Pei Fang, Zhendong Cai, Hui Chen, QingJiang Shi
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques and is a key step to improve the performance of machine learning algorithms. In the multi-party feature engineering scenario (features are stored in many different IoT devices), direct and unlimited multivariate feature transformations will quickly exhaust memory, power, and bandwidth of devices, not to mention the security of information threatened. Given this, we present a framework called FLFE to conduct privacy-preserving and communication-preserving multi-party feature transformations. The framework pre-learns the pattern of the feature to directly judge the usefulness of the transformation on a feature. Explored the new useful feature, the framework forsakes the encryption-based algorithm for the well-designed feature exchange mechanism, which largely decreases the communication overhead under the premise of confidentiality. We made experiments on datasets of both open-sourced and real-world thus validating the comparable effectiveness of FLFE to evaluation-based approaches, along with the far more superior efficacy.
Hui Chen, Daoyuan Fang, Ting Zhang
In this paper, we consider the 3D Navier-Stokes equations in the whole space. We investigate some new inequalities and \textit{a priori} estimates to provide the critical regularity criteria in terms of one directional derivative of the velocity field, namely $\partial_3 \mathbf{u} \in L^p((0,T); L^q(\mathbb{R}^3)), ~\frac{2}{p} + \frac{3}{q} = 2, ~\frac{3}{2}<q\leq 6$. Moreover, we extend the range of $q$ while the solution is axisymmetric, i.e. the axisymmetric solution $\mathbf{m}{u}$ is regular in $(0,T]$, if $ \partial_3 u^3 \in L^p((0,T); L^q(\mathbb{R}^3)), ~\frac{2}{p} + \frac{3}{q} = 2, ~\frac{3}{2}<q< \infty$.
Hui Chen, Chenyin Qian, Ting Zhang
In this paper, we consider the Cauchy problem to the 3D MHD equations. We show that the Serrin--type conditions imposed on one component of the velocity $u_{3}$ and one component of magnetic fields $b_{3}$ with $$ u_{3} \in L^{p_{0},1}(-1,0;L^{q_{0}}(B(2))),\ b_{3} \in L^{p_{1},1}(-1,0;L^{q_{1}}(B(2))), $$ $\frac{2}{p_{0}}+\frac{3}{q_{0}}=\frac{2}{p_{1}}+\frac{3}{q_{1}}=1$ and $3<q_{0},q_{1}<+\infty$ imply that the suitable weak solution is regular at $(0,0)$. The proof is based on the new local energy estimates introduced by Chae-Wolf (Arch. Ration. Mech. Anal. 2021) and Wang-Wu-Zhang (arXiv:2005.11906).
Haitao Yang, Zihao Huang, Yuhang Zhang, Zhen Zhao, Jinan Shi, Hailan Luo, Lin Zhao, Guojian Qian, Hengxin Tan, Bin Hu, Ke Zhu, Zouyouwei Lu, Hua Zhang, Jianping Sun, Jingguagn Cheng, Chengmin Shen, Xiao Lin, Binghai Yan, Xingjiang Zhou, Ziqiang Wang, Stephen J. Pennycook, Hui Chen, Xiaoli Dong, Wu Zhou, Hong-Jun Gao
The vanadium-based kagome superconductor CsV3Sb5 has attracted tremendous attention due to its unexcepted anomalous Hall effect (AHE), charge density waves (CDWs), nematicity, and a pseudogap pair density wave (PDW) coexisting with unconventional strong-coupling superconductivity (SC). The origins of CDWs, unconventional SC, and their correlation with different electronic states in this kagome system are of great significance, but so far, are still under debate. Chemical doping in the kagome layer provides one of the most direct ways to reveal the intrinsic physics, but remains unexplored. Here, we report, for the first time, the synthesis of Ti-substituted CsV3Sb5 single crystals and its rich phase diagram mapping the evolution of intertwining electronic states. The Ti atoms directly substitute for V in the kagome layers. CsV3-xTixSb5 shows two distinct SC phases upon substitution. The Ti slightly-substituted phase displays an unconventional V-shaped SC gap, coexisting with weakening CDW, PDW, AHE, and nematicity. The Ti highly-substituted phase has a U-shaped SC gap concomitant with a short-range rotation symmetry breaking CDW, while long-range CDW, twofold symmetry of in-plane resistivity, AHE, and PDW are absent. Furthermore, we also demonstrate the chemical substitution of V atoms with other elements such as Cr and Nb, showing a different modulation on the SC phase and CDWs. These findings open up a way to synthesise a new family of doped CsV3Sb5 materials, and further representing a new platform for tuning the different correlated electronic states and superconducting pairing in kagome superconductors.
Hui Chen, Hongkuan Zhang, Qian Wu, Yu Huang, Huy Nguyen, Emil Prodan, Xiaoming Zhou, Guoliang Huang
Synthetic dimensions can be rendered in the physical space and this has been achieved with photonics and cold atomic gases, however, little to no work has been succeeded in acoustics because acoustic wave-guides cannot be weakly coupled in a continuous fashion. Here, we establish the theoretical principles and for the first time manufacture acoustic crystals composed of arrays of acoustic cavities strongly coupled through modulated channels to evidence one-dimensional (1D) and two-dimensional (2D) dynamic topological pumpings. In particular, the topological edge-bulkedge and corner-bulk-corner transport are physically illustrated in finite-sized acoustic structures. We delineate the generated 2D and four-dimensional (4D) quantum Hall effects by calculating first and second Chern numbers and demonstrating robustness against the geometrical imperfections. Synthetic dimensions could provide a powerful way for acoustic topological wave steering and open up a new platform to explore higher-order topological matter in dimensions four and higher.
Hui Chen, Musa Furkan Keskin, Adham Sakhnini, Nicoló Decarli, Sofie Pollin, Davide Dardari, Henk Wymeersch
The far-field channel model has historically been used in wireless communications due to the simplicity of mathematical modeling and convenience for algorithm design. With the need for high data rates, low latency, and ubiquitous connectivity in the sixth generation (6G) of communication systems, new technology enablers such as extremely large antenna arrays (ELAAs), reconfigurable intelligent surfaces (RISs), and distributed multiple-input-multiple-output (D-MIMO) systems will be adopted. These enablers not only aim to improve communication services but also have an impact on localization and sensing (L&S), which are expected to be fundamentally built-in functionalities in future wireless systems. Despite appearing in different scenarios and supporting different frequency bands, such enablers share the so-called near-field (NF) features, which will provide extra geometric information conducive to L&S. In this work, we describe the NF features, namely, the spherical wave model, spatial non-stationarity, and beam squint effect. After discussing how L&S see NF differently from communication, the opportunities and open research challenges are provided.
Chen Hui, Ma Wen-Gan, Zhang Ren-You, Zhou Pei-Jun, Hou Hong-Sheng, Sun Yan-Bin
We calculate the ${\cal O}(α_{s})$ QCD and ${\cal O}(α_{\rm ew})$ electroweak one-loop corrections in the Standard Model framework, to the production of an intermediate Higgs boson associated with $t\bar{t}$ pair via $γγ$ fusion at an electron-positron linear collider (LC). We find the ${\cal O}(α_{s})$ QCD corrections can be larger than the ${\cal O}(α_{\rm ew})$ electroweak ones, with the variations of the Higgs boson mass $m_{h}$ and $e^+e^-$ colliding energy $\sqrt{s}$. Both corrections may significantly decrease or increase the Born cross section. The numerical results show that the relative corrections from QCD to the process \eep may reach 34.8%, when $\sqrt{s}=800$ GeV and $m_h=200$ GeV, while those from electroweak can be -13.1%, -15.8% and -12.0%, at $\sqrt{s} = 800$ GeV, 1 TeV and 2 TeV respectively.
Yuan Yuan, Hui Chen
In turbid media, scattering of light scrambles information of the incident beam and represents an obstacle to optical imaging. Noninvasive imaging through opaque layers is challenging for dynamic and wide-field objects due to unreliable image reconstruction processes. We here propose a new perspective to solve these problems: rather than using the full point-spread-function (PSF), the wave distortions in scattering layers can be characterized with only the phase of the optical-transfer-function (OTF, the Fourier transform of PSF), with which diffraction-limit images can be analytically solved. We then develop a method that exploits the redundant information dynamic objects, and can reliably and rapidly recover OTFs' phases within several iterations. It enables not only noninvasive video imaging at 25 ~ 200 Hz of a moving object hidden inside turbid media, but also imaging under weak illumination that is inaccessible with previous methods. Furthermore, by scanning a localized illumination on the object plane, we propose a wide-field imaging approach, with which we demonstrate an application where a photoluminescent sample hidden behind four-layers of opaque polythene films is imaged with a modified multi-photon excitation microscopy setup.
Yi Lu, Hui Chen, Jukka Talvitie, Henk Wymeersch, Mikko Valkama
Reconfigurable intelligent surfaces (RISs) are expected to be a key component enabling the mobile network evolution towards a flexible and intelligent 6G wireless platform. In most of the research works so far, RIS has been treated as a passive base station (BS) with a known state, in terms of its location and orientation, to boost the communication and/or terminal positioning performance. However, such performance gains cannot be guaranteed anymore when the RIS state is not perfectly known. In this paper, by taking the RIS state uncertainty into account, we formulate and study the performance of a joint RIS calibration and user positioning (JrCUP) scheme. From the Fisher information perspective, we formulate the JrCUP problem in a network-centric single-input multiple-output (SIMO) scenario with a single BS, and derive the analytical lower bound for the states of both user and RIS. We also demonstrate the geometric impact of different user locations on the JrCUP performance while also characterizing the performance under different RIS sizes. Finally, the study is extended to a multi-user scenario, shown to further improve the state estimation performance.
Ali Behravan, Vijaya Yajnanarayana, Musa Furkan Keskin, Hui Chen, Deep Shrestha, Traian E. Abrudan, Tommy Svensson, Kim Schindhelm, Andreas Wolfgang, Simon Lindberg, Henk Wymeersch
Among the key differentiators of 6G compared to 5G will be the increased emphasis on radio based positioning and sensing. These will be utilized not only for conventional location-aware services and for enhancing communication performance, but also to support new use case families with extreme performance requirements. This paper presents a unified vision from stakeholders across the value chain in terms of both opportunities and challenges for 6G positioning and sensing, as well as use cases, performance requirements, and gap analysis. Combined, this motivates the technical advances in 6G and guides system design.
Mustafa Ammous, Hui Chen, Henk Wymeersch, Shahrokh Valaee
Reconfigurable intelligent surfaces (RISs) are expected to be a main component of future 6G networks, due to their capability to create a controllable wireless environment, and achieve extended coverage and improved localization accuracy. In this paper, we present a novel cooperative positioning use case of the RIS in mmWave frequencies, and show that in the presence of RIS, together with sidelink communications, localization with zero access points (APs) is possible. We show that multiple (at least three) half-duplex single-antenna user equipments (UEs) can cooperatively estimate their positions through device-to-device communications with a single RIS as an anchor without the need for any APs. We start by formulating a three-dimensional positioning problem with Cramér-Rao lower bound (CRLB) derived for performance analysis. After that, we discuss the RIS profile design and the power allocation strategy between the UEs. Then, we propose low-complexity estimators for estimating the channel parameters and UEs' positions. Finally, we evaluate the performance of the proposed estimators and RIS profiles in the considered scenario via extensive simulations and show that sub-meter level positioning accuracy can be achieved under multi-path propagation.
Xianghe Han, Hui Chen, Zhongyi Cao, Jingwen Guo, Fucong Fei, Hengxin Tan, Jianfeng Guo, Yanhao Shi, Runnong Zhou, Ruwen Wang, Zhen Zhao, Haitao Yang, Fengqi Song, Shiyu Zhu, Binghai Yan, Ziqiang Wang, Hong-Jun Gao
The symmetry breaking and its interplay among spin, charge, and lattice degrees of freedom is crucial for understanding correlated quantum states such as charge density waves (CDWs) and unconventional superconductivity. Here, we report the discovery by low-temperature scanning tunneling microscopy/spectroscopy of unconventional charge-spin-intertwined density waves in magnetic kagome metal GdTi3Bi4, which exhibits the one-third magnetization plateau. We reveal the emergence of 3Q CDWs incommensurate with the crystalline lattice in both periodicity and orientation, breaking all mirror and rotation symmetries. The CDW exhibits incommensurate-commensurate transitions in an applied magnetic field and transitions between 3Q and 1Q CDWs as a function of field and temperature, accompanied by changes in the spatial symmetries. Remarkably, the quantum and classic melting of the CDWs exhibits a phase structure which is consistent with the magnetization phase diagram of bulk GdTi3Bi4, providing strong evidence for the intertwined charge-spin density wave order. The origin of the charge-spin intertwinement is further evidenced by the observed hybridization between itinerant electrons and Gd local moments. Our findings uncover an unconventional form of charge-spin orders and offer new insights into a broad class of multi-components density wave formation in kagome and other correlated quantum materials.
Hui Chen, Miao Xiong, Yujie Lu, Wei Han, Ailin Deng, Yufei He, Jiaying Wu, Yibo Li, Yue Liu, Bryan Hooi
Recent advancements in AI agents have demonstrated their growing potential to drive and support scientific discovery. In this work, we introduce MLR-Bench, a comprehensive benchmark for evaluating AI agents on open-ended machine learning research. MLR-Bench includes three key components: (1) 201 research tasks sourced from NeurIPS, ICLR, and ICML workshops covering diverse ML topics; (2) MLR-Judge, an automated evaluation framework combining LLM-based reviewers with carefully designed review rubrics to assess research quality; and (3) MLR-Agent, a modular agent scaffold capable of completing research tasks through four stages: idea generation, proposal formulation, experimentation, and paper writing. Our framework supports both stepwise assessment across these distinct research stages, and end-to-end evaluation of the final research paper. We then use MLR-Bench to evaluate six frontier LLMs and an advanced coding agent, finding that while LLMs are effective at generating coherent ideas and well-structured papers, current coding agents frequently (e.g., in 80% of the cases) produce fabricated or invalidated experimental results--posing a major barrier to scientific reliability. We validate MLR-Judge through human evaluation, showing high agreement with expert reviewers, supporting its potential as a scalable tool for research evaluation. We open-source MLR-Bench to help the community benchmark, diagnose, and improve AI research agents toward trustworthy and transparent scientific discovery.
Hui Chen, Hyowon Kim, Mustafa Ammous, Gonzalo Seco-Granados, George C. Alexandropoulos, Shahrokh Valaee, Henk Wymeersch
A smart city involves, among other elements, intelligent transportation, crowd monitoring, and digital twins, each of which requires information exchange via wireless communication links and localization of connected devices and passive objects (including people). Although localization and sensing (L&S) are envisioned as core functions of future communication systems, they have inherently different demands in terms of infrastructure compared to communications. Wireless communications generally requires a connection to only a single access point (AP), while L&S demand simultaneous line-of-sight propagation paths to several APs, which serve as location and orientation anchors. Hence, a smart city deployment optimized for communication will be insufficient to meet stringent L&S requirements. In this article, we argue that the emerging technologies of reconfigurable intelligent surfaces (RISs) and sidelink communications constitute the key to providing ubiquitous coverage for L&S in smart cities with low-cost and energy-efficient technical solutions. To this end, we propose and evaluate AP-coordinated and self-coordinated RIS-enabled L&S architectures and detail three groups of application scenarios, relying on low-complexity beacons, cooperative localization, and full-duplex transceivers. A list of practical issues and consequent open research challenges of the proposed L&S systems is also provided.
Hui Chen, Mengting Li, Alireza Pourafzal, Huiping Huang, Yu Ge, Sigurd Sandor Petersen, Ming Shen, George C. Alexandropoulos, Henk Wymeersch
Integrated sensing and communication (ISAC) is a key technology for enabling a wide range of applications in future wireless systems. However, the sensing performance is often degraded by model mismatches caused by geometric errors (e.g., position and orientation) and hardware impairments (e.g., mutual coupling and amplifier non-linearity). This paper focuses on the angle estimation performance with antenna arrays and tackles the critical challenge of array beam pattern calibration for ISAC systems. To assess calibration quality from a sensing perspective, a novel performance metric that accounts for angle estimation error, rather than beam pattern similarity, is proposed and incorporated into a differentiable loss function. Additionally, a cooperative calibration framework is introduced, allowing multiple user equipments to iteratively optimize the beam pattern based on the proposed loss functions and local data, and collaboratively update global calibration parameters. The proposed models and algorithms are validated using real-world beam pattern measurements collected in an anechoic chamber. Experimental results show that the angle estimation error can be reduced from {$\textbf{1.01}^\circ$} to $\textbf{0.11}^\circ$ in 2D calibration scenarios, and from $\textbf{5.19}^\circ$ to $\textbf{0.86}^\circ$ in 3D calibration ones.
Hui Chen, Deepanway Ghosal, Navonil Majumder, Amir Hussain, Soujanya Poria
Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies. Due to its potential application in persuasive dialogue systems, the task of persuasive strategy recognition has gained much attention lately. Previous methods on user intent recognition in dialogue systems adopt recurrent neural network (RNN) or convolutional neural network (CNN) to model context in conversational history, neglecting the tactic history and intra-speaker relation. In this paper, we demonstrate the limitations of a Transformer-based approach coupled with Conditional Random Field (CRF) for the task of persuasive strategy recognition. In this model, we leverage inter- and intra-speaker contextual semantic features, as well as label dependencies to improve the recognition. Despite extensive hyper-parameter optimizations, this architecture fails to outperform the baseline methods. We observe two negative results. Firstly, CRF cannot capture persuasive label dependencies, possibly as strategies in persuasive dialogues do not follow any strict grammar or rules as the cases in Named Entity Recognition (NER) or part-of-speech (POS) tagging. Secondly, the Transformer encoder trained from scratch is less capable of capturing sequential information in persuasive dialogues than Long Short-Term Memory (LSTM). We attribute this to the reason that the vanilla Transformer encoder does not efficiently consider relative position information of sequence elements.
Hussein Nassar, Hui Chen, Guoliang Huang
The topologically polarized isostatic lattices discovered by Kane and Lubensky (2014, Nat. Phys. 10, 39-45) challenged the standard effective medium theories used in the modeling of many truss-based materials and metamaterials. As a matter of fact, these exhibit Parity (P) asymmetric distributions of zero modes that induce a P-asymmetric elastic behavior, both of which cannot be reproduced within Cauchy elasticity. Here, we propose a new effective medium theory baptized "microtwist elasticity" capable of rendering polarization effects on a macroscopic scale. The theory is valid for trusses on the brink of a polarized-unpolarized phase transition in which case they necessarily exhibit more periodic zero modes than they have dimensions. By mapping each periodic zero mode to a macroscopic degree of freedom, the microtwist theory ends up being a kinematically enriched theory. Microtwist elasticity is constructed thanks to leading order two-scale asymptotics and its constitutive and balance equations are derived for a fairly generic isostatic truss: the Kagome lattice. Various numerical and analytical calculations, of the shape and distribution of zero modes, of dispersion diagrams and of polarization effects, systematically show the quality of the proposed effective medium theory. Most notably, the theory is capable of producing a continuum version of Kane and Lubensky's topological polarization vector.
Hui Chen, Kostadin Damevski, David Shepherd, Nicholas A. Kraft
Traces of user interactions with a software system, captured in production, are commonly used as an input source for user experience testing. In this paper, we present an alternative use, introducing a novel approach of modeling user interaction traces enriched with another type of data gathered in production - software fault reports consisting of software exceptions and stack traces. The model described in this paper aims to improve developers' comprehension of the circumstances surrounding a specific software exception and can highlight specific user behaviors that lead to a high frequency of software faults. Modeling the combination of interaction traces and software crash reports to form an interpretable and useful model is challenging due to the complexity and variance in the combined data source. Therefore, we propose a probabilistic unsupervised learning approach, adapting the Nested Hierarchical Dirichlet Process, which is a Bayesian non-parametric topic model commonly applied to natural language data. This model infers a tree of topics, each of whom describes a set of commonly co-occurring commands and exceptions. The topic tree can be interpreted hierarchically to aid in categorizing the numerous types of exceptions and interactions. We apply the proposed approach to large scale datasets collected from the ABB RobotStudio software application, and evaluate it both numerically and with a small survey of the RobotStudio developers.
Hui Chen, Ahmed Elzanaty, Reza Ghazalian, Musa Furkan Keskin, Riku Jäntti, Henk Wymeersch
Radio localization is applied in high-frequency (e.g., mmWave and THz) systems to support communication and to provide location-based services without extra infrastructure. {For solving localization problems, a simplified, stationary, narrowband far-field channel model is widely used due to its compact formulation.} However, with increased array size in extra-large MIMO systems and increased bandwidth at upper mmWave bands, the effect of channel spatial non-stationarity (SNS), spherical wave model (SWM), and beam squint effect (BSE) cannot be ignored. In this case, localization performance will be affected when an inaccurate channel model deviating from the true model is adopted. In this work, we employ the MCRB (misspecified Cramér-Rao lower bound) to lower bound the localization error using a simplified mismatched model while the observed data is governed by a more complex true model. The simulation results show that among all the model impairments, the SNS has the least contribution, the SWM dominates when the distance is small compared to the array size, and the BSE has a more significant effect when the distance is much larger than the array size.
Haitao Yang, Zhen Zhao, Xin-Wei Yi, Jiali Liu, Jing-Yang You, Yuhang Zhang, Hui Guo, Xiao Lin, Chengmin Shen, Hui Chen, Xiaoli Dong, Gang Su, Hong-Jun Gao
Since the discovery of a new family of vanadium-based kagome superconductor AV3Sb5 (A=K, Rb, and Cs) with topological band structures, extensive effort has been devoted to exploring the origin of superconducting states and the intertwined orders. Meanwhile, searching for new types of superconductors with novel physical properties and higher superconducting transition temperatures has always been a major thread in the history of superconductor research. Here we report a successful fabrication and the topological states of a Titanium-based kagome metal CsTi3Bi5 (CT3B5) crystal. The as-grown CT3B5 crystal is of high quality and possesses a perfect two-dimensional kagome net of Titanium. The superconductivity of the CT3B5 crystal shows that the critical temperature Tc is of ~4.8 K. First-principle calculations predict that the CT3B5 has robust topological surface states, implying that CT3B5 is a Z2 topological kagome superconductor. This finding provides a new type of superconductors and the base for exploring the origin of superconductivity and topological states in kagome superconductors.