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We implement a double-pixel, compressive sensing camera to efficientlycharacterize, at high resolution, the spatially entangled fields produced byspontaneous parametric downconversion. This technique leverages sparsity inspatial correlations between entangled photons to improve acquisition timesover raster-scanning by a scaling factor up to n^2/log(n) for n-dimensionalimages. We image at resolutions up to 1024 dimensions per detector anddemonstrate a channel capacity of 8.4 bits per photon. By comparing theclassical mutual information in conjugate bases, we violate an entropicEinstein-Podolsky-Rosen separability criterion for all measured resolutions.More broadly, our result indicates compressive sensing can be especiallyeffective for higher-order measurements on correlated systems.

Efficient high-dimensional entanglement imaging with a compressive sensing, double-pixel camera