On Lipschitz Analysis and Lipschitz Synthesis for the Phase Retrieval Problem

Abstract: In this paper we prove two results regarding reconstruction from magnitudes of frame coefficients (the so called "phase retrieval problem"). First we show that phase retrievability as an algebraic property implies that nonlinear maps are bi-Lipschitz with respect to appropriate metrics on the quotient space. Second we prove that reconstruction can be performed using Lipschitz continuous maps. Specifically we show that when nonlinear analysis maps $\alpha,\beta:\hat{H}\rightarrow R^m$ are injective, with $\alpha(x)=(|\langle x,f_k\rangle |){k=1}^m$ and $\beta(x)=(|\langle x,f_k \rangle|^2){k=1}^m$, where ${f_1,\ldots,f_m}$ is a frame for a Hilbert space $H$ and $\hat{H}=H/T^1$, then $\alpha$ is bi-Lipschitz with respect to the class of "natural metrics" $D_p(x,y)= min_{\varphi} || x-e^{i\varphi}y {||}_p$, whereas $\beta$ is bi-Lipschitz with respect to the class of matrix-norm induced metrics $d_p(x,y)=|| xx^-yy^{||}_p$. Furthermore, there exist left inverse maps $\omega,\psi:R^m\rightarrow \hat{H}$ of $\alpha$ and $\beta$ respectively, that are Lipschitz continuous with respect to the appropriate metric. Additionally we obtain the Lipschitz constants of these inverse maps in terms of the lower Lipschitz constants of $\alpha$ and $\beta$. Surprisingly the increase in Lipschitz constant is a relatively small factor, independent of the space dimension or the frame redundancy.