switching mechanism. In contrast to magnetoresistive heterostructures, this system achieves electrically tunable spin filtering within a single material, driven by interaction between free and localized spins residing in energy-separated spin/valley polarized bands. Similar spin-selective conductivity may be realizable in multi-flat band systems at zero magnetic field.

cond-mat.mes-hall↗

arXiv2023

Byzantine-Robust Clustered Federated Learning

This paper focuses on the problem of adversarial attacks from Byzantine machines in a Federated Learning setting where non-Byzantine machines can be partitioned into disjoint clusters. In this setting, non-Byzantine machines in the same cluster have the same underlying data distribution, and different clusters of non-Byzantine machines have different learning tasks. Byzantine machines can adversarially attack any cluster and disturb the training process on clusters they attack. In the presence of Byzantine machines, the goal of our work is to identify cluster membership of non-Byzantine machines and optimize the models learned by each cluster. We adopt the Iterative Federated Clustering Algorithm (IFCA) framework of Ghosh et al. (2020) to alternatively estimate cluster membership and optimize models. In order to make this framework robust against adversarial attacks from Byzantine machines, we use coordinate-wise trimmed mean and coordinate-wise median aggregation methods used by Yin et al. (2018). Specifically, we propose a new Byzantine-Robust Iterative Federated Clustering Algorithm to improve on the results in Ghosh et al. (2019). We prove a convergence rate for this algorithm for strongly convex loss functions. We compare our convergence rate with the convergence rate of an existing algorithm, and we demonstrate the performance of our algorithm on simulated data.

stat.ML↗

arXiv2023

Simultaneously Transmitting and Reflecting RIS (STAR-RIS) Assisted Multi-Antenna Covert Communications: Analysis and Optimization

This paper investigates the multi-antenna covert communications assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In particular, to shelter the existence of covert communications between a multi-antenna transmitter and a single-antenna receiver from a warden, a friendly full-duplex receiver with two antennas is leveraged to make contributions where one antenna is responsible for receiving the transmitted signals and the other one transmits the jamming signals with a varying power to confuse the warden. Considering the worst case, the closed-form expression of the minimum detection error probability (DEP) at the warden is derived and utilized in a covert constraint to guarantee the system performance. Then, we formulate an optimization problem maximizing the covert rate of the system under the covertness constraint and quality of service (QoS) constraint with communication outage analysis. To jointly design the active and passive beamforming of the transmitter and STAR-RIS, an iterative algorithm based on semi-definite relaxation (SDR) method and Dinkelbachs algorithm is proposed to effectively solve the non-convex optimization problem. Simulation results show that the proposed STAR-RIS-assisted scheme highly outperforms the case with conventional RIS, which validates the effectiveness of the proposed algorithm as well as the superiority of STAR-RIS in guaranteeing the covertness of wireless communications.

cs.IT↗

arXiv2023

Enigma of the vortex state in a strongly correlated d-wave superconductor

We show that strong electronic repulsion transforms a vortex core from a metallic-type in overdoped regime to a Mott-insulator at underdoping of a strongly correlated d-wave superconductor. This changeover is accompanied by an accumulation of electron density at the vortex core towards local half-filling in the underdoped region, which in turn facilitates the formation of the Mott insulating core. We find that the size of vortices evolves non-monotonically with doping. A similar non-monotonicity of critical field $H_{\rm c2}$, as extracted from superfluid stiffness, is also found. Our results explain some recent experimental puzzles of cuprate superconductors.

cond-mat.supr-con↗

arXiv2023

Polar Coded Integrated Data and Energy Networking: A Deep Neural Network Assisted End-to-End Design

Wireless sensors are everywhere. To address their energy supply, we proposed an end-to-end design for polar-coded integrated data and energy networking (IDEN), where the conventional signal processing modules, such as modulation/demodulation and channel decoding, are replaced by deep neural networks (DNNs). Moreover, the input-output relationship of an energy harvester (EH) is also modelled by a DNN. By jointly optimizing both the transmitter and the receiver as an autoencoder (AE), we minimize the bit-error-rate (BER) and maximize the harvested energy of the IDEN system, while satisfying the transmit power budget constraint determined by the normalization layer in the transmitter. Our simulation results demonstrate that the DNN aided end-to-end design conceived outperforms its conventional model-based counterpart both in terms of the harvested energy and the BER.

cs.IT↗

arXiv2023

DMSA: Dynamic Multi-scale Unsupervised Semantic Segmentation Based on Adaptive Affinity

The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyramid Pooling (ASPP) module to enhance feature extraction. At the same time, a dynamic dilation strategy is designed to better capture multi-scale context information. Secondly, a Pixel-Adaptive Refinement (PAR) module is introduced, which can adaptively refine the initial pseudo labels after feature fusion to obtain high quality pseudo labels. Experiments show that the proposed DSMA framework is superior to the existing methods on the saliency dataset. On the COCO 80 dataset, the MIoU is improved by 2.0, and the accuracy is improved by 5.39. On the Pascal VOC 2012 Augmented dataset, the MIoU is improved by 4.9, and the accuracy is improved by 3.4. In addition, the convergence speed of the model is also greatly improved after the introduction of the PAR module.

cs.CV↗

arXiv2023

A novel efficient Multi-view traffic-related object detection framework

With the rapid development of intelligent transportation system applications, a tremendous amount of multi-view video data has emerged to enhance vehicle perception. However, performing video analytics efficiently by exploiting the spatial-temporal redundancy from video data remains challenging. Accordingly, we propose a novel traffic-related framework named CEVAS to achieve efficient object detection using multi-view video data. Briefly, a fine-grained input filtering policy is introduced to produce a reasonable region of interest from the captured images. Also, we design a sharing object manager to manage the information of objects with spatial redundancy and share their results with other vehicles. We further derive a content-aware model selection policy to select detection methods adaptively. Experimental results show that our framework significantly reduces response latency while achieving the same detection accuracy as the state-of-the-art methods.

cs.CV↗

arXiv2023

Orthogonal-Time-Frequency-Space Signal Design for Integrated Data and Energy Transfer: Benefits from Doppler Offsets

Integrated data and energy transfer (IDET) is an advanced technology for enabling energy sustainability for massively deployed low-power electronic consumption components. However, the existing work of IDET using the orthogonal-frequency-division-multiplexing (OFDM) waveforms is designed for static scenarios, which would be severely affected by the destructive Doppler offset in high-mobility scenarios. Therefore, we proposed an IDET system based on orthogonal-time-frequency-space (OTFS) waveforms with the imperfect channel assumption, which is capable of counteracting the Doppler offset in high-mobility scenarios. At the transmitter, the OTFS-IDET system superimposes the random data signals and deterministic energy signals in the delay-Doppler (DD) domain with optimally designed amplitudes. The receiver optimally splits the received signal in the power domain for achieving the best IDET performance. After formulating a non-convex optimisation problem, it is transformed into a geometric programming (GP) problem through inequality relaxations to obtain the optimal solution. The simulation demonstrates that a higher amount of energy can be harvested when employing our proposed OTFS-IDET waveforms than the conventional OFDM-IDET ones in high mobility scenarios.

eess.SP↗

arXiv2023

Non-Fermi liquid behavior in a simple model of Fermi arcs and pseudogap

We consider a perturbed version of a very simple and exactly solvable model that supports Fermi arcs and pseudogap in its ground state and excitation spectrum, which includes Hubbard-like interactions in both momentum and real spaces. We find the combined effects give rise to non-Fermi liquid behavior in the electron self-energy. Comparison will be made with phenomenology of high temperature cuprate superconductors.

cond-mat.str-el↗

arXiv2023

Eigenstate thermalization and disappearance of quantum many-body scar states in interacting fermion systems

The recent discovery of quantum many-body scar states has revealed the possibility of having states with low entanglement that violate the eigenstate thermalization hypothesis in nonintegrable systems. Such states with low entanglement entropy are rare but naturally exist in the integrable system of free fermions. Here, we demonstrate analytically that these atypical states would be always eliminated when an arbitrary weak interaction is introduced between the fermions. In particular, we show that the probability of having a many-body scar state with entanglement entropy satisfying a sub-volume scaling law decreases double exponentially as the system size. Thus, our results provide a quantitative argument for the disappearance of scar states in interacting fermion systems.

cond-mat.stat-mech↗

arXiv2022

String-like Theory of Quantum Hall Interfaces

We derive the effective theories for quantum hall droplets with attractive interaction among the constituent particles. In the absence of confining potentials such droplets are defined by their freely moving interfaces (or boundaries) with the vacuum. We demonstrate the effective theories take forms similar to string theories. Generalization to interfaces between different quantum Hall liquids is discussed.

cond-mat.str-el↗

arXiv2022

Two Types of 3D Quantum Hall Effects in Multilayer WTe$_2$

Interplay between the topological surface states and bulk states gives rise to diverse exotic transport phenomena in topological materials. The recently proposed Weyl orbit in topological semimetals in the presence of magnetic field is a remarkable example. This novel closed magnetic orbit consists of Fermi arcs on two spatially separated sample surfaces which are connected by the bulk chiral zero mode, which can contribute to transport. Here we report Shubnikov-de Haas (SdH) oscillation and its evolution into quantum Hall effect (QHE) in multilayered type-II Weyl semimetal WTe2. We observe both the three-dimensional (3D) QHE from bulk states by parallelly stacking of confined two-dimensional layers in the low magnetic field region and the 3D QHE in the quantized surface transport due to Weyl orbits in the high magnetic field region. Our study of the two types of novel QHEs controlled by magnetic field and our demonstration of the crossover between quantized bulk and surface transport provide an essential platform for the future quantized transport studies in topological semimetals.

cond-mat.mes-hall↗

arXiv2022

SISO-OFDM and MISO-OFDM Counterparts for "Wideband Waveforming for Integrated Data and Energy Transfer: Creating Extra Gain Beyond Multiple Antennas and Multiple Carriers"

In this article, we proposethe SISO-OFDM and MISO-OFDM based IDET systems, which are the counterparts of our optimal wideband waveforming strategy in [1]. The fair-throughput and the sum-throughput optimisation problems are formulated. By exploiting the FP based alternating algorithm, we obtain the optimal fair-throughput and sum-throughput for both the SISO-OFDM and MISO-OFDM.

eess.SP↗

arXiv2022

Fractional quantum Hall effect at the filling factor $ν=5/2$

The fractional quantum Hall (FQH) effect at the filling factor $ν=5/2$ was discovered in GaAs heterostructures more than 35 years ago. Various topological orders have been proposed as possible candidates to describe this FQH state. Some of them possess non-Abelian anyon excitations, an entirely new type of quasiparticle with fascinating properties. If observed, non-Abelian anyons could offer fundamental building blocks of a topological quantum computer. Nevertheless, the nature of the FQH state at $ν=5/2$ is still under debate. In this chapter, we provide an overview of the theoretical background, numerical results, and experimental measurements pertaining to this special FQH state. Furthermore, we review some recent developments and their possible interpretations. Possible future directions toward resolving the nature of the $5/2$ state are also discussed.

cond-mat.mes-hall↗

arXiv2022

Task-load-Aware Game-Theoretic Framework for Wireless Federated Learning

Federated learning (FL) has been proposed as a popular learning framework to protect the users' data privacy but it has difficulties in motivating the users to participate in task training. This paper proposes a Bertrand-game-based framework for FL in wireless networks, where the model server as a resource buyer can issue an FL task, whereas the employed user equipment (UEs) as the resource sellers can help train the model by using their local data. Specially, the influence of time-varying \textit{task load} and \textit{channel quality} on UE's motivation to participate in FL is considered. Firstly, we adopt the finite-state discrete-time Markov chain (FSDT-MC) method to predict the \textit{existing task load} and \textit{channel gain} of a UE during a FL task. Depending on the performance metrics set by the model server and the estimated overall energy cost for engaging in the FL task, each UE seeks the best price to maximize its own profit in the game. To this end, the Nash equilibrium (NE) of the game is obtained in closed form, and a distributed iterative algorithm is also developed to find the NE. Simulation result verifies the effectiveness of the proposed approach.

cs.GT↗

arXiv2022

Exact solution for finite center-of-mass momentum Cooper pairing

Pair density waves (PDWs) are superconducting states formed by ``Cooper pairs" of electrons containing a non-zero center-of-mass momentum. They are characterized by a spatially modulated order parameter and may occur in a variety of emerging quantum materials such as cuprates, transition metal dichalcogenides (TMDs) and Kagome metals. Despite extensive theoretical and numerical studies seeking PDWs in a variety of lattices and interacting settings, there is currently no generic and robust mechanism that favors a modulated solution of the superconducting order parameter in the presence of time reversal symmetry. Here, we study the problem of two electrons subject to an anisotropic ($d$-wave) attractive potential. We solve the two-body Schrodinger wave equation exactly to determine the pair binding energy as a function of the center-of-mass momentum. We find that a modulated (finite momentum) pair is favored over a homogeneous (zero momentum) solution above a critical interaction. Using this insight from the exact two-body solution, we construct a BCS-like variational many-body wave function and calculate the free energy and superconducting gap as a function of the center-of-mass momentum. A zero temperature analysis of the energy shows that the conclusions of the two-body problem are robust in the many-body limit. Our results lay the theoretical and microscopic foundation for the existence of PDWs.

cond-mat.supr-con↗

arXiv2022

Review of research on lunar dust dynamics

Lunar dust particles are generated by hypervelocity impacts of interplanetary micron-meteoroids onto the surface of the Moon, which seriously threatens the security of explorations. Studying the lunar dust dynamics helps to understand the origin and migration mechanism of lunar dust, and to provide the theoretical guidelines for the orbital design of lunar space missions. This paper reviews previous research on the lunar dust dynamics, including the interplanetary impactor environment at the Earth-Moon system, the mass production rate, the initial mass, speed and ejecta angle distributions, the related space exploration missions, the dynamical model and spatial distribution of dust particles originating from the lunar surface in the whole Earth-Moon system.

astro-ph.EP↗

arXiv2022

Kolmogorov complexity as intrinsic entropy of a pure state: Perspective from entanglement in free fermion systems

We consider free fermion systems in arbitrary dimensions and represent the occupation pattern of each eigenstate as a classical binary string. We find that the Kolmogorov complexity of the string correctly captures the scaling behavior of its entanglement entropy (EE). In particular, the logarithmically-enhanced area law for EE in the ground state and the volume law for EE in typical highly excited states are reproduced. Since our approach does not require bipartitioning the system, it allows us to distinguish typical and atypical eigenstates directly by their intrinsic complexity. We reveal that the fraction of atypical eigenstates which do not thermalize in the free fermion system vanishes exponentially in the thermodynamic limit. Our results illustrate explicitly the connection between complexity and EE of individual pure states in quantum systems.

cond-mat.stat-mech↗