On the connection between least squares, regularization, and classical shadows
Zhihui Zhu,
Joseph M. Lukens,
Brian T. Kirby
Abstract:Classical shadows (CS) offer a resource-efficient means to estimate quantum observables, circumventing the need for exhaustive state tomography. Here, we clarify and explore the connection between CS techniques and least squares (LS) and regularized least squares (RLS) methods commonly used in machine learning and data analysis. By formal identification of LS and RLS "shadows" completely analogous to those in CS – namely, point estimators calculated from the empirical frequencies of single measurements – we sh… Show more
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