arXiv subjects

Qiang Fu

Publications and source records attributed to Qiang Fu.

At least 19 recordsLinked to original sources

arXiv2026

Centers of quantum Schur superalgebras from Hecke algebras

We study the center of the quantum Schur superalgebra $\mathcal{S}_v(m|n,r)$ associated with the general linear Lie superalgebra $\mathfrak{gl}_{m|n}$. Using the super Schur--Weyl duality due to Mitsuhashi between the quantum supergroup $U_v(\mathfrak{gl}_{m|n})$ and the Hecke algebra $\mathcal{H}_v(\mathfrak{S}_r)$, we transfer two known bases of the center of $\mathcal{H}_v(\mathfrak{S}_r)$, namely the Geck--Rouquier basis and the Jones basis, to the center of $\mathcal{S}_v(m|n,r)$. This yields two distinct bases for $\mathscr{Z}(\mathcal{S}_v(m|n,r))$, indexed respectively by the symmetrized hook set $H^{\vee}(m|n,r):=H(\min(m,n)\mid \max(m,n),r)$ and by the full $(m|n)$-hook set $H(m|n,r)$. Our approach relies on a detailed analysis of the ring $\Lambda_{m|n}$ of doubly symmetric polynomials satisfying $f|_{x_m=t=-y_n}$ independent of $t$, and of its power-sum bases.

math.QA↗

arXiv2026

Quantum Locally Repairable Codes from Negacyclic and Repeated-Root Cyclic Codes over Small Fields

Quantum locally recoverable codes (qLRCs), introduced recently by Golowich and Guruswami, allow any single-qudit erasure to be recovered from a small set of other qudits. Most known constructions require a large alphabet. We systematically investigate qLRCs obtained, via the CSS construction, from classical constacyclic codes over small fields $\Ff_q$ with $q\in\{2,3,4,5,7\}$. First, we prove that a nonzero dual-containing $\lambda$-constacyclic code exists only when $\lambda^2=1$, so that negacyclic and (repeated-root) cyclic codes exhaust the constacyclic route to qLRCs. Second, we show that the locality of a constacyclic code equals the minimum distance of its dual minus one, and we give a simple purity criterion for the resulting quantum codes. Third, we show that odd-like duadic codes whose splitting is given by $\mu_{-1}$ yield pure qLRCs; specializing to $q$-ary quadratic residue codes of prime length $p\equiv 3 \pmod 4$ gives an infinite family of pure qLRCs with unbounded minimum distance and certified locality. Finally, by means of concrete computations, we obtain a classification of qLRCs from cyclic, negacyclic, and repeated-root cyclic codes of moderate lengths, which contains the first binary qLRCs from repeated-root cyclic codes and many parameter sets that cyclic codes cannot attain.

cs.IT↗

arXiv2026

Kimi K3: Open Frontier Intelligence

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is built on Kimi Delta Attention and Attention Residuals, which improve information flow across sequence length and model depth. Together with Stable LatentMoE, which effectively activates 16 of 896 routed experts per token, and refined training and data recipes, these advances yield an approximately 2.5x improvement in overall scaling efficiency over Kimi K2. Post-training highlights reinforcement learning across general, agentic, and coding domains and multiple reasoning-effort levels, enabling compositional generalization and robust long-horizon execution. At 2.8T scale, Kimi K3 is supported by infrastructure advances in multiple areas: algorithm-system co-design for KDA, perfectly balanced expert-parallel training with efficient memory management, million-token agentic RL with persistent rollout and sandbox states, and deployment innovations. Extensive evaluations show that Kimi K3 achieves frontier-level performance across long-horizon coding, agentic, knowledge, reasoning, and vision tasks. While its overall performance still trails the most powerful proprietary models, namely Claude Fable 5 and GPT-5.6 Sol, Kimi K3 consistently outperforms other open and proprietary models evaluated in our suite. We release the full Kimi K3 model weights to facilitate future research and accelerate the broader deployment and adoption of frontier intelligence.

cs.CL↗

arXiv2026

Scalable LLM Agent Tool Access in the Cloud

LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scale, however, becomes difficult. On the tool provider side, legacy services are not directly callable through MCP; the rapid protocol development also creates ongoing compatibility cost. On the agent side, the number of accessible tool is limited by the LLM context window and inference overhead; mounting a large tool set increases token usage and inference latency and can reduce task success rate. Moreover, for stateful MCP backends with multiple replicas, preserving session affinity increases client-side complexity. We present a cloud-scale gateway system for MCP service. It breaks the direct-connect model on the data plane and offloads legacy service integration, consolidating incompatible MCP variants, access control, tool recommendation, and session-aware routing to the gateway. Hybrid retrieval sustains 98% Top-15 recall; it scales agent tool access to 3,000+ with high tool selection accuracy, and reduces tool selection time by $8.9\times$ and token usage by $23.8\times$, with low per-call overhead, stable under scale-out. Finally, we share the lessons learned from deploying the gateway system in production.

cs.DC↗

arXiv2026

Quantum Codes from $r$-Nearly Self-Orthogonal Linear Codes via Jordan Canonical Form over $\mathbb{F}_{q^2}$

We introduce a Jordan-canonical-form framework for constructing $q$-ary quantum stabilizer codes from arbitrary classical linear codes over $\F_{q^2}$. The framework does not require the classical linear code $\mathcal{C}$ to satisfy the dual-containing condition (i.e., self-orthogonality). Given a classical code $\mathcal{C}=[n,k,d]_{q^2}$ with parity-check matrix $H$, we measure the obstruction to Hermitian self-orthogonality by the rank $r=(n-k)-\dim_{\F_{q^2}}(\mathcal{C}^{\perp_h}\cap \mathcal{C})$. The ingredient code $\mathcal{C}$ is $r$-nearly dual containing, or, equivalently, $\mathcal{C}^{\perp_h}$ is $r$-nearly self-orthogonal, by which we mean that $r=\Rank(HH^{\dagger})=\dim_{\F_{q^2}}(\mathcal{C}^{\perp_h})-\dim_{\F_{q^2}}(\mathcal{C}^{\perp_h}\cap \mathcal{C})$. By systematically reducing the rank of the Hermitian inner-product matrix $A=HH^{\dagger}$ through rank-one perturbations along the Jordan basis $W=P^{-1}$ of the decomposition $A=PJ_AP^{-1}$, we construct an explicit Hermitian self-orthogonal code $\mathcal{C}_{\mathrm{so}}=[n+r,n-k]_{q^2}$. A sufficient distance-preservation criterion guarantees that the resulting $q$-ary quantum code has parameters $[[n+r,2k-n+r,\geq d]]_q$. Applying this construction to classical codes produces several record quantum codes that improve or supplement the best-known parameters in Grassl's tables.

cs.IT↗

arXiv2026

Integrating Power Electronics-based Energy Storages to Power Systems: A Review on Dynamic Modeling, Analysis, and Future Challenges

The integration of power electronics-based energy storage systems (PEESs) into power systems introduces potential instabilities. This study reviews efforts in dynamic analysis of both AC and DC power systems integrated with PEESs, covering dynamic modeling, analysis methods, and potential instability risks. Major conclusions are drawn as: 1) Simplified models of PEESs have been widely used for dynamic analysis of power systems. However, it may cause "error aggregation" as the scale of PEESs increases, leading to mistakes in results, which induces significant concerns. 2) Traditional stability mechanism analysis methods remain effective for single grid-connected PEES and large-scale PEESs with parallel and series connections. However, they are inadequate for PEESs with distributed connections. To fill in this gap, an idea of mechanism analysis based on "dynamic reconstruction" is proposed. 3) Potential instability risks caused by PEESs integration may differ from those caused by renewable energy integration due to differences in functional controls and bidirectional power flow. However, comprehensive investigations in this regard are lacking and require significant attention. To ensure the stable operation of power systems with increasing integration of PEESs, significant challenges are summarized in the end, providing inspirations for future studies.

eess.SY↗

arXiv2026

Damping Analysis of Subsynchronous Oscillations at the Sending-End of Practical Grid-Forming MTDC Power System for Isolated Renewable Energy

Subsynchronous oscillations (SSOs) have occurred at the sending-end of Zhangbei grid-forming MTDC power system (SE-GFPS). This paper gives an alert for the wide application of grid-forming (GFM) control by presenting a detailed report on such SSOs and the practical GFM configuration. Different from traditional studies that consider only parts of GFM control loops for simplification, power synchronous control (PSC), d- and q-axis AC voltage control (AVC), and inner current control (ICC) loops are comprehensively involved in this study. A self- and coupling-damping method is proposed to quantify the impact of both the inherent dynamics of different GFM control loops and the external dynamic coupling between the GFM control and the remaining SE-GFPS on the SSOs. It determines whether the major causes of SSOs are attributed to inherent GFM dynamics or external dynamic couplings. Based on the damping sensitivity analysis, the major impact factors of the SSOs are identified. Self-damping can be improved more by q-axis than by d-axis AVC parameters, and negative coupling damping can be reduced by PSC parameters. Finally, SSO mitigation strategies are proposed, and an SE-GFPS mirroring the real-world Zhangbei project is established on the electromagnetic transient (EMT) platform in Simulink, validating the accuracy of our conclusions.

eess.SY↗

arXiv2026

Stability Analysis in Large-scale Centralized Bidirectional Inverter-based Stations Connected to Bulk Power Systems through AC and DC Connections

Massive controlled DC resources (CDCRs), such as battery energy storage systems, are connected to AC power systems through bidirectional inverters for power balance requirements. This study investigates converter-driven stability (CDS) issues in the sub-synchronous frequency range caused by large-scale bidirectional inverter-based stations (IBSs). The impacts of the AC and DC connections of IBSs on subsynchronous oscillations (SSOs) are compared by examining three factors: the number of CDCRs, power flow direction, and control parameters of the inverters. For AC connections, IBSs may induce instability as the number of CDCRs increases, regardless of the power flow direction. To maintain stability, the maximum power amplitude of the IBS is calculated. It is found that switching to DC connections can reduce these instability risks if the DC line resistance is much less than the AC line reactance. Moreover, the method of tuning control parameters is demonstrated to be more effective in improving power-related critical stability under DC connections. Therefore, The DC-IBS is preferred for high-voltage transmission. Finally, the conclusions are validated in power systems connected with both AC- and DC-IBSs under various network topologies and system scales.

eess.SY↗

arXiv2026

Instability Caused by Integration of IBRs under Strong Grid Connections -- A Practical Case Study on Large-scale Energy Storage Systems

It has been well known that inverter-based resources (IBRs) can lead to converter-driven stability issues under weak grid connections. However, as the number of IBRs increases, instabilities can also occur even under strong grid connections. A practical case is presented to demonstrate this conclusion, using large-scale energy storage systems (ESSs) as an example. In this study, the ESSs induce oscillations with a frequency of 150 Hz in the d-q coordinates while providing both capacitive and inductive reactive power support (achieved by ESS functional control loops) to the connected power system. Theoretical analysis reveals that under strong grid connections, the dynamic interactions among power conversion systems (PCSs) of ESSs can be superimposed and intensified as the ESS scale extends, which reduces oscillation damping and leads to system instability. This indicates that ESS functional control loops also have potential instability risks when providing supports to power systems, which should be carefully examined. Finally, major impact factors are identified to mitigate the oscillations, and the conclusions are validated based on the SIMULINK platform. This paper provides valuable practical insights into system instabilities even under strong grid conditions, emphasizing the importance of functional control design and careful planning of the scale for IBR-dominated systems.

eess.SY↗

arXiv2026

Dynamic Analysis of Centralized Energy Storage Systems -- A Comparison between Grid-following and Grid-forming Controls

This study investigates the small-signal stability of centralized energy storage systems (CESSs) using grid-following (GFL) and grid-forming (GFM) controls, particularly focusing on bidirectional power flow and multiple energy storage systems (ESSs). To address the issue of complex dynamics in CESSs when comprehensive GFL and GFM control loops are considered, high-order dynamics are simplified using the virtual damping method by focusing on the dominant oscillation mode. Damping analysis verifies that CESSs using a single-type control (either GFL or GFM) have dynamic superimposition characteristics. Specifically, as ESS number increases, the damping of GFM-CESSs improves but that of GFL-CESSs decreases. The damping sensitivity shows that the damping of GFM-CESSs is more sensitive to bidirectional power flow and all control loops, whereas that of GFL-CESSs is more sensitive to d-axis control loop. Consequently, GFM-CESSs are preferred for large-scale integration but are limited in scenarios with significant power reversal. If GFL and GFM controls are hybridized in CESSs, the ratio of GFM-CESSs should be constrained to avoid instability from modal resonance between GFL-CESSs and GFM-CESSs. This highlights that implementing GFM-CESSs necessitates considering scenario limitations rather than pursuing maximal integration under hybrid integration conditions. The conclusions are validated through modal analysis and time-domain simulations.

eess.SY↗

arXiv2026

Accelerated Convex Optimization via Hamiltonian Dynamics with Deterministic Integration Time

We develop Hamiltonian dynamics-based algorithms for smooth convex optimization that achieve accelerated rates of convergence. By exploiting contraction of averaged Hamiltonian flow trajectories rather than requiring contraction at trajectory endpoints, we show that Hamiltonian dynamics-based optimization methods admit deterministic and accelerated convergence guarantees, extending prior work that is limited to quadratic objectives or holds only in expectation. We analyze an idealized continuous-time algorithm and derive practical discrete-time implementations with optimal first-order complexity, thereby establishing Hamiltonian dynamics as a useful algorithmic primitive for deterministic accelerated convex optimization.

math.OC↗

arXiv2026

Multi-pulse accumulation of gas molecular coherence enables gigahertz ultrafast frequency conversion

Frequency conversion of ultrafast lasers is fundamentally constrained by the trade-off between pulse energy and repetition rate, limiting access to regimes critical for fundamental science and industry. Here, we demonstrate a frequency-conversion mechanism in which molecular coherence accumulates across ultrafast pulse trains in gas-filled hollow-core fibers. Unlike conventional nonlinear interactions initiated by individual high-energy pulses, this mechanism relies on the collective buildup of coherent molecular oscillations driven by successive pulses. Using this mechanism, we achieve Raman frequency conversion at repetition rates up to 3 GHz with nanojoule pulse energies. The results establish a regime of nonlinear optical interaction governed by coherence accumulation of gas molecular oscillations with broad implications for ultrafast laser science and frequency conversion technologies.

physics.optics↗

arXiv2026

Quantum current algebra ${\bf U}(\frak{gl}_n[t])$: canonical bases, rigidity, and relation with Yangians

We introduce a quantum deformation $\mathbf{U}(\mathfrak{gl}_n[t])$ of the universal enveloping algebra of the current algebra $\mathfrak{gl}_n[t]$, realized as a parabolic subalgebra of quantum affine $\mathfrak{gl}_n$. Unlike the Yangian -- the standard quantization of the current algebra -- our algebra admits a canonical basis. We give a BLM-type realization of $\mathbf{U}(\mathfrak{gl}_n[t])$ via certain subalgebras of affine quantum Schur algebras, and then construct canonical bases for the modified quantum current algebra $\dot{\mathbf{U}}(\mathfrak{gl}_n[t])$ and for its finite dimensional irreducible graded modules. Moreover, we prove a rigidity theorem: every finite dimensional polynomial irreducible module for quantum affine $\mathfrak{gl}_n$ remains irreducible when restricted to ${\bf U}_{\mathbf v}(\frak{gl}_n[t])$ (the specialization of ${\bf U}(\frak{gl}_n[t])$ at a non-root-of-unity complex number ${\mathbf v}$); conversely, every finite dimensional polynomial irreducible ${\bf U}_{\mathbf v}(\frak{gl}_n[t])$-module extends uniquely to a polynomial irreducible module for quantum affine $\mathfrak{gl}_n$. Consequently, the finite dimensional polynomial irreducible modules of ${\bf U}_{\mathbf v}(\frak{gl}_n[t])$ are in bijection with those of the Yangian $Y(\mathfrak{gl}_n)$. This provides the first example of a quantum current algebra with a well-developed canonical basis theory, providing new combinatorial approaches to the representation theory of current algebras.

math.QA↗

arXiv2026

Kairos: Lightweight Testing Framework for Timing-Induced Interaction Failures in LTE and 5G Core Networks

As cellular core networks evolve toward distributed and cloud-native architectures, control-plane interactions become more intricate and bring new challenges. Among these challenges, we find that introducing specific timing between two control-plane interactions can cause network function crash, which we define as timing-induced interaction failures. Prior research primarily addresses identifying malformed inputs and specification violations, while timing-induced interaction failures remain largely unexplored. In this paper, we conduct a systematic study of timing-induced interaction failures in LTE and 5G core networks. First, we establish a taxonomy of control-plane interaction patterns and analyze the failure modes of each pattern. Then, we design and implement Kairos, a lightweight testing framework to expose timing-induced interaction failures without analyzing cellular standard documents. Evaluating Kairos on two open source and two commercial LTE and 5G core networks, we uncover 20 new vulnerabilities and reproduce 34 existing issues. Our results show that timing-induced interaction failures are prevalent in LTE and 5G core networks and should be explicitly considered in future specifications.

cs.NI↗

arXiv2026

Test Time Training for Supervised Causal Learning

Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from significant out-of-distribution generalization challenges. We reveal three limitations of previous SCL practices: a significant performance gap between synthetic benchmarks and real-world data, fragility to distribution shifts, and failure in compositional generalization, collectively questioning its real-world applicability. To address this, we propose Test-Time Training for Supervised Causal Learning (TTT-SCL), a novel framework that dynamically generates training sets explicitly aligned with any specific test instance. We demonstrate the correlation between TTT-SCL and score-based methods, and design an efficient module for generating training sets based on the classic scoring function. Experiments on synthetic benchmarks, pseudo-real and real-world datasets demonstrate that TTT-SCL significantly outperforms existing SCL and traditional causal discovery methods.

cs.LG↗

arXiv2026

Low Latency Gaze Tracking via Latent Optical Sensing

We present a real-time gaze tracking system that directly acquires task-relevant latent features using a fully passive optical encoder. Instead of forming and processing full-resolution images, our approach leverages a microlens array with a co-designed binary chromium mask to perform spatially multiplexed optical encoding, producing a compact set of measurements sufficient for gaze estimation. By integrating sensing and feature extraction in the optical domain, the proposed system eliminates the need for high-bandwidth image readout and substantially reduces computational overhead. The encoded measurements are captured by a 4 x 4 phototransistor array and mapped to gaze direction using a lightweight neural network. Our proof-of-concept prototype enables an end-to-end sensing-to-inference latency of 3.4 ms, outperforming published research systems. We demonstrate the effectiveness of our approach on both simulated and real-world data, achieving competitive gaze estimation accuracy while significantly improving latency and energy efficiency compared to conventional camera-based pipelines. This work highlights the potential of task-driven optical sensing for ultra-low-latency, computationally efficient human-computer interaction systems.

cs.CV↗

arXiv2026

Ada-MK: Adaptive MegaKernel Optimization via Automated DAG-based Search for LLM Inference

When large language models (LLMs) serve real-time inference in commercial online advertising systems, end-to-end latency must be strictly bounded to the millisecond range. Yet every token generated during the decode phase triggers thousands of kernel launches, and kernel launch overhead alone can account for 14.6% of end-to-end inference time. MegaKernel eliminates launch overhead and inter-operator HBM round-trips by fusing multiple operators into a single persistent kernel. However, existing MegaKernel implementations face a fundamental tension between portability and efficiency on resource-constrained GPUs such as NVIDIA Ada: hand-tuned solutions are tightly coupled to specific architectures and lack portability, while auto-compiled approaches introduce runtime dynamic scheduling whose branch penalties are unacceptable in latency-critical settings. We observe that under a fixed deployment configuration, the optimal execution path of a MegaKernel is uniquely determined, and runtime dynamic decision-making can be entirely hoisted to compile time. Building on this insight, we propose Ada-MK: (1) a three-dimensional shared-memory constraint model combined with K-dimension splitting that reduces peak shared memory usage by 50%; (2) MLIR-based fine-grained DAG offline search that solidifies the optimal execution path, completely eliminating runtime branching; and (3) a heterogeneous hybrid inference engine that embeds MegaKernel as a plugin into TensorRT-LLM, combining high-throughput Prefill with low-latency Decode. On an NVIDIA L20, Ada-MK improves single-batch throughput by up to 23.6% over vanilla TensorRT-LLM and 50.2% over vLLM, achieving positive gains across all tested scenarios--the first industrial deployment of MegaKernel in a commercial online advertising system.

cs.CL↗

arXiv2026

Efficient LLM-based Advertising via Model Compression and Parallel Verification

Large language models (LLMs) have shown remarkable potential in advertising scenarios such as ad creative generation and targeted advertising. However, deploying LLMs in real-time advertising systems poses significant challenges due to their high inference latency and computational cost. In this paper, we propose an Efficient Generative Targeting framework that integrates adaptive group quantization, layer-adaptive hierarchical sparsification, and prefix-tree parallel verification to accelerate LLM inference while preserving generation quality. Extensive experiments on two real-world advertising scenarios demonstrate that our framework achieves significant speedup with acceptable quality degradation, making it operationally viable for practical deployments.

cs.CL↗