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 language | English |
|---|---|
| Pages (from-to) | 27636-27649 |
| Number of pages | 14 |
| Journal | Optics Express |
| Volume | 23 |
| Issue number | 21 |
| DOIs | |
| State | Published - 19 Oct 2015 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015 Optical Society of America.