Superanalysis for Random-Matrix Theory

Abstract

Gossip has it that the “supersymmetry technique” is difficult to learn. But quite to the contrary, representing determinants as Gaussian integrals over anticommuting alias Grassmann variables makes for great simplifications in computing averages over the underlying matrices, as we have seen in Chaps. 4 and 8. Even in the semiclassical work of Chap. 10 Grassmann integrals were found to simplfy the bookkeeping, and the semiclassical construction of a sigma model even brought superintegrals into play.