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Fast adaptive discontinuous basis sets for electronic structure.
Y. Pan and M. Lindsey, arXiv preprint (2025). [arXiv] -
Geometric adaptive smoothed aggregation multigrid for discontinuous Galerkin discretisations.
Y. Pan, M. Lindsey and P.-O. Persson, arXiv preprint (2025). [arXiv] -
Optimization of a triangular Delaunay mesh generator using reinforcement learning.
W. Thacher, Y. Pan and P.-O. Persson, Computer-Aided Design, 103964 (2025). [journal] [arXiv] -
Half-closed discontinuous Galerkin discretisations.
Y. Pan and P.-O. Persson, J. Comp. Phys., Vol. 524, 113731, (2025). [journal] [arXiv] -
Learning topological operations on meshes with application to block decomposition of polygons.
A. Narayanan, Y. Pan and P.-O. Persson, Computer-Aided Design, 103744, (2024). [journal] [arXiv] -
A face-upwinded spectral element method.
Y. Pan and P.-O. Persson, J. Comp. Phys., Vol. 503, 112825, (2024). [journal] [arXiv] -
High-order accurate finite difference discretisations on fully unstructured dual quadrilateral meshes.
Y. Pan and P.-O. Persson, J. Comp. Phys., Vol. 461, 111201, (2022). [journal] [arXiv] -
Agglomeration-based geometric multigrid solvers for compact discontinuous Galerkin discretisations on unstructured meshes.
Y. Pan and P.-O. Persson, J. Comp. Phys., Vol. 449, 110775, (2022) [journal] [arXiv]
About
I am a graduate student in Applied Mathematics at UC Berkeley working with Prof. Per-Olof Persson and Prof. Michael Lindsey. My research is broadly focused on developing fast numerical algorithms for solving partial differential equations.
I am applying to postdoc positions starting Fall 2026. Here is my CV.
Publications
Selected presentations
Code
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adaptiveMG: Adaptive multigrid for Discontinuous Galerkin discretisations. Can handle scalar equations (e.g. Poisson, advection) using different fluxes including Interior Penalty, Local Discontinuous Galerkin and more. Code available on Github.
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dgSCF: Discontinuous Galerkin basis sets for SCF calculations. Basic functionality includes Hartree-Fock and density functional theory implementations. Code available on Github.
Teaching
- Fall 2021: Math 1A, Calculus
- Spring 2022: Math 124, Programming for Mathematics
- Fall 2022: Math 54, Linear Algebra
- Fall 2023: Math 221, Numerical Linear Algebra
- Fall 2023: Math 126, Partial Differential Equations
- Summer 2023: Math 128A, Numerical Analysis
- Fall 2024: Math 128A, Numerical Analysis
- Fall 2025: Math 170, Mathematical Methods for Optimisation