Faculty Publish in SIAM
Drs. Lora Billings and Eric Forgoston found that classical tools from dynamical systems and perturbation theory provide an intuitive way to analyze stochastic epidemiological models with seasonal forcing and predict noise-induced rare events.
Posted in: Faculty and Student Research
With its long history in a variety of fields, stochastic analysis continues to challenge modelers. Noise plays an important functional role in changing a system’s dynamics in applications across mathematical finance, physics, and biology [7]. Researchers in multiple disciplines have developed numerous approaches and notations to understand the dynamics beyond numerical simulation. Adding to the complexity, one can model noise as an external source or a collection of random internal processes, and few have considered incorporating either concept into models with time-dependent forcing.