Abstract

When Light propagates through optical elements (such as lenses), it undergoes a transform. The input and the output data take the form of light and optical elements that perform different mathematical operations on light represent the linear transform. The transform is performed not on the discrete elements of the data but on the whole vector at once, and most significantly, at the speed of light. The great advantages offered by optical processing are that it offers enormous parallelism, operating on all data points simultaneously, very low latency, a high transform rate and low power dissipation. The outcome is enormously increased speed and a reduction in the amount of associated cooling required. The Optical Signal Processor (OSP) increases the speed of processing transforms by many orders of magnitude. The Signal Processor is also reconfigurable and can be dynamically tailored to the required transform type. One advantage of an optical processor is that it allows software designers to work at a much higher level of abstraction. This is because the device executes transforms instead of the ordinary MACs in the case of DSPs. Instead of handling algorithms at individual data points, algorithms for handling the entire vector could be processed, shortening the computational complexity and speeding the time-to-market for new products. An optical filter can be represented as a generic function, the most fundamental of the optical processor. The impulse response of this filter is defined with respect to frequency of light. Any transform on light can be represented as a combination of linear transforms. This is fundamentally the law of optical signal processing. The most important application of an OSP in Optical Networking is Pattern recognition, and this can easily be done by the usual cross-correlation technique that is common in digital signal processing. The OSP can be programmed to autocorrelate against specific temporal reference waveforms, viz. Data. The decoding is done without electronic processing. And of

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