Publications

[43]  Santolo Leveque, Luca Bergamaschi, Ángeles Martínez, and John W. Pearson, Parallel-in-Time Solver for the All-at-Once Runge-Kutta Discretization, submitted.  [link]

[42]  Jonna C. Roden, Rory D. Mills-Williams, John W. Pearson, and Benjamin D. Goddard, MultiShape: A Spectral Element Method, with Applications to Dynamic Density Functional Theory and PDE-Constrained Optimization, submitted.  [link]

[41]  John W. Pearson and Andreas Potschka, Double Saddle-Point Preconditioning for Krylov Methods in the Inexact Sequential Homotopy Method, submitted.  [link]

[40]  Andrés Miniguano-Trujillo, John W. Pearson, and Benjamin D. Goddard, A Numerical Framework for the Parameter Identification of the SIRD Model, submitted. 

[39]  Jemima M. Tabeart and John W. Pearson, Saddle Point Preconditioners for Weak-Constraint 4D-Var, submitted.  [link]

[38]  Jonna C. Roden, Benjamin D. Goddard, and John W. Pearson, DDFT for Sedimentation Processes: Dynamic Density Functional Theory for Sedimentation Processes on Complex Domains: Modelling, Spectral Elements, and Control Problems, to appear in The Journal of Chemical Physics, 2023.

[37]  John W. Pearson and Andreas Potschka, On Symmetric Positive Definite Preconditioners for Multiple Saddle-Point Systems, IMA Journal of Numerical Analysis, https://doi.org/10.1093/imanum/drad046, 2023.  [link]

[36]   Santolo Leveque and John W. Pearson, Parameter-Robust Preconditioning for Oseen Iteration Applied to Stationary and Instationary Navier–Stokes Control, SIAM Journal on Scientific Computing, 44(3), pp. B694-B722, 2022.  [link]

[35]  Jacek Gondzio, John W. Pearson, and Spyridon Pougkakiotis, General-Purpose Preconditioning for Regularized Interior Point Methods, Computational Optimization and Applications, 83, 727--757, 2022.  [link]

[34]  Mildred Aduamoah, Benjamin D. Goddard, John W. Pearson, and Jonna C. Roden, Pseudospectral Methods and Iterative Solvers for Optimization Problems from Multiscale Particle Dynamics, BIT Numerical Mathematics, 62, pp. 1703-1743, 2022.  [link]

[33]  Santolo Leveque and John W. Pearson, Fast Iterative Solver for the Optimal Control of Time-Dependent PDEs with Crank-Nicolson Discretization in Time, Numerical Linear Algebra with Applications, 29(2), e2419, 2022.  [link]

[32]  Stefan Güttel and John W. Pearson, A spectral-in-time Newton–Krylov method for nonlinear PDE-constrained optimization, IMA Journal of Numerical Analysis, 42(2), 1478-1499, 2022.  [link]

[31]  Luca Bergamaschi, Jacek Gondzio, Ángeles Martinez, John W. Pearson, and Spyridon Pougkakiotis, A new preconditioning approach for an interior point-proximal method of multipliers for linear and convex quadratic programming, Numerical Linear Algebra with Applications, 28(4), e2361, 2021.  [link]

[30]  Santolo Leveque and John W. Pearson, Parameter-Robust Preconditioning for Unsteady Stokes Control Problems, Proceedings in Applied Mathematics and Mechanics, 21, e202100131, 2021.  [link]

[29]  John W. Pearson and Jennifer Pestana, Preconditioners for Krylov Subspace Methods: An Overview, GAMM-Mitteilungen, 43(4), e202000015, 2020.  [link]

[28]  Spyridon Pougkakiotis, John W. Pearson, Santolo Leveque, and Jacek Gondzio, Fast Solution Methods for Convex Quadratic Optimization of Fractional Differential Equations, SIAM Journal on Matrix Analysis and Applications, 41(3), pp. 1443-1476, 2020.  [link]

[27]  John W. Pearson, Margherita Porcelli, and Martin Stoll, Interior Point Methods and Preconditioning for PDE-Constrained Optimization Problems Involving Sparsity Terms, Numerical Linear Algebra with Applications, 27(2), e2276, 2020.  [link]

[26]  Jun Liu and John W. Pearson, Parameter-Robust Preconditioning for the Optimal Control of the Wave Equations, Numerical Algorithms, 83(3), pp. 1171-1203, 2020.  [link]

[25]  Sergey Dolgov and John W. Pearson, Preconditioners and Tensor Product Solvers for Optimal Control Problems from Chemotaxis, SIAM Journal on Scientific Computing, 41(6), pp. B1228-B1253, 2019.  [link]

[24]  Roland Herzog, John W. Pearson, and Martin Stoll, Fast Iterative Solvers for an Optimal Transport Problem, Advances in Computational Mathematics, 45(2), pp. 495–517, 2019.  [link]

[23]  John W. Pearson and Jacek Gondzio, On Block Triangular Preconditioners for the Interior Point Solution of PDE-Constrained Optimization Problems, in Domain Decomposition Methods in Science and Engineering XXIV, pp. 503-510, Springer, 2019.  [link]

[22]  John W. Pearson, PDE-Constrained Optimization Problems for Scientific Processes, Proceedings in Applied Mathematics and Mechanics, 18, 2018.  [link]

[21]  John W. Pearson and Andy Wathen, Matching Schur Complement Approximations for Certain Saddle-Point Systems, in Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan (J. Dick, F. Y. Kuo, H. Woźniakowski, eds.), pp. 1001-1016, Springer, 2018.  [link]

[20]  Stefan Güttel and John W. Pearson, A Rational Deferred Correction Approach to Parabolic Optimal Control Problems, IMA Journal of Numerical Analysis, 38(4), pp. 1861-1892, 2018.  [link]

[19]  John W. Pearson, Jennifer Pestana, and David J. Silvester, Refined Saddle-Point Preconditioners for Discretized Stokes Problems, Numerische Mathematik, 138(2), pp. 331-362, 2018.  [link]

[18]  Patrick E. Farrell and John W. Pearson, A Preconditioner for the Ohta-Kawasaki Equation, SIAM Journal on Matrix Analysis and Applications, 38(1), pp. 217-225, 2017.  [link]

[17]  John W. Pearson and Jacek Gondzio, Fast Interior Point Solution of Quadratic Programming Problems Arising from PDE-Constrained Optimization, Numerische Mathematik, 137(4), pp. 959-999, 2017.  [link]

[16]  John W. Pearson, Sheehan Olver, and Mason A. Porter, Numerical Methods for the Computation of the Confluent and Gauss Hypergeometric Functions, Numerical Algorithms, 74(3), pp. 821-866, 2017.  [link]  [code]

[15]  John W. Pearson and Jacek Gondzio, Fast interior point solvers for H1-regularized PDE-constrained optimization problems, Proceedings in Applied Mathematics and Mechanics, 16, pp. 737-738, 2016.  [link]

[14]  Martin Stoll, John W. Pearson, and Philip K. Maini, Fast Solvers for Optimal Control Problems from Pattern Formation, Journal of Computational Physics, 304, pp. 27-45, 2016.  [link]

[13]  Sergey Dolgov, John W. Pearson, Dmitry V. Savostyanov, and Martin Stoll, Fast Tensor Product Solvers for Optimization Problems with Fractional Differential Equations as Constraints, Applied Mathematics and Computation, 273, pp. 604-623, 2016.  [link]

[12]  John W. Pearson, Fast Iterative Solvers for Large Matrix Systems Arising from Time-Dependent Stokes Control Problems, Applied Numerical Mathematics, 108, pp. 87-101, 2016.  [link]

[11]  John W. Pearson, Block Triangular Preconditioning for Time-Dependent Stokes Control, Proceedings in Applied Mathematics and Mechanics, 15, pp. 727-730, 2015.  [link]

[10]  John W. Pearson, Preconditioned Iterative Methods for Navier-Stokes Control Problems, Journal of Computational Physics, 292, pp. 194-207, 2015.  [link]

[9]  John W. Pearson, On the Development of Parameter-Robust Preconditioners and Commutator Arguments for Solving Stokes Control Problems, Electronic Transactions on Numerical Analysis, 44, pp. 53-72, 2015.  [link]

[8]  John W. Pearson, Martin Stoll, and Andrew J. Wathen, Preconditioners for State Constrained Optimal Control Problems with Moreau-Yosida Penalty Function, Numerical Linear Algebra with Applications, 21(1), pp. 81-97, 2014.  [link]

[7]  John W. Pearson, Fast Iterative Solvers for PDE-Constrained Optimization Problems, DPhil Thesis, University of Oxford, 2013.  [link]

[6]  John W. Pearson and Martin Stoll, Fast Iterative Solution of Reaction-Diffusion Control Problems Arising from Chemical Processes, SIAM Journal on Scientific Computing, 35, pp. B987-B1009, 2013.  [link]

[5]  John W. Pearson and Andrew J. Wathen, Fast Iterative Solvers for Convection-Diffusion Control Problems, Electronic Transactions on Numerical Analysis, 40, pp. 294-310, 2013.  [link]

[4]  John W. Pearson, A Radial Basis Function Method for Solving PDE-Constrained Optimization Problems, Numerical Algorithms, 64(3), pp. 481-506, 2013.  [link]

[3]  John W. Pearson, Martin Stoll, and Andrew J. Wathen, Robust Iterative Solution of a Class of Time-Dependent Optimal Control Problems, Proceedings in Applied Mathematics and Mechanics, 12, pp. 3-6, 2012.  [link]

[2]  John W. Pearson, Martin Stoll, and Andrew J. Wathen, Regularization-Robust Preconditioners for Time-Dependent PDE-Constrained Optimization Problems, SIAM Journal on Matrix Analysis and Applications, 33(4), pp. 1126-1152, 2012.  [link]

[1]  John W. Pearson and Andrew J. Wathen, A New Approximation of the Schur Complement in Preconditioners for PDE-Constrained Optimization, Numerical Linear Algebra with Applications, 19(5), pp. 816-829, 2012.  [link]

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Link to my Google Scholar page

Link to Edinburgh Research Explorer page

Link to my MSc thesis of 2009 - Computation of Hypergeometric Functions