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Imaging High-Dimensional Spatial Entanglement with Compressive Sensing

Gregory A. Howland, John C. Howell

Published Jan 1, 2013• 0 citations
Publisher

Abstract

We use compressive sensing to efficiently image spatial correlations from spontaneous parametric downconversion at high resolution and witness entanglement. This technique efficiently scales to large dimensions and efficiently handles very low flux signals.
DOI
10.1364/cleo_qels.2013.qf1b.5

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We implement a double-pixel compressive-sensing camera to efficiently characterize, at high resolution, the spatially entangled fields that are produced by spontaneous parametric down-conversion.This technique leverages sparsity in spatial correlations between entangled photons to improve acquisition times over raster scanning by a scaling factor up to n 2 = logðnÞ for n-dimensional images.We image at resolutions up to 1024 dimensions per detector and demonstrate a channel capacity of 8.4 bits per photon.By comparing the entangled photons' classical mutual information in conjugate bases, we violate an entropic Einstein-Podolsky-Rosen separability criterion for all measured resolutions.More broadly, our result indicates that compressive sensing can be especially effective for higher-order measurements on correlated systems.
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