The Condition Number in Phase Retrieval from Intensity Measurements
Abstract
This paper investigates the stability of phase retrieval by analyzing the condition number of the nonlinear map A(x) = ( aj, x 2 )1 j m, where aj ∈ Hn are known sensing vectors with H ∈ \R, C\. For each p 1, we define the condition number β_Ap as the ratio of optimal upper and lower Lipschitz constants of A measured in the p norm, with respect to the metric distH(x, y) = \|x x - y y\|*. We establish universal lower bounds on β_Ap for any sensing matrix A ∈ Hm × d, proving that β_A1 π/2 and β_A2 3 in the real case (H = R), and β_Ap 2 for p=1,2 in the complex case (H = C). These bounds are shown to be asymptotically tight: both a deterministic harmonic frame Em ∈ Rm × 2 and Gaussian random matrices A ∈ Hm × d asymptotically attain them. Notably, the harmonic frame Em ∈ Rm × 2 achieves the optimal lower bound 3 for all m 3 when p=2, thus serving as an optimal sensing matrix within A ∈ Rm × 2. Our results provide the first explicit uniform lower bounds on β_Ap and offer insights into the fundamental stability limits of phase retrieval.
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