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Jonathan C. Mattingly

Jonathan C. Mattingly

Research.com Recognitions

  • 2015 - Fellow of the American Mathematical Society For contributions to the analysis of stochastic systems.
  • 2005 - Fellow of Alfred P. Sloan Foundation

Overview

Jonathan C. Mattingly is affiliated with Duke University in the United States and primarily works in the field of Mathematics. Their research spans various subfields including Mathematical Physics, Statistical and Nonlinear Physics, Finance, Statistics and Probability, and Molecular Biology. The main topics covered in their work include stochastic processes and financial applications, Markov Chains and Monte Carlo Methods, stochastic processes and statistical mechanics, fluid dynamics and turbulent flows, theoretical and computational physics, mathematical dynamics and fractals, and electoral systems and political participation.

Recent publications by Jonathan C. Mattingly demonstrate an emphasis on mathematical approaches to social and physical systems. Notable papers include:

  • "Quantifying Gerrymandering in North Carolina" (2020, Statistics and Public Policy)
  • "Metropolized Multiscale Forest Recombination for Redistricting" (2021, Multiscale Modeling and Simulation)
  • "Metropolized Forest Recombination for Monte Carlo Sampling of Graph Partitions" (2023, SIAM Journal on Applied Mathematics)
  • "Multi-Scale Merge-Split Markov Chain Monte Carlo for Redistricting" (2020, arXiv (Cornell University))
  • "Optimal Legislative County Clustering in North Carolina" (2020, Statistics and Public Policy)

Jonathan C. Mattingly frequently publishes in venues such as arXiv (Cornell University), Statistics and Public Policy, Multiscale Modeling and Simulation, Communications in Mathematical Sciences, and the SIAM Journal on Applied Mathematics.

Frequent collaborators include:

  • Gregory Herschlag
  • Andréa Agazzi
  • Ezra Miller
  • Zach Hunter
  • David P. Herzog

Throughout their career, Mattingly has been recognized with awards such as Fellow of the American Mathematical Society in 2015, for contributions to the analysis of stochastic systems, and Fellow of the Alfred P. Sloan Foundation in 2005.

Best Publications

  • Ergodicity for SDEs and approximations: Locally Lipschitz vector fields and degenerate noise

    J.C. Mattingly;A.M. Stuart;D.J. Higham

  • Ergodicity of the 2D Navier-Stokes equations with degenerate stochastic forcing

    Martin Hairer;Jonathan C. Mattingly

  • Yet Another Look at Harris’ Ergodic Theorem for Markov Chains

    Martin Hairer;Jonathan C. Mattingly

  • Asymptotic coupling and a general form of Harris’ theorem with applications to stochastic delay equations

    Martin Hairer;Martin Hairer;Jonathan Christopher Mattingly;Michael Scheutzow

  • Low-dimensional models of coherent structures in turbulence

    Philip J. Holmes;John L. Lumley;Gal Berkooz;Gal Berkooz;Jonathan C. Mattingly

  • Gibbsian Dynamics and Ergodicity¶for the Stochastically Forced Navier–Stokes Equation

    Weinan E;J. C. Mattingly;Yakov G. Sinai

  • Spectral gaps in Wasserstein distances and the 2D stochastic Navier–Stokes equations

    Martin Hairer;Jonathan Christopher Mattingly

  • Exponential Convergence for the Stochastically Forced Navier-Stokes Equations and Other Partially Dissipative Dynamics

    Jonathan C. Mattingly

  • Ergodicity for the Navier-Stokes Equation with Degenerate Random Forcing: Finite-Dimensional Approximation

    E Weinan;E Weinan;Jonathan Christopher Mattingly

  • Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations

    Jonathan C. Mattingly;Andrew M. Stuart;M. V. Tretyakov

  • A Theory of Hypoellipticity and Unique Ergodicity for Semilinear Stochastic PDEs

    Martin Hairer;Jonathan C Mattingly

  • AN ELEMENTARY PROOF OF THE EXISTENCE AND UNIQUENESS THEOREM FOR THE NAVIER–STOKES EQUATIONS

    J. C. Mattingly;Ya. G. Sinai

  • Ergodicity of 2D Navier–Stokes Equations with¶Random Forcing and Large Viscosity

    Jonathan C. Mattingly

  • Diffusion limits of the random walk metropolis algorithm in high dimensions

    Jonathan C. Mattingly;Natesh S. Pillai;Andrew M. Stuart

  • Malliavin calculus for the stochastic 2D Navier Stokes equation

    Jonathan C. Mattingly;Étienne Pardoux

  • An adaptive Euler–Maruyama scheme for SDEs: convergence and stability

    H. Lamba;J. C. Mattingly;A. M. Stuart

  • The strong Feller property for singular stochastic PDEs

    M Hairer;Jonathan Christopher Mattingly

  • Sticky central limit theorems on open books

    Thomas Hotz;Stephan Huckemann;Huiling Le;J. S. Marron

  • Sticky central limit theorems on open books

    Thomas Hotz;Sean Skwerer;Stephan Huckemann;Huiling Le

  • Asymptotic coupling and a weak form of Harris' theorem with applications to stochastic delay equations

    Martin Hairer;Jonathan C. Mattingly;Michael Scheutzow

Frequent Co-Authors

Martin Hairer
Martin Hairer Imperial College London
Andrew M. Stuart
Andrew M. Stuart California Institute of Technology
Sayan Mukherjee
Sayan Mukherjee Duke University
Etienne Pardoux
Etienne Pardoux Aix-Marseille University
John Harer
John Harer Duke University
Eric Vanden-Eijnden
Eric Vanden-Eijnden Courant Institute of Mathematical Sciences
Alan Frieze
Alan Frieze Carnegie Mellon University
David B. Dunson
David B. Dunson Duke University
Weinan E
Weinan E Princeton University
H. Frederik Nijhout
H. Frederik Nijhout Duke University

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