Ergodicity

Statistics

Applied mathematics

Stochastic differential equation

Mathematics

Burgers' equation

Martingale (probability theory)

Domain (mathematical analysis)

Mathematical analysis

Uniqueness

Partial differential equation

Ergodic theory

Probability Theory and Related Fields

We develop a martingale approach for a class of singular stochastic PDEs of Burgers type (including fractional and multi-component Burgers equations) by constructing a domain for their infinitesimal generators. It was known that the domain must have trivial intersection with the usual cylinder test functions, and to overcome this difficulty we import some ideas from paracontrolled distributions to an infinite dimensional setting in order to construct a domain of controlled functions . Using the new domain, we are able to prove existence and uniqueness for the Kolmogorov backward equation and the martingale problem. We also extend the uniqueness result for “energy solutions” of the stochastic Burgers equation of Gubinelli and Perkowski (J Am Math Soc 31(2):427–471, 2018) to a wider class of equations. As applications of our approach we prove that the stochastic Burgers equation on the torus is exponentially $$L^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>L</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:math> -ergodic, and that the stochastic Burgers equation on the real line is ergodic.

The infinitesimal generator of the stochastic Burgers equation