Fast Hadamard transforms for compressive sensing of joint systems: Measurement of a 3.2 million-dimensional bi-photon probability distribution

Daniel J. Lum, Samuel H. Knarr, John C. Howell

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

We demonstrate how to efficiently implement extremely high-dimensional compressive imaging of a bi-photon probability distribution. Our method uses fast-Hadamard-transform Kronecker-based compressive sensing to acquire the joint space distribution. We list, in detail, the operations necessary to enable fast-transform-based matrix-vector operations in the joint space to reconstruct a 16.8 million-dimensional image in less than 10 minutes. Within a subspace of that image exists a 3.2 million-dimensional bi-photon probability distribution. In addition, we demonstrate how the marginal distributions can aid in the accuracy of joint space distribution reconstructions.

Original languageAmerican English
Pages (from-to)27636-27649
Number of pages14
JournalOptics Express
Volume23
Issue number21
DOIs
StatePublished - 19 Oct 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Optical Society of America.

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