We consider a class of nonlinear mappings $\mathsf{ F}_{ A,N}$ in $\mathbb{ R}^N$ indexed by symmetric random matrices $A\in\mathbb{ R}^{ N\times N}$ with independent entries. Within spin glass theory, special cases of these mappings correspond to iterating the TAP equations and were studied by Bolthausen [Comm. Math. Phys. 325 (2014) 333-366]. Within information theory, they are known as "approximate message passing" algorithms. We study the high-dimensional (large $N$) behavior of the iterates of $\mathsf{ F}$ for polynomial functions $\mathsf{ F}$, and prove that it is universal; that is, it depends only on the first two moments of the entries of $A$, under a sub-Gaussian tail condition. As an application, we prove the universality of a certain phase transition arising in polytope geometry and compressed sensing. This solves, for a broad class of random projections, a conjecture by David Donoho and Jared Tanner.

Categories: math.PR cs.IT math.IT

Universality in polytope phase transitions and message passing algorithms