  We show that the fundamental tasks of sorting lists and building search trees
or heaps can be modeled as quadratic unconstrained binary optimization problems
(QUBOs). The idea is to understand these tasks as permutation problems and to
devise QUBOs whose solutions represent appropriate permutation matrices. We
discuss how to construct such QUBOs and how to solve them using Hopfield nets
or adiabatic) quantum computing. In short, we show that neurocomputing methods
or quantum computers can solve problems usually associated with abstract data
structures.
