English

Large deviations for Gaussian diffusions with delay

Probability 2018-01-04 v3 Molecular Networks

Abstract

Dynamical systems driven by nonlinear delay SDEs with small noise can exhibit important rare events on long timescales. When there is no delay, classical large deviations theory quantifies rare events such as escapes from metastable fixed points. Near such fixed points, one can approximate nonlinear delay SDEs by linear delay SDEs. Here, we develop a fully explicit large deviations framework for (necessarily Gaussian) processes XtX_t driven by linear delay SDEs with small diffusion coefficients. Our approach enables fast numerical computation of the action functional controlling rare events for XtX_t and of the most likely paths transiting from X0=pX_0 = p to XT=qX_T=q. Via linear noise local approximations, we can then compute most likely routes of escape from metastable states for nonlinear delay SDEs. We apply our methodology to the detailed dynamics of a genetic regulatory circuit, namely the co-repressive toggle switch, which may be described by a nonlinear chemical Langevin SDE with delay.

Keywords

Cite

@article{arxiv.1610.08769,
  title  = {Large deviations for Gaussian diffusions with delay},
  author = {Robert Azencott and Brett Geiger and William Ott},
  journal= {arXiv preprint arXiv:1610.08769},
  year   = {2018}
}

Comments

28 pages, 6 figures (Version 3: minor corrections)

R2 v1 2026-06-22T16:33:54.762Z