What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Algebra
- Numerical analysis
The scientist’s investigation covers issues in Iterative method, Finite element method, Numerical analysis, Mathematical analysis and Eigenvalues and eigenvectors.
His Iterative method research incorporates elements of Conjugate gradient method, System of linear equations and Applied mathematics.
His Applied mathematics course of study focuses on Diagonal and Stokes operator and Rate of convergence.
His work carried out in the field of Finite element method brings together such families of science as Grid, Algorithm, Computation and Euclidean geometry.
In his study, Linearization is strongly linked to Navier–Stokes equations, which falls under the umbrella field of Mathematical analysis.
Andrew J. Wathen interconnects Linear system and Schur complement in the investigation of issues within Eigenvalues and eigenvectors.
His most cited work include:
- Finite Elements and Fast Iterative Solvers: with Applications in Incompressible Fluid Dynamics (868 citations)
- A Note on Preconditioning for Indefinite Linear Systems (401 citations)
- Fast iterative solution of stabilised Stokes systems part II: using general block preconditioners (311 citations)
What are the main themes of his work throughout his whole career to date?
Andrew J. Wathen focuses on Applied mathematics, Numerical analysis, Preconditioner, Iterative method and Mathematical analysis.
His Applied mathematics research is multidisciplinary, incorporating elements of Matrix, Linear system, Finite element method and Eigenvalues and eigenvectors.
His work in Numerical analysis covers topics such as Mathematical optimization which are related to areas like Regularization.
His study in Preconditioner is interdisciplinary in nature, drawing from both Compressibility, Simple, Toeplitz matrix, Generalized minimal residual method and Schur complement.
His Iterative method research focuses on subjects like Multigrid method, which are linked to Solver.
His studies deal with areas such as Reynolds-averaged Navier–Stokes equations, Navier–Stokes equations and Hagen–Poiseuille flow from the Navier–Stokes equations as well as Mathematical analysis.
He most often published in these fields:
- Applied mathematics (37.86%)
- Numerical analysis (35.71%)
- Preconditioner (32.86%)
What were the highlights of his more recent work (between 2013-2021)?
- Applied mathematics (37.86%)
- Preconditioner (32.86%)
- Iterative method (31.43%)
In recent papers he was focusing on the following fields of study:
Andrew J. Wathen mainly investigates Applied mathematics, Preconditioner, Iterative method, Numerical analysis and Mathematical analysis.
His Applied mathematics research incorporates themes from Linear system, Krylov subspace, Finite element method, System of linear equations and Schur complement.
His Preconditioner study combines topics from a wide range of disciplines, such as Simple, Compressibility and Toeplitz matrix.
His Iterative method study frequently draws connections to other fields, such as Generalized linear mixed model.
His work deals with themes such as Algorithm, Mathematical optimization and Interpolation, which intersect with Numerical analysis.
His Mathematical analysis study integrates concerns from other disciplines, such as Reynolds-averaged Navier–Stokes equations and Hagen–Poiseuille flow from the Navier–Stokes equations.
Between 2013 and 2021, his most popular works were:
- Finite Elements and Fast Iterative Solvers: with Applications in Incompressible Fluid Dynamics (868 citations)
- Natural preconditioning and iterative methods for saddle point systems (41 citations)
- Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function (38 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Algebra
- Numerical analysis
Andrew J. Wathen spends much of his time researching Applied mathematics, Iterative method, Numerical analysis, Preconditioner and Krylov subspace.
The study incorporates disciplines such as Saddle point and Linear system, Mathematical analysis in addition to Iterative method.
His work carried out in the field of Numerical analysis brings together such families of science as Eigenvalues and eigenvectors, Mathematical optimization and Computation.
His Preconditioner research is multidisciplinary, relying on both Simple, Finite element method and Magma.
Many of his research projects under Finite element method are closely connected to Software with Software, tying the diverse disciplines of science together.
His Krylov subspace study deals with Circulant matrix intersecting with Diagonalizable matrix, Multigrid method and Conjugate gradient method.
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