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Modern communication systems increasingly rely on light to transmit large amounts of information. One way to increase their capacity is to encode data into complex light patterns, but reading those patterns quickly and accurately presents a challenge. Conventional approaches may require detailed imaging and extensive digital processing, potentially limiting the speed at which information can be decoded.
Researchers at the University of the Witwatersrand have developed a light-based neural network that can recognize information embedded in structured light without first capturing a complete image.
The technology combines principles from artificial intelligence and optical physics, allowing light itself to perform part of the information-processing task.
Instead of analyzing a light pattern pixel by pixel using conventional computing, the system passes incoming light through specially designed optical layers. These layers manipulate how the light travels, directing it toward different detectors.
The location where the light arrives indicates which information is encoded in the original pattern.
According to TechXplore, the approach focuses on a mathematical property called topology, which describes features that remain unchanged even when an object’s shape is distorted.
For example, a twisted ribbon can be bent or folded into different shapes without changing its number of twists. Certain structured light patterns contain similarly persistent characteristics, allowing information to be identified even when their appearance changes.
The optical neural network is designed to recognize those underlying features rather than reconstruct every detail of the incoming light.
During experiments, the system learned from just 15 training examples and successfully recognized 81 different light structures within the family being studied, including configurations it had not previously encountered.
It also maintained its recognition capability when researchers introduced noise into the detector, suggesting potential advantages when optical signals are affected by imperfect measurement conditions.
The research could have implications for future optical communications, where complex light patterns may allow more information to be transmitted through a single communication channel.
It could also become relevant to defense and homeland-security applications. Military communications, secure data links and advanced sensing systems increasingly depend on processing information quickly and reliably. Optical technologies capable of extracting useful information with less digital processing could potentially support compact, efficient communication receivers.
However, the research remains a laboratory demonstration rather than an operational communications system. Its performance in deployed networks has not yet been established.
The researchers are also exploring potential applications in quantum technologies, where extracting information from individual particles of light presents additional measurement challenges.
The broader significance lies in changing where information processing happens. Instead of converting an entire optical signal into digital data before analyzing it, part of the interpretation can take place directly through the behavior of light.
For future communication systems, that could mean reading increasingly complex signals without requiring equally complex electronic processing.
The research was published here.
