After attending a seminar by Pete Ashwin (Exeter) several weeks ago, quasipotentials (in the sense of Freidlin and Wentzell) have been on a mind.
Consider a gradient system, that is, a system of the form dx/dt = ∇V(x). Minima of the potential are attractors for this system. If we now add some noise, the equation becomes the stochastic differential equation dxₜ = ∇V(x) dt + σ dWₜ. The noise can push the system from one minimum to another. Large deviation theory gives a formula for the expected time that we have to wait for this to happen.
But what if we don't start with a gradient system? The equation is now dxₜ = f(x) dt + σ dWₜ for general f. The same formula holds if we replace the potential V with the so-called pseudopotential. The pseudopotential measures how much you have to go against the motion of the noise-free system dx/dt = f(t). Unfortunately, the pseudopotential is not so easy to compute and this is what I have been thinking about.
For a precise statement and references, maybe look at the Wikipedia page https://en.wikipedia.org/wiki/Freidlin%E2%80%93Wentzell_theorem (I don't know the topic well enough to understand the details).
#StochasticDifferentialEquations #LargeDeviationsTheory