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20062026
most citedNumerical methods for nonlinear Dirac equation

71 citations · 280 across the 32 of their papers we have counts for

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8 papers · 1 filter

math.NA2026

Asymptotic Recovery in Fourier Spectral Methods for the Schrödinger Equation with Point Singularities

Yanjie Li, Sihong Shao

This paper studies the Fourier spectral method (FSM) for the Schrödinger equation with singular potentials , where and denotes the spatial d…

math.NA2026

An Adaptive Log-Laguerre Spectral Method for the Radial Dirac Equation: Resolving Asymptotic Decay and Core Singularities in Atomic Calculations

Sheng Chen, Sihong Shao, Shuai Wu

The high-precision solution of the radial Dirac equation is fundamental to relativistic quantum chemistry, essential for reliable pseudopotential generation and all-electron electr…

math.NA2022

Performance evaluations on the parallel CHAracteristic-Spectral-Mixed (CHASM) scheme

Yunfeng Xiong, Yong Zhang, Sihong Shao

Performance evaluations on the deterministic algorithms for 6-D problems are rarely found in literatures except some recent advances in the Vlasov and Boltzmann community [Dimarco…

math.NA2022

Adaptive Hermite Spectral Methods in Unbounded Domains

Tom Chou, Sihong Shao, Mingtao Xia

Recently, new adaptive techniques were developed that greatly improved the efficiency of solving PDEs using spectral methods. These adaptive spectral techniques are especially suit…

math.NA2020★ 1 cited

A frequency-dependent -adaptive technique for spectral methods

Mingtao Xia, Sihong Shao, Tom Chou

When using spectral methods, a question arises as how to determine the expansion order, especially for time-dependent problems in which emerging oscillations may require adjusting…

math.NA2020★ 6 cited

Efficient Scaling and Moving Techniques for Spectral Methods in Unbounded Domains

Mingtao Xia, Sihong Shao, Tom Chou

When using Laguerre and Hermite spectral methods to numerically solve PDEs in unbounded domains, the number of collocation points assigned inside the region of interest is often in…