An efficient spectral trust-region deflation method for multiple solutions
It is quite common that a nonlinear partial differential equation (PDE) admits multiple distinct solutions and each solution may carry a unique physical meaning. One typical approach for finding multiple solutions is to use the Newton method with different initial guesses that ideally fall into the...
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sg-ntu-dr.10356-1689832023-06-26T04:16:54Z An efficient spectral trust-region deflation method for multiple solutions Li, Lin Wang, Li-Lian Li, Huiyuan School of Physical and Mathematical Sciences Science::Mathematics Multiple Solutions Trust-Region Method It is quite common that a nonlinear partial differential equation (PDE) admits multiple distinct solutions and each solution may carry a unique physical meaning. One typical approach for finding multiple solutions is to use the Newton method with different initial guesses that ideally fall into the basins of attraction confining the solutions. In this paper, we propose a fast and accurate numerical method for multiple solutions comprised of three ingredients: (i) a well-designed spectral-Galerkin discretization of the underlying PDE leading to a nonlinear algebraic system (NLAS) with multiple solutions; (ii) an effective deflation technique to eliminate a known (founded) solution from the other unknown solutions leading to deflated NLAS; and (iii) a viable nonlinear least-squares and trust-region (LSTR) method for solving the NLAS and the deflated NLAS to find the multiple solutions sequentially one by one. We demonstrate through ample examples of differential equations and comparison with relevant existing approaches that the spectral LSTR-Deflation method has the merits: (i) it is quite flexible in choosing initial values, even starting from the same initial guess for finding all multiple solutions; (ii) it guarantees high-order accuracy; and (iii) it is quite fast to locate multiple distinct solutions and explore new solutions which are not reported in literature. Ministry of Education (MOE) L. Li: This work of this author is partially supported by the Science Foundations of Hunan Province (Nos: 2020JJ5464, 20C1595). L-L. Wang: The research of this author is partially supported by Singapore MOE AcRF Tier 1 Grant: RG15/21. 2023-06-26T04:16:54Z 2023-06-26T04:16:54Z 2023 Journal Article Li, L., Wang, L. & Li, H. (2023). An efficient spectral trust-region deflation method for multiple solutions. Journal of Scientific Computing, 95(1). https://dx.doi.org/10.1007/s10915-023-02154-0 0885-7474 https://hdl.handle.net/10356/168983 10.1007/s10915-023-02154-0 2-s2.0-85150200882 1 95 en RG15/21 Journal of Scientific Computing © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. |
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Science::Mathematics Multiple Solutions Trust-Region Method Li, Lin Wang, Li-Lian Li, Huiyuan An efficient spectral trust-region deflation method for multiple solutions |
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It is quite common that a nonlinear partial differential equation (PDE) admits multiple distinct solutions and each solution may carry a unique physical meaning. One typical approach for finding multiple solutions is to use the Newton method with different initial guesses that ideally fall into the basins of attraction confining the solutions. In this paper, we propose a fast and accurate numerical method for multiple solutions comprised of three ingredients: (i) a well-designed spectral-Galerkin discretization of the underlying PDE leading to a nonlinear algebraic system (NLAS) with multiple solutions; (ii) an effective deflation technique to eliminate a known (founded) solution from the other unknown solutions leading to deflated NLAS; and (iii) a viable nonlinear least-squares and trust-region (LSTR) method for solving the NLAS and the deflated NLAS to find the multiple solutions sequentially one by one. We demonstrate through ample examples of differential equations and comparison with relevant existing approaches that the spectral LSTR-Deflation method has the merits: (i) it is quite flexible in choosing initial values, even starting from the same initial guess for finding all multiple solutions; (ii) it guarantees high-order accuracy; and (iii) it is quite fast to locate multiple distinct solutions and explore new solutions which are not reported in literature. |
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School of Physical and Mathematical Sciences |
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School of Physical and Mathematical Sciences Li, Lin Wang, Li-Lian Li, Huiyuan |
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Article |
author |
Li, Lin Wang, Li-Lian Li, Huiyuan |
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Li, Lin |
title |
An efficient spectral trust-region deflation method for multiple solutions |
title_short |
An efficient spectral trust-region deflation method for multiple solutions |
title_full |
An efficient spectral trust-region deflation method for multiple solutions |
title_fullStr |
An efficient spectral trust-region deflation method for multiple solutions |
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An efficient spectral trust-region deflation method for multiple solutions |
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efficient spectral trust-region deflation method for multiple solutions |
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2023 |
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https://hdl.handle.net/10356/168983 |
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1772826261478965248 |