With the remarkable empirical success of neural networks across diverse scientific disciplines,rigorous error and convergence analysis are also being developed and enriched.However,there has been little theoretical wo...With the remarkable empirical success of neural networks across diverse scientific disciplines,rigorous error and convergence analysis are also being developed and enriched.However,there has been little theoretical work focusing on neural networks in solving interface problems.In this paper,we perform a convergence analysis of physics-informed neural networks(PINNs)for solving second-order elliptic interface problems.Specifically,we consider PINNs with domain decomposition technologies and introduce gradient-enhanced strategies on the interfaces to deal with boundary and interface jump conditions.It is shown that the neural network sequence obtained by minimizing a Lipschitz regularized loss function converges to the unique solution to the interface problem in H2 as the number of samples increases.Numerical experiments are provided to demonstrate our theoretical analysis.展开更多
Poisson-Nernst-Planck equations are a coupled system of nonlinear partial differential equations consisting of the Nernst-Planck equation and the electrostatic Poisson equation with delta distribution sources,which de...Poisson-Nernst-Planck equations are a coupled system of nonlinear partial differential equations consisting of the Nernst-Planck equation and the electrostatic Poisson equation with delta distribution sources,which describe the electrodiffusion of ions in a solvated biomolecular system.In this paper,some error bounds for a piecewise finite element approximation to this problem are derived.Several numerical examples including biomolecular problems are shown to support our analysis.展开更多
Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poi...Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poisson-Nernst-Planck equations by coarse grid finite element approximations. Both theoretical analysis and numerical experiments show the efficiency and effectiveness of the two-grid algorithms for solving Poisson-Nernst-Planck equations.展开更多
This paper summarizes the mathematical and numerical theories and computational elements of the adaptive fast multipole Poisson-Boltzmann(AFMPB)solver.We introduce and discuss the following components in order:the Poi...This paper summarizes the mathematical and numerical theories and computational elements of the adaptive fast multipole Poisson-Boltzmann(AFMPB)solver.We introduce and discuss the following components in order:the Poisson-Boltzmann model,boundary integral equation reformulation,surface mesh generation,the nodepatch discretization approach,Krylov iterative methods,the new version of fast multipole methods(FMMs),and a dynamic prioritization technique for scheduling parallel operations.For each component,we also remark on feasible approaches for further improvements in efficiency,accuracy and applicability of the AFMPB solver to largescale long-time molecular dynamics simulations.The potential of the solver is demonstrated with preliminary numerical results.展开更多
We propose a direct solver for the three-dimensional Poisson equation with a variable coefficient,and an algorithm to directly solve the associated sparse linear systems that exploits the sparsity pattern of the coeff...We propose a direct solver for the three-dimensional Poisson equation with a variable coefficient,and an algorithm to directly solve the associated sparse linear systems that exploits the sparsity pattern of the coefficient matrix.Introducing some appropriate finite difference operators,we derive a second-order scheme for the solver,and then two suitable high-order compact schemes are also discussed.For a cube containing N nodes,the solver requires O(N^(3/2)log^(2)N)arithmetic operations and O(NlogN)memory to store the necessary information.Its efficiency is illustrated with examples,and the numerical results are analysed.展开更多
基金the National Natural Science Foundation of China(Grant Nos.11771435,22073110 and 12171466).
文摘With the remarkable empirical success of neural networks across diverse scientific disciplines,rigorous error and convergence analysis are also being developed and enriched.However,there has been little theoretical work focusing on neural networks in solving interface problems.In this paper,we perform a convergence analysis of physics-informed neural networks(PINNs)for solving second-order elliptic interface problems.Specifically,we consider PINNs with domain decomposition technologies and introduce gradient-enhanced strategies on the interfaces to deal with boundary and interface jump conditions.It is shown that the neural network sequence obtained by minimizing a Lipschitz regularized loss function converges to the unique solution to the interface problem in H2 as the number of samples increases.Numerical experiments are provided to demonstrate our theoretical analysis.
基金supported by the China NSF(NSFC 11001062,NSFC 11161014)the fund from Education Department of Guangxi Province under grant 201012MS094B.Z.Lu was supported by the National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of Sciences and the China NSF(NSFC10971218).
文摘Poisson-Nernst-Planck equations are a coupled system of nonlinear partial differential equations consisting of the Nernst-Planck equation and the electrostatic Poisson equation with delta distribution sources,which describe the electrodiffusion of ions in a solvated biomolecular system.In this paper,some error bounds for a piecewise finite element approximation to this problem are derived.Several numerical examples including biomolecular problems are shown to support our analysis.
文摘Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poisson-Nernst-Planck equations by coarse grid finite element approximations. Both theoretical analysis and numerical experiments show the efficiency and effectiveness of the two-grid algorithms for solving Poisson-Nernst-Planck equations.
基金supported by NSF,DOE,HHMI,and NIH(B.Z./X.S./N.P.:NSF 0905164,B.Z./J.H.:NSF 0811130 and NSF 0905473,J.A.M.:NSF MCB1020765 and NIH GM31749)the NSF Center of Theoretical Biological Physics(CTBP)partially funded by the Chinese Academy of Sciences,the State Key Laboratory of Scientific/Engineering Computing,and the China NSF(NSFC1097218).
文摘This paper summarizes the mathematical and numerical theories and computational elements of the adaptive fast multipole Poisson-Boltzmann(AFMPB)solver.We introduce and discuss the following components in order:the Poisson-Boltzmann model,boundary integral equation reformulation,surface mesh generation,the nodepatch discretization approach,Krylov iterative methods,the new version of fast multipole methods(FMMs),and a dynamic prioritization technique for scheduling parallel operations.For each component,we also remark on feasible approaches for further improvements in efficiency,accuracy and applicability of the AFMPB solver to largescale long-time molecular dynamics simulations.The potential of the solver is demonstrated with preliminary numerical results.
基金supported by NFS No.11001257,was stimulated by Per-Gunnar Martinsson’s paper”A Fast Direct Solver for a Class of Elliptic Partial Differential Equations”.Professor Jingfang Huang suggested solving the Poisson equation with variable coefficient as a test case.We are very grateful to both of them for their selfless help.
文摘We propose a direct solver for the three-dimensional Poisson equation with a variable coefficient,and an algorithm to directly solve the associated sparse linear systems that exploits the sparsity pattern of the coefficient matrix.Introducing some appropriate finite difference operators,we derive a second-order scheme for the solver,and then two suitable high-order compact schemes are also discussed.For a cube containing N nodes,the solver requires O(N^(3/2)log^(2)N)arithmetic operations and O(NlogN)memory to store the necessary information.Its efficiency is illustrated with examples,and the numerical results are analysed.
