Special Session 55: Sparse signal learning and its applications in data science

Instability of the Infinite Dimensional Operator Recovery Problem

Christopher Dock
Tufts University
USA
Co-Author(s):    Radu V. Balan
Abstract:
This talk expands on a well-known result of Daubechies, Cahill, and Casazza which says that the infinite dimensional phase-retrieval problem is never stable with respect to certain natural choices of metric. Following their proof, we bootstrap all the way up to the operator recovery problem for compact operators on a Hilbert space. The next part of the talk is a novel and far simpler proof which generalizes the result to bounded operators on a Hilbert space, and dispenses with some of the criteria required in the original proof. The result in this form has several interesting corollaries in terms of the non-existence of certain types of Banach Frames.