arXiv subjects

Kai Jiang

Publications and source records attributed to Kai Jiang.

At least 19 recordsLinked to original sources

arXiv2026

Equivalence of superintegrable Poisson projection chains: magnetic cotangent bundles and spin Calogero-Moser models

We study superintegrable Hamiltonian systems in terms of Poisson projection chains and their (spectral) equivalence. We compare two reduction constructions: (i) the cotangent bundle $T^*(G/A)$, $A=Z_G(γ)$, with the magnetic symplectic form defined by the orbit $G\cdot γ\cong G/A$, and (ii) the left-right Hamiltonian reduction of $T^*G$ that gives spin Calogero-Moser type systems. We prove that the two resulting chains are equivalent on an open set of regular points of principal orbit type: the phase spaces, the intermediate Poisson manifolds and the base spaces are identified compatibly with the projections. In particular, both constructions give the same commuting Hamiltonians.

math-ph↗

arXiv2026

Structure and energetics of grain boundaries in self-assembled double-gyroid block copolymer networks

Grain boundaries (GBs) are ubiquitous defects in crystalline materials, but remain less explored in block copolymer ordered phases. Here, we develop a self-consistent field theory framework to investigate GB structure and energetics in double-gyroid (DG) diblock copolymer networks. Two energy landscapes are obtained for tilt and twist GBs as functions of GB orientations revealing multiple local minima. The lowest-energy GB among the sampled GBs is an asymmetric-tilt network-switching GB ($[\bar{1}\bar{1}1]$ ATNS) rather than the experimentally observed $(422)$ twin boundary (TB) among the sampled GBs. Comparative analyses of tilt ($[\bar{1}\bar{1}1]$, $[100]$ ATNS) and twist ($(422)$ TB, $[0\bar{1}\bar{1}]$ TNS) GBs reveal that, unlike enthalpy-dominated hard matter, GB stability in DG networks is entropy-driven. Twist-type GBs generate new nodes and disrupt nodal coplanarity, causing chain-packing frustration and entropy penalties. Although the [100] ATNS does not generate new nodes, its disruption of nodal coplanarity still incurs large entropy penalties. Conversely, the $[\bar{1}\bar{1}1]$ ATNS preserves favorable network connectivity and minimizes conformational constraints, making it the energetically preferred GB.

cond-mat.soft↗

arXiv2026

SLA2: Sparse-Linear Attention with Learnable Routing and Quantization-aware Training

Sparse-Linear Attention (SLA) combines sparse and linear attention to accelerate diffusion models and has shown strong performance in video generation. However, (i) SLA relies on a heuristic split that assigns computations to the sparse or linear branch based on attention-weight magnitude, which can be suboptimal. Additionally, (ii) after formally analyzing the attention error in SLA, we identify a mismatch between SLA and a direct decomposition into sparse and linear attention. We propose SLA2, which introduces (I) a learnable router that dynamically selects whether each attention computation should use sparse or linear attention, (II) a more faithful and direct sparse-linear attention formulation that uses a learnable ratio to combine the sparse and linear attention branches, and (III) a sparse + low-bit attention design, where low-bit attention is introduced via quantization-aware fine-tuning to reduce quantization error. Experiments show that on video diffusion models, SLA2 can achieve 97% attention sparsity and deliver an 18.6x attention speedup while preserving generation quality.

cs.LG↗

arXiv2026

SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning

Many training-free sparse attention methods are effective for accelerating diffusion models. Recently, several works suggest that making sparse attention trainable can further increase sparsity while preserving generation quality. We study three key questions: (1) when do the two common masking rules, i.e., Top-k and Top-p, fail, and how can we avoid these failures? (2) why can trainable sparse attention reach higher sparsity than training-free methods? (3) what are the limitations of fine-tuning sparse attention using the diffusion loss, and how can we address them? Based on this analysis, we propose SpargeAttention2, a trainable sparse attention method that achieves high sparsity without degrading generation quality. SpargeAttention2 includes (i) a hybrid masking rule that combines Top-k and Top-p for more robust masking at high sparsity, (ii) an efficient trainable sparse attention implementation, and (iii) a distillation-inspired fine-tuning objective to better preserve generation quality during fine-tuning using sparse attention. Experiments on video diffusion models show that SpargeAttention2 reaches 95% attention sparsity and a 16.2x attention speedup while maintaining generation quality, consistently outperforming prior sparse attention methods.

cs.CV↗

arXiv2026

PhyAVBench: A Challenging Audio Physics-Sensitivity Benchmark for Physically Grounded Text-to-Audio-Video Generation

Text-to-audio-video (T2AV) generation is central to applications such as filmmaking and world modeling. However, current models often fail to produce physically plausible sounds. Previous benchmarks primarily focus on audio-video temporal synchronization, while largely overlooking explicit evaluation of audio-physics grounding, thereby limiting the study of physically plausible audio-visual generation. To address this issue, we present PhyAVBench, the first benchmark that systematically evaluates the audio-physics grounding capabilities of T2AV, image-to-audio-video (I2AV), and video-to-audio (V2A) models. PhyAVBench offers PhyAV-Sound-11K, a new dataset of 25.5 hours of 11,605 audible videos collected from 184 participants to ensure diversity and avoid data leakage. It contains 337 paired-prompt groups with controlled physical variations that drive sound differences, each grounded with an average of 17 videos and spanning 6 audio-physics dimensions and 41 fine-grained test points. Each prompt pair is annotated with the physical factors underlying their acoustic differences. Importantly, PhyAVBench leverages paired text prompts to evaluate this capability. We term this evaluation paradigm the Audio-Physics Sensitivity Test (APST) and introduce a novel metric, the Contrastive Physical Response Score (CPRS), which quantifies the acoustic consistency between generated videos and their real-world counterparts. We conduct a comprehensive evaluation of 17 state-of-the-art models. Our results reveal that even leading commercial models struggle with fundamental audio-physical phenomena, exposing a critical gap beyond audio-visual synchronization and pointing to future research directions. We hope PhyAVBench will serve as a foundation for advancing physically grounded audio-visual generation. Prompts, ground-truth, and generated video samples are available at https://github.com/imxtx/PhyAVBench.

cs.SD↗

arXiv2026

Accurately computing quasiperiodic parabolic equations within finite-size domains via modeling quasiperiodic boundary conditions

Quasiperiodic parabolic equations (QPEs) describe various physical processes in systems with long-range order without decay, such as heat conduction, diffusion, and transport, and are naturally posed on the whole space. However, practical computations could be performed on finite domains, where preserving the global quasiperiodic structure through appropriate boundary conditions remains a key challenge. Traditional periodic boundary conditions (PBCs) cannot capture quasiperiodic information beyond the computational domain and suffer from Diophantine errors caused by rational approximations of irrational numbers. To address this issue, we propose a class of quasiperiodic boundary conditions (QBCs) based on a homomorphism between the physical domain and a high-dimensional torus, enabling the long-range quasiperiodic structure to be captured at the boundaries. We further establish rigorous convergence results for numerical discretizations of finite-size QPEs with QBCs. Numerical experiments demonstrate that QBCs avoid the influence of Diophantine errors and enable accurate and efficient computations for both high- and low-regularity cases, with improved convergence over PBCs.

math.NA↗

arXiv2026

Irrationality exponents of logarithms of positive rational numbers

We study rational approximation to logarithms of positive rational numbers and give a separated-weight determinant argument for $μ(\log r)=2$ whenever $r\in\mathbb Q_{>0}\setminus\{1\}$. The geometric input is an interpolation theorem for logarithmic jets at points with distinct multiplicative coordinates. Its successive weight thresholds are independent of the interpolation centres; the eventual degree threshold may depend on them. A local intersection-length bound and a curve inequality lead to surjectivity through a blow-up and Serre vanishing. For a fixed rational argument, this produces a nonzero rational determinant. Clearing denominators gives an arithmetic lower bound, while an exact row translation and repeated Taylor indices yield a contradictory analytic upper bound. The consequences include nonzero rational linear combinations of such logarithms, rational affine changes, and logarithms of positive numbers with a rational positive integer power. We also give a bounded-fibre interpolation extension, an explicit bound for the final analytic degree, and a counterexample to interpolation under the volume condition alone.

math.NT↗

arXiv2026

Mathematical foundation of symmetric fast Fourier transform

In this work, we study the fast Fourier transform (FFT) of discrete data with crystallographic symmetry, for which standard FFT algorithms incur substantial redundant computation. We establish a rigorous mathematical theory of the symmetric fast Fourier transform (SFFT) for $n$-dimensional crystallographic groups and propose the SFFT and symmetric inverse fast Fourier transform (SIFFT) algorithms. We derive symmetry-reduction formulas for both linear and translational symmetries and unify them into a recursive framework. We analyze the arithmetic complexity to obtain theoretical speedup factors relative to the standard FFT, and we confirm the accuracy and efficiency of the proposed methods by numerical experiments on representative three-dimensional space groups.

math.NA↗

arXiv2026

A High-Accuracy Numerical Homogenization Method for Quasiperiodic Hamilton--Jacobi Equations

In this work, we develop an accurate numerical homogenization method for computing effective Hamiltonians of quasiperiodic Hamilton--Jacobi equations (QHJEs) with convex Hamiltonians of the form $H(x,p) = |p|^k/{k}-f(x), ~k>1$, where $f$ is quasiperiodic. Computing effective Hamiltonians in the quasiperiodic setting requires solving QHJEs posed on the whole space. Their solutions generally possess neither translational symmetry nor decay and may exhibit low regularity. These features pose substantial challenges for numerical computation. To address these difficulties, we introduce a quasiperiodic boundary condition, which allows the original whole-space problem to be treated on a bounded domain while preserving quasiperiodicity at the boundary. We then propose an SL--FPR scheme that combines a semi-Lagrangian (SL) approximation with the finite points recovery (FPR) method and establish stability and error estimates for the resulting scheme. We also extend the quasiperiodic homogenization result from the quadratic case to general $k>1$ and apply the proposed method to accurately approximate the corresponding effective Hamiltonians. Numerical experiments illustrate the convergence and applicability of the method and validate the extended homogenization results.

math.NA↗

arXiv2026

Minimum energy paths for defect annihilation in finite dodecagonal quasicrystal clusters

Defect repair in quasicrystals involves local structural rearrangements on a complex potential energy landscape. Here, we combine the string method with the spring pair method to compute a minimum energy path connecting a locally defective finite dodecagonal quasicrystal cluster to a locally repaired reference configuration in the Lennard-Jones--Gauss particle model. The computed path contains seven local minima connected through six transition states. A detailed analysis of one defective region resolves three successive stages: a phason flip, aggregation of neighboring shield-like defects, and decomposition of the aggregated motif. The phason flip restores the local outer-ring structure and relocates a shield-like defect into the interior. Subsequent collective rearrangements remove the defective motifs and yield a net decrease in the local interaction-energy measure together with an increase in local bond-orientational order. These results provide a microscopic description of a specific defect-repair pathway on the potential energy surface of a finite dodecagonal quasicrystal cluster.

cond-mat.mtrl-sci↗

arXiv2026

Nucleation and phase transition of spherical crystals and quasicrystals

We investigated the nucleation, growth, and solid-to-solid phase transition processes of spherical six-fold symmetric crystals (C6) and ten-fold symmetric quasicrystals (DQC) using the Lifshitz-Petrich model. By combining the spherical-harmonic pseudospectral method with a nullspace-preserving saddle-point search technique, we resolved the critical nucleus structures and phase transition pathways. Although both transitions from the homogeneous state to the ordered state involve the formation of localized critical nuclei, their subsequent growth processes exhibit distinct modes of accommodating geometric mismatch: C6 forms branched domain structures and persistent line defects associated with orientation and phase mismatches, whereas DQC relaxes collision-induced defects through local coordination rearrangements. The resolved DQC-to-C6 pathway proceeds through a series of metastable intermediates that progressively connect these distinct modes of mismatch accommodation. Its multi-step character reflects the coupled adjustment of local coordination and compatibility between the emerging C6 domains. These results reveal the intrinsic link between the multi-step nature of the phase transition and the distinct structural requirements for accommodating geometric mismatch.

cond-mat.soft↗

arXiv2026

SEmoEdit: Probing and Harnessing the Editability of Pre-trained Speech Flows

Existing training-based speech emotion editing methods often require substantial task-specific training and can be unstable. This motivates us to investigate whether the pretrained generative dynamics of large-scale text-to-speech (TTS) models can be directly manipulated for training-free emotion editing. To answer this question, we probe the editability of pretrained flow-matching and hybrid TTS models by constructing a controlled test set and systematically diagnosing editing effects along the generative trajectory. Our analysis reveals that pretrained TTS models are substantially editable in emotion, but such editability is architecture- and trajectory-dependent and can be disrupted by early flow-matching steps, while cross-speaker emotion transport carries additional acoustic attributes beyond emotion. To address these limitations, we propose SEmoEdit, the first training-free framework that formulates emotion editing as dynamic velocity transport between source and target emotions, enabling robust, flow-based speech emotion editing directly within pretrained TTS models. SEmoEdit unifies three core operations: emotion replacement, emotion erasure, and continuous emotion interpolation, requiring neither parameter updates nor task-specific optimization. To systematically evaluate these capabilities, we introduce SEmoEditBench, a dataset comprising 600 editing cases, and conduct extensive experiments across state-of-the-art (SOTA) models and backbones. Our results show that SEmoEdit is highly effective and broadly applicable, outperforming existing training-based and activation-steering methods. Ultimately, this work reveals that pretrained speech flows possess rich, latent emotion-editing capabilities, providing useful guidance for real applications. Code, benchmark, and Audio samples are available at https://github.com/imxtx/SEmoEdit.

cs.SD↗

arXiv2026

Investigation of Hopping Conduction and Its Impact on the Subthreshold and Transition Region Transport in Oxide Semiconductor Transistors by Magneto-Transport Measurements

In this work, magneto-transport measurements, including Hall effects and magnetoresistance (MR) at various temperatures, are employed to directly probe the electron transport properties in crystalline indium oxide (In2O3) and amorphous indium-zinc oxide (IZO) transistors. For the first time, we develop a subgap density of states (DOS) extraction method based on the MR measurements at low temperature, considering both the interference and orbital shrinkage effects. The sign and magnitude of MR are used as direct evidence to distinguish the dominating transport mechanisms between hopping conduction and free-electron conduction. It is found that crystalline In2O3 exhibits a subgap DOS more than two orders of magnitude lower than that of amorphous IZO, together with a smaller localization radius of hopping sites. As a result, crystalline In2O3 not only enhances the carrier mobility but also significantly reduces the supply voltage (VDD) because of the smaller transition region enabled by the much-suppressed subgap DOS. This study reveals that structural disorder critically influences the device operation in the subthreshold and transition regions of oxide semiconductor transistors.

cond-mat.mtrl-sci↗

arXiv2026

Demonstrate of High-Performance Top-Gate ALD Crystalline In2O3 Transistor Enabled by Lattice-Matched HfO2 and In2O3 Heterostructure

In this work, we demonstrate high-mobility top-gate (TG) atomic-layer-deposited (ALD) crystalline In2O3 transistors through simultaneous interface and crystallinity engineering. First, a HfO2/In2O3/HfO2 stack is employed, enabling epitaxial-like crystallization of the ultrathin In2O3 channel, because of the lattice matching between monoclinic phase HfO2 and cubic phase In2O3. Second, an oxygen-rich gate insulator process is applied using high-dose O3 precursor and elevated deposition temperature, effectively suppressing oxygen scavenging during gate dielectric deposition, significantly reducing interfacial defect formation. Third, the homogeneous In-O bonding network in crystalline In2O3 exhibits substantially enhanced resistance to oxygen scavenging by source/drain contacts, which significantly improves the immunity to threshold voltage (VTH) roll-off at short channel length compared to amorphous In2O3. As a result, high-performance TG long-channel In2O3 transistors are achieved with a high mobility of 163 cm2/V s and a steep subthreshold slope of 64 mV/dec. High-performance TG short-channel In2O3 transistors with high ION of 1650 μA/μm at VD of 1 V, large on/off ratio over 1010 and VTH of -0.27 V are demonstrated. These results establish lattice-engineered crystalline In2O3 as an effective strategy for high-mobility, aggressively scaled TG oxide transistors suitable for BEOL-compatible applications.

cond-mat.mtrl-sci↗

arXiv2026

High-Performance Scaled P-Type SnOx Transistor by Atomic Layer Deposition with CFET Integration

The development of high-performance p-type oxide semiconductors is essential for realizing complementary logic for monolithic 3D integration, yet p-type oxide semiconductors still exhibit substantially inferior performance compared with their n-type counterparts. In this work, we demonstrate high-performance p-type SnOx transistors by atomic layer deposition (ALD), as back-end-of-line compatible devices for monolithic 3D integration. The SnOx transistors exhibit high field-effect mobility of 6.9 cm2/Vs, low subthreshold swing (SS) of 185 mV/dec, decent on/off ratio (ION/IOFF) of 1.8*104 and high bias stability. By scaling the channel length down to 80 nm, a high on-current of 38.7 mA/mm at VDS of -1 V is achieved. It is understood that precursor and reaction engineering to suppress Sn4+ component in SnOx film are the key for performance enhancement. Furthermore, a complementary field-effect transistor with ALD SnOx p-FET vertically stacking on ALD In2O3 n-FET is also demonstrated, achieving maximum voltage gain of 21 V/V at VDD of 4 V. These findings suggest ALD SnOx as a promising candidate for scaled high-performance BEOL p-type transistors.

cond-mat.mtrl-sci↗

arXiv2026

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. Moreover, we explore the feasibility of real-time spatial video generation for both Vidu S2-Avatar and Vidu S2-Editing. Compared with Vidu S1, Vidu S2-Avatar supports real-time 720p video generation, generation with dynamic references that can be updated at any moment, and stronger instruction following, such as dancing. Vidu S2-Editing supports editing a video stream in real time, including style rendering, clothing replacement, character replacement, and background replacement. Experiments show that Vidu S2 outperforms all baselines. A playable online demo is available at https://vidu.com/vidu-stream.

cs.CV↗

arXiv2026

TurboT2VA: Fast Large-Scale Text-to-Video-Audio Generation via Score-Regularized Consistency Distillation

Joint text-to-video-audio generation produces synchronized visual and acoustic content, but the long sampling trajectories and heterogeneous multimodal computation of large models make inference prohibitively expensive. We present TurboT2VA, a distillation and inference framework for accelerating a 19B-parameter joint video-audio model. Large-scale T2VA distillation is challenged by modality-imbalanced optimization, the difficulty of continuous-time consistency training at scale, and the quality--diversity trade-off. TurboT2VA addresses these issues with per-modality normalization and a progressive curriculum comprising discrete consistency warm-up, continuous consistency refinement, and joint consistency--distribution matching. The curriculum first establishes a stable, diverse generation trajectory and only then introduces distribution-level refinement. On LTX-2, four-step distillation reduces generator latency from 50.52s to 2.51s at the standard evaluation resolution of 512$\times$768, achieving a 20.1$\times$ speedup while maintaining strong visual quality, audio fidelity, diversity, and video-audio synchronization. We further develop an architecture-aware inference stack that combines guarded W8A8 and fused operators, padded-text compaction, and modality-aware sparse attention while preserving dense cross-modal and text-conditioning paths. Under the high-resolution deployment setting at 1024$\times$1792, the complete stack reduces generator latency from 318.74s to 5.83s on one NVIDIA H20, achieving a 54.67$\times$ generator-only speedup. Inference code and generation demos are available at https://github.com/thu-ml/TurboDiffusion/tree/main/turbot2va.

cs.CV↗

arXiv2026

Regional Frequency Constrained Dispatch Method Considering Spatial-joint Stochastic Disturbances and Contingencies

The increasing penetration of renewable energy challenges frequency stability due to high variability and declining inertia. Traditional frequency security constrained dispatch methods fail to capture regional frequency heterogeneity and spatially correlated stochastic disturbances, resulting in inaccurate frequency security enforcement. To address this, a regional frequency constrained dispatch method is proposed, considering the spatially joint stochastic disturbances and contingencies. Firstly, a multi-regional frequency response model is constructed, incorporating the Vine-Copula based characterization of regional stochastic disturbances and regional frequency support. Then, a progressive latent-bottleneck physics-informed neural network is applied to characterize differential frequency nadir terms and regional frequency support integral terms via an encoder-decoder architecture, which enables optimization compatible expressions of system frequency dynamics. Finally, a day ahead dispatch model is developed in which regional stochastic frequency constraints are embedded using a CVaR-based formulation. A case study on the IEEE 118-bus system shows that the proposed method outperforms the unified center of inertia embedded approach in mitigating regional frequency violations, with the regional frequency nadir and RoCoF improved by 32.76% and 2.06%, respectively.

eess.SY↗