Paper Published in the Journal, Scientific Reports, Co-authored by Faculty and PhD Students from Georgia Tech-Lorraine and Centrale-Supélec

Dr. Alexandre Locquet of Georgia Tech-Lorraine, and Dr. David Citrin of Georgia Tech/Georgia Tech-Lorraine, co-authored with Dr. Damien Rontani of Centrale-Supélec, and with PhD students Daeyoung Choi (ECE) and C.-Y. Chang (Physics), a paper in Scientific Reports (Nature Publishing Group), entitled, "Compressive Sensing with Optical Chaos."

Compressive sensing was devised to sample a sparse signal below the Nyquist-Shannon limit, but nonetheless to permit its faithful reconstruction, and thus to store and transmit sparse signals in a very efficient fashion. Compressive sensing relies on having at hand large strings of random (or sufficiently random-looking) numbers to populate the compression matrix needed to compress the data. Such strings of pseudo-random numbers are typically generated on a digital computer. Nevertheless, for the ultimate in high speed and simplicity, it is desirable to generate the string of random-like numbers, and ultimately carry out the compression itself, not only at speeds not readily attained
on a conventional computer, but also physically. The authors have used a chaotic optical signal produced by an external-cavity semiconductor laser to generate sufficiently random-like numbers at very high rate, based on the sub-100 picosecond timescale determining the dynamics of the laser. The team demonstrated efficient compression flowed by high-fidelity reconstruction of images using this technique. According to Citrin, "This work is exciting as it opens the way to ultrahigh-speed compression of sparse signals--and we hope soon in a way to be carried out in the physical layer."

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Chaotic patterns are used to generate random numbers