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Researchers in the US have shown how all-optical processors could be used to carry out a range of linear mathematical transformations, including Fourier transforms. Using machine learning techniques, Onur Kulce, Aydogan Ozcan and colleagues at the University of California, Los Angeles, generated the blueprint for set of diffractive surfaces that can be used to produce specific optical outputs from any arbitrary input. When implemented in the lab, the approach could provide an alternative for calculating linear transformations using conventional computers.

To process information, computers often use linear transformations to perform mathematical operations on data. A classic example is the Fourier transform, which converts a time sequence of data – such as sound captured by a microphone – into a representation of the frequencies present in the data.

The speed at which such transformations can be done is limited by the processing power of electronic computers, but recently researchers have been exploring the possibility of using purely optical devices to do the task. Since optical waves travel effortlessly at the speed of light, this approach could one day be used to process information at far higher speeds and using far less energy than conventional computers.

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