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[PAST EVENT] Physics Colloquium
November 15, 2013
4pm - 5pm
Abstract:
Compressive sensing utilizes sparsity to realize efficient image reconstruction. It is a valuable processing technique when cost, power, technology or computational overhead are limited or high. In the quantum domain technology usually limits efficient acquisition of weak or fragile signals. We have used compressive sampling for low-flux laser Radar [1], photonic phase transitions, high resolution biphoton ghost imaging [2], Ghost object tracking [3] and high dimensional entanglement characterization [4]. As shown below, we were able to efficiently and rapidly reconstruct high dimensional joint probability functions of biphotons in momentum and position. With conventional raster scanning this process would take approximately a year, but using double-pixel compressive sensing, the pictures were acquired in a few hours with modest flux.
Compressive sensing utilizes sparsity to realize efficient image reconstruction. It is a valuable processing technique when cost, power, technology or computational overhead are limited or high. In the quantum domain technology usually limits efficient acquisition of weak or fragile signals. We have used compressive sampling for low-flux laser Radar [1], photonic phase transitions, high resolution biphoton ghost imaging [2], Ghost object tracking [3] and high dimensional entanglement characterization [4]. As shown below, we were able to efficiently and rapidly reconstruct high dimensional joint probability functions of biphotons in momentum and position. With conventional raster scanning this process would take approximately a year, but using double-pixel compressive sensing, the pictures were acquired in a few hours with modest flux.
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