14 papers
SPEAR: A Spectral-Disentangled MoE Neural Operator with Knowledge-Guided Expert Aggregation for Large-Scale PDE Pretraining
Dengdi Sun, Xiaoya Zhou, Xiao Wang +3
Large-scale pre-training has improved the generalization of neural operators across diverse PDEs. However, existing PDE foundation models still struggle with heterogeneous dynamics…
Nuclear Fusion Knowledge Graph Guided Edge-Localized Mode Recognition on EAST
Wanli Lyu, Laiqi Qian, Xiao Wang +5
Edge-localized modes (ELMs) are transient magnetohydrodynamic instabilities commonly observed in tokamak plasmas. Although deep time-series models can learn complex dynamic pattern…
Fusing Global Diagnostic Signals and Spectral Data for Electron and Ion Temperature Profile Prediction on EAST via Attention-based Neural Networks
Xiao Wang, Jiangtao Yu, Zichao Lin +6
Ion temperature Ti and electron temperature Te are fundamental kinetic parameters for evaluating tokamak plasma confinement, turbulent transport and magnetohydrodynamic stability.…
FusionMMT: A Unified Multimodal and Multitask Learning Framework for Nuclear Fusion
Qiang Chen, Xiao Wang, Qingquan Yang +5
With the growing global demand for energy, nuclear fusion has emerged as a promising direction for future clean energy. Tokamaks represent one of the leading approaches to magnetic…
SafeDivertor: Faithful Divertor Heat Flux Reconstruction from Macroscopic Plasma State Signals via Time-Frequency Prior Exploitation
Hao Si, Zehua Chen, Qingquan Yang +8
Divertor heat-flux analysis is essential for understanding plasma-wall interactions and protecting plasma-facing components in magnetic-confinement fusion devices, while convention…
Physics-Informed Neural Networks for Complex Eigenfrequency Identification and Mode Structure Reconstruction of the Ground-State ITG Branch
Dengdi Sun, Bingbing Zhang, Xiao Wang +5
Physics-informed neural networks (PINNs) combine sparse observations with physical equations, providing an important approach for modeling complex plasma processes and inferring un…
Visible-Light Imaging Diagnosis of Neutral Particle Emission Tomography in the Tokamak Divertor: An Efficient Transformer-based Surrogate Model
Xiao Wang, Hao Si, Qiang Chen +8
Nuclear fusion has made significant progress in recent years and is expected to become one of the most important pathways to addressing global energy challenges. This paper focuses…
Hierarchical Multi-to-Single-Modal Knowledge Distillation for Disruption Prediction in EAST
Qiang Chen, Xiao Wang, Hao Si +9
Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible images provide complementary…
Temperature Field Reconstruction of Tungsten Monoblock Divertor on EAST using Physics-aware Neural Operator Transformer
Zikang Yan, Xiao Wang, Qingquan Yang +6
Accurate modeling of the divertor temperature field is essential for preventing material melting and damage and for extending the service life of fusion devices. However, conventio…
UniPINN: A Unified PINN Framework for Multi-task Learning of Diverse Navier-Stokes Equations
Dengdi Sun, Jie Chen, Xiao Wang +1
Physics-Informed Neural Networks (PINNs) have shown promise in solving incompressible Navier-Stokes equations, yet existing approaches are predominantly designed for single-flow se…
NESTOR: A Nested MOE-based Neural Operator for Large-Scale PDE Pre-Training
Dengdi Sun, Xiaoya Zhou, Xiao Wang +4
Neural operators have emerged as an efficient paradigm for solving PDEs, overcoming the limitations of traditional numerical methods and significantly improving computational effic…
EMRRG: Efficient Fine-Tuning Pre-trained X-ray Mamba Networks for Radiology Report Generation
Mingzheng Zhang, Jinfeng Gao, Dan Xu +5
X-ray image-based medical report generation (MRG) is a pivotal area in artificial intelligence that can significantly reduce diagnostic burdens for clinicians and patient wait time…
Revisiting Heat Flux Analysis of Tungsten Monoblock Divertor on EAST using Physics-Informed Neural Network
Xiao Wang, Zikang Yan, Hao Si +5
Estimating heat flux in the nuclear fusion device EAST is a critically important task. Traditional scientific computing methods typically model this process using the Finite Elemen…
HGTS-Former: Hierarchical HyperGraph Transformer for Multivariate Time Series Analysis
Hao Si, Xiao Wang, Fan Zhang +5
Multivariate time series analysis has long been one of the key research topics in the field of artificial intelligence. However, analyzing complex time series data remains a challe…