Causality and Green’s functions

The chapter elucidates causality to prevent its erroneous use. It then develops Green’s functions to analyze and predict systems under stimulation in the presence of cause and chance. Causality is the tracing of an observed phenomenon entirely to an identified cause. Cause and chance both lead to observations in the natural world. Chance is tackled through probabilities. A toy quantum model emphasizing uncertainty is used to illustrate cause and chance. Several examples are discussed to illustrate the development of Green’s functions—examining both advancing Green’s functions and retarding Green’s functions—for classical and quantum evolution. The S-matrix is also discussed.