Jonathan Christopher Mattingly

  • Professor of Mathematics
  • Chair of the Department of Mathematics
  • Professor of Statistical Science (Secondary)

Research Areas and Keywords

Analysis
Stochastic Analysis, Malliavin Calculus, Ergodic Theory
Biological Modeling
Stochastic and Random PDEs, Stochastic Dynamical Systems, Mathematical Ecology and Evolution, Metabolic and Cellular modeling, Out of equilibrium statistical mechanics
Computational Mathematics
Markov Chain Mixing, Stochastic Numerical Methods, High Dimensional Random Algorithms
PDE & Dynamical Systems
Stochastic and Random PDEs, Stochastic Dynamical Systems, Malliavin Calculus, Fluid Mechanics, Approximating invariant measures
Physical Modeling
Stochastic and Random PDEs, Stochastic Dynamical Systems, Fluid Mechanics
Probability
Stochastic and Random PDEs, Stochastic Dynamical Systems, Stochastic Analysis, Malliavin Calculus, Markov Chain Mixing, Ergodic Theory, High Dimensional Random Algorithms, Probability on stratified spaces, Out of equilibrium statistical mechanics, Approximating invariant measures

Jonathan Christopher  Mattingly grew up in Charlotte, NC where he attended Irwin Ave elementary and Charlotte Country Day.  He graduated from the NC School of Science and Mathematics and received a BS is Applied Mathematics with a concentration in physics from Yale University. After two years abroad with a year spent at ENS Lyon studying nonlinear and statistical physics on a Rotary Fellowship, he returned to the US to attend Princeton University where he obtained a PhD in Applied and Computational Mathematics in 1998. After 4 years as a Szego assistant professor at Stanford University and a year as a member of the IAS in Princeton, he moved to Duke in 2003. He is currently a Professor of Mathematics and of Statistical Science.

His expertise is in the longtime behavior of stochastic system including randomly forced fluid dynamics, turbulence, stochastic algorithms used in molecular dynamics and Bayesian sampling, and stochasticity in biochemical networks.

He is the recipient of a Sloan Fellowship and a PECASE CAREER award.  He is also a fellow of the IMS and the AMS.

Education & Training
  • Ph.D., Princeton University 1998

  • M.A., Princeton University 1996

  • B.S., Yale University 1992

Mattingly, JC, and Suidan, TM. "The small scales of the stochastic Navier-Stokes equations under rough forcing." JOURNAL OF STATISTICAL PHYSICS 118.1-2 (January 2005): 343-364. Full Text

Bakhtin, Y, and Mattingly, JC. "Stationary solutions of stochastic differential equations with memory and stochastic partial differential equations." Communications in Contemporary Mathematics 7.5 (2005): 553-582. Full Text

Hairer, M, Mattingly, JC, and Pardoux, É. "Malliavin calculus for highly degenerate 2D stochastic Navier–Stokes equations." Comptes Rendus Mathematique 339.11 (December 2004): 793-796. Full Text

Hairer, M, and Mattingly, JC. "Ergodic properties of highly degenerate 2D stochastic Navier–Stokes equations." Comptes Rendus Mathematique 339.12 (December 2004): 879-882. Full Text

Mattingly, JC, Mattingly, JC, and Mattingly, JC. "On recent progress for the stochastic Navier Stokes equationsOn recent progress for the stochastic Navier Stokes equationsOn Recent Progress for the Stochastic Navier Stokes Equations." Journées "Équations aux Dérivées Partielles" XV (July 2003): viii+298-. (Academic Article)

Mattingly, JC. "The dissipative scale of the stochastics Navier-Stokes equation: Regularization and analyticity." Journal of Statistical Physics 108.5-6 (December 1, 2002): 1157-1179. Full Text

Mattingly, JC. "Exponential convergence for the stochastically forced Navier-Stokes equations and other partially dissipative dynamics." Communications in Mathematical Physics 230.3 (November 1, 2002): 421-462. Full Text

Mattingly, JC, Stuart, AM, and Higham, DJ. "Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise." Stochastic Processes and their Applications 101.2 (October 2002): 185-232. Full Text

Mattingly, JC, and Stuart, AM. "Geometric ergodicity of some hypo-elliptic diffusions for particle motions." Markov Processes and Related Fields 8 (2002): 199-214. (Academic Article)

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