Phase Retrieval for $$L^2([-\pi ,\pi ])$$ via the Provably Accurate and Noise Robust Numerical Inversion of Spectrogram Measurements

Iwen, Mark A.; Perlmutter, Michael; Sissouno, Nada; Viswanathan, Aditya

doi:10.1007/s00041-022-09988-6

Cited by 1 publication

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“…Different further aspects of uniqueness and stability for Gabor phase retrieval have been studied over the past decade [ 2 – 6 , 8 , 12 , 14 – 21 , 23 , 24 , 27 , 30 – 32 ]. Here, we want to highlight two findings that motivate the study of this paper: Prior work by two authors of this paper on the (non-)uniqueness of sampled Gabor phase retrieval [ 4 ] shows that sampled Gabor phase retrieval does not enjoy uniqueness (for signals in ) when the sampling set is any (shifted) lattice in .…”

Section: Introductionmentioning

confidence: 99%

On the connection between uniqueness from samples and stability in Gabor phase retrieval

Alaifari,

Bartolucci,

Steinerberger

et al. 2024

Sampl. Theory Signal Process. Data Anal.

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Gabor phase retrieval is the problem of reconstructing a signal from only the magnitudes of its Gabor transform. Previous findings suggest a possible link between unique solvability of the discrete problem (recovery from measurements on a lattice) and stability of the continuous problem (recovery from measurements on an open subset of $$\mathbb {R}^2$$ R 2 ). In this paper, we close this gap by proving that such a link cannot be made. More precisely, we establish the existence of functions which break uniqueness from samples without affecting stability of the continuous problem. Furthermore, we prove the novel result that counterexamples to unique recovery from samples are dense in $$L^2(\mathbb {R})$$ L 2 ( R ) . Finally, we develop an intuitive argument on the connection between directions of instability in phase retrieval and certain Laplacian eigenfunctions associated to small eigenvalues.

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