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Xiuping Wang

About Xiuping Wang

KAUST-AMCS-SCML-Xiuping-Wang

Xiuping Wang

  • Ph.D. Student, Applied Mathematics and Computational Science

Events

Presented Events

Nov 17 - Nov 23, 2024

  • KAUST-CEMSE-AMCS-PhD-Dissertation-Defense-Xiuping-Wang

    Efficient and Structure-Preserving Numerical Schemes for Kohn-Sham Gradient Flow Models

    Xiuping Wang, Ph.D. Student, Applied Mathematics and Computational Science
    Nov 20, 09:00 - 10:00

    B4, L5, R5220

    This dissertation presents efficient and structure-preserving numerical schemes for calculating the electronic structure via the Kohn-Sham density functional theory (DFT) and gradient flow models. The efficiency relies on the numerical scheme’s unconditional energy stability, orbital-wise splitting design, and linearity. The structure-preserving property refers to both energy stability and orthonormality-preserving. The corresponding theoretical analysis is rigorously conducted and presented. Various numerical examples are performed to show the schemes’ effectiveness and robustness.

Related Sites

  • Scientific Computing and Machine Learning (SCML)
  • Computational Transport Phenomena Lab (CTPL)

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Applied Mathematics and Computational Science (AMCS)

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