*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Metz, France | Posted: January 18, 2017
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."