Deterministic and stochastic systems lie at the heart of applied mathematics. They are dynamical models of the real world, whose reach is widespread and growing rapidly. Interest in such models grew from the discovery of chaos in simple models of atmospheric circulation, at almost the same time as astonishingly well-ordered and predictable behaviour was observed in models of particle physics. These starting points led to the development of new tools in applied mathematics, which turned out to be profoundly effective at describing emergent behaviours and change. The Economist magazine has stated that "The equations of a good theory are taken to represent physical reality because they can be used to make predictions". This unit will present a toolbox for describing and predicting outcomes. The tools also allow for methods of checking how parameters in a model could be changed to compare predictions to observations. You will learn how profound mathematical theory is applied to produce tools that are universal, adaptable and far-reaching. You will adapt and apply this fundamental theory to these to explore classical and current applications of mathematics to real world problems. You will use methods, developed to study classical areas, as springboards for new tools for innovative applications such as artificial intelligence and machine learning.
4-5 contact hours/week comprising lectures, and tutorials or seminars
tutorial participation (10%), written assignments (40%), final exam (50%)
Familiarity with the methods of classical applied mathematics (e.g., MATH4412) and some experience of probabilistic systems (e.g., STAT3021, MATH4311 or equivalent). Please consult with the coordinator for further information.