arXiv subjects

Xinyuan Jiang

Publications and source records attributed to Xinyuan Jiang.

9 recordsLinked to original sources

arXiv2026

Multistate Manipulation of Charge-Spin Conversion in Two-Dimensional Ferroelectric Bilayers

Achieving nonvolatile and multistate manipulation of charge-spin conversion, including the Edelstein effect (EE) and spin Hall effect (SHE), is crucial for high-density spintronic memory. Here, we propose a mechanism to simultaneously control both EE and SHE in two-dimensional ferroelectric bilayers, where interlayer-parallel and interlayer-antiparallel polarization configurations can coexist. Symmetry analysis shows that in the interlayer-parallel states, reversal of the total polarization switches the sign of the EE, whereas changing to an interlayer-antiparallel configuration suppresses the EE to zero, enabling electrically switchable current-induced spin accumulation among three distinct states, which could be used for ternary logic operations. Meanwhile, the magnitude of the SHE can be tuned by switching between two different classes of polarization configurations, namely interlayer-parallel and interlayer-antiparallel configurations. Using first-principles calculations, we demonstrate this mechanism in bilayer metallic ferroelectric PtBi2, where both interlayer-parallel and interlayer-antiparallel polarization configurations are energetically stable. The EE coefficient in interlayer-parallel states, which can be reversed by polarization switching, arises from competing electron- and hole-pocket contributions near the Fermi surface. The intrinsic SHE coefficients originate from spin Berry curvature that can be reshaped by polarization configuration variation and Fermi-level tuning. Our results establish ferroelectric bilayers as an all-in-one platform for electrically programmable charge-spin conversion.

cond-mat.mtrl-sci↗

arXiv2026

Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations

Operating and maintaining (O&M) large-scale online engine systems (eg, search, recommendation and advertising) demands substantial human effort for release monitoring, alert response, and root cause analysis. Despite the inherent suitability of LLM-based agents for such operational scenarios, the critical bottleneck impeding their practical deployment lies not in reasoning, but in orchestration capability - specifically, the precise selection of relevant data (encompassing metrics, logs, and change events) and applicable knowledge (including handbook-defined rules and empirically derived practitioner experience) tailored to each individual operational event. Feeding all signals indiscriminately causes dilution and hallucination, while manually curating the event-to-(data, knowledge) mapping is intractable under dozens of daily releases. Here we present Bian Que, an agentic operating framework with three contributions: (i) The unified operational paradigm, which abstracts routine daily O&M actions into three canonical patterns: release interception, proactive inspection, and alert root cause analysis; (ii) The flexible Skill Arrangement, each predefined Skill explicitly defines the requisite data and operational knowledge for each specific context. Such Skills can be automatically generated and updated by LLM agents, and can also be iteratively optimized by on-call engineers via natural language instructions. (iii) The unified self-evolving mechanism, where each correction signal enables two parallel evolutionary pathways: distilling event memory into knowledge, and targeted refinement of Skills. Deployed on the e-commerce search engine of KuaiShou, Bian Que reduces alert volume by 75%, achieves 80% root-cause analysis accuracy, cuts mean time to resolution by over 50%, and attains a 99.0% pass rate on offline evaluations. Codes are at https://github.com/benchen4395/BianQue_Assistant.

cs.AI↗

arXiv2026

Shifted Dissipativity and Rotor-Angle Feedback for Orbital Stability of Power Networks

This paper considers a shifted dissipativity property of synchronous generators (SGs) with the aim of establishing stability of the synchronous orbit of a power network. Existing shifted-passivity analyses are formulated in a reference frame attached to the rotor and therefore suppress the problem of rotor-angle alignment in a multimachine network. The analysis takes two steps to reconcile angle-modulated power sources with dissipation. First, we define a weaker shifted dissipativity property whose supply rate retains a cross term between rotor-angle and terminal-voltage errors. We show that an SG connected to an infinite bus is locally asymptotically stable if it satisfies this property. Second, for networks of multiple SGs interconnected through dynamic transmission lines and static loads, we introduce a consensus-like rotor-angle feedback that consolidates the contributions of the distributed angle-modulated power sources into a single effective channel. This channel is then dominated by the dissipative dynamics of an auxiliary state variable representing the phase of the synchronous orbit, thereby establishing local orbital stability. Numerical examples demonstrate the feasibility of the shifted dissipativity condition.

eess.SY↗

arXiv2025

Switching between Skyrmions and Yoshimori Spin Spirals via Li Absorption in Janus Magnets

Chiral magnetic textures have attracted considerable attention owing to their topological properties and potential applications in spintronic devices. Here, we employ first-principles calculations together with atomic spin dynamics simulations to explore the switching between skyrmions and Yoshimori-type spin spirals induced by Li adsorption in Janus two-dimensional (2D) CrTeSe. We show that selective Li adsorption on either the Se- or Te-terminated surface stabilizes distinct magnetic phases: Li adsorption on the Se side favors a Yoshimori-type spin spiral, whereas adsorption on the Te side stabilizes the skyrmionic state. This contrast originates from site-dependent modifications of exchange interactions, magnetic anisotropy (MA), and the Dzyaloshinskii-Moriya interaction (DMI). In addition, the response of magnetic textures to out-of-plane magnetic fields differs strongly between the two systems. These results demonstrate that surface adsorption provides an effective strategy for reversible control of chiral magnetic states in 2D magnets, while also offering fundamental insights into the competing interactions that govern the stability of skyrmions and Yoshimori spin spirals. Our findings highlight the potential of Janus 2D materials as a versatile platform for engineering tunable spintronic devices.

cond-mat.mtrl-sci↗

arXiv2025

On the Equivalence of Koopman Eigenfunctions and Commuting Symmetries

The Koopman operator framework offers a way to represent a nonlinear system as a linear one. The key to this simplification lies in the identification of eigenfunctions. While various data-driven algorithms have been developed for this problem, a theoretical characterization of Koopman eigenfunctions from geometric properties of the flow is still missing. This paper provides such a characterization by establishing an equivalence between a set of Koopman eigenfunctions and a set of commuting symmetries -- both assumed to span the tangent spaces at every point on a simply connected open set. Based on this equivalence, we derive an explicit formula for the principal Koopman eigenfunctions and prove its uniform convergence on the region of attraction of a locally asymptotically stable equilibrium point, thereby offering a constructive method for computing Koopman eigenfunctions.

eess.SY↗

arXiv2025

A reference frame-based microgrid primary control for ensuring global convergence to a periodic orbit

Power systems with a high penetration of renewable generation are vulnerable to frequency oscillation and voltage instability. Traditionally, the stability of power systems is considered either in terms of local stability or as an angle oscillator synchronization problem with the simplifying assumption that the dynamics of the amplitudes are on much shorter time scales. Without this assumption, however, the steady state being studied is essentially a limit cycle with the convergence of its orbit in question. In this paper, we present a method to analyze the orbital stability of a microgrid and propose a voltage controller for the inverter-interfaced renewable generators. The main hurdle to the problem lies in the constant terms in the rotating internal reference frames of each generator. We extend the shifted passivity of port-Hamiltonian systems to the analysis of limit cycles and prove that, if the system is shifted passive without considering these constant terms, then the periodic orbit is globally attractive. To the best of our knowledge, this is the first global stability result for non-nominal steady states of the microgrid in the full state space, which provides new insights into the synchronization phenomenon where the dissipativity of the system ensures convergence. The proposed controller is verified with a test microgrid, demonstrating its stability and transient smoothness compared to the standard droop control.

eess.SY↗

arXiv2025

Power System Electromagnetic Transient Stability: an Analysis Based on Convergent Hamiltonian

Transient stability is crucial to the reliable operation of power systems. Existing theories rely on the simplified electromechanical models, substituting the detailed electromagnetic dynamics of inductor and capacitor with their impedance representations. However, this simplification is inadequate for the growing penetration of fast-switching power electronic devices. Attempts to extend the existing theories to include electromagnetic dynamics lead to overly conservative stability conditions. To tackle this problem more directly, we study the condition under which the power source and dissipation in the electromagnetic dynamics tend to balance each other asymptotically. This is equivalent to the convergence of the Hamiltonian (total stored energy) and can be shown to imply transient stability. Using contraction analysis, we prove that this property holds for a large class of time-varying port-Hamiltonian systems with (i) constant damping matrix and (ii) strictly convex Hamiltonian. Then through port-Hamiltonian modeling of the electromagnetic dynamics, we obtain that the synchronized steady state of the power system is globally stable if it exists. This result provides new insights into the reliable operation of power systems. The proposed theory is illustrated in the simulation results of a two-machine system.

eess.SY↗

arXiv2022

Modularized Bilinear Koopman Operator for Modeling and Predicting Transients of Microgrids

Modularized Koopman Bilinear Form (M-KBF) is presented to model and predict the transient dynamics of microgrids in the presence of disturbances. As a scalable data-driven approach, M-KBF divides the identification and prediction of the high-dimensional nonlinear system into the individual study of subsystems; and thus, alleviating the difficulty of intensively handling high volume data and overcoming the curse of dimensionality. For each subsystem, Koopman bilinear form is applied to efficiently identify its model by developing eigenfunctions via the extended dynamic mode decomposition method with an eigenvalue-based order truncation. Extensive tests show that M-KBF can provide accurate transient dynamics prediction for the nonlinear microgrids and verify the plug-and-play modeling and prediction function, which offers a potent tool for identifying high-dimensional systems. The modularity feature of M-KBF enables the provision of fast and precise prediction for the microgrid operation and control, paving the way towards online applications.

eess.SY↗

arXiv2022

PIDGeuN: Graph Neural Network-Enabled Transient Dynamics Prediction of Networked Microgrids Through Full-Field Measurement

A Physics-Informed Dynamic Graph Neural Network (PIDGeuN) is presented to accurately, efficiently and robustly predict the nonlinear transient dynamics of microgrids in the presence of disturbances. The graph-based architecture of PIDGeuN provides a natural representation of the microgrid topology. Using only the state information that is practically measurable, PIDGeuN employs a time delay embedding formulation to fully reproduce the system dynamics, avoiding the dependency of conventional methods on internal dynamic states such as controllers. Based on a judiciously designed message passing mechanism, the PIDGeuN incorporates two physics-informed techniques to improve its prediction performance, including a physics-data-infusion approach to determining the inter-dependencies between buses, and a loss term to respect the known physical law of the power system, i.e., the Kirchhoff's law, to ensure the feasibility of the model prediction. Extensive tests show that PIDGeuN can provide accurate and robust prediction of transient dynamics for nonlinear microgrids over a long-term time period. Therefore, the PIDGeuN offers a potent tool for the modeling of large scale networked microgrids (NMs), with potential applications to predictive or preventive control in real time applications for the stable and resilient operations of NMs.

eess.SY↗