In a new study published in Nature Reviews Physics, a team of researchers suggests that the future of computing may not lie in silicon chips but in beams of light. Rather than relying on conventional optical systems, they propose an emerging framework called “multidimensional photonic computing”, which encodes and processes information across multiple properties of light simultaneously.
The international team, led by scientists from the University of Münster and Heidelberg University, outlines how this approach could enable faster, denser, and more energy-efficient data processing, potentially transforming how machines manage the exploding demands of artificial intelligence and machine learning.
According to the researchers, multidimensional photonic computing uses independent characteristics of light — such as wavelength, polarization, phase, and spatial mode — to run many operations in parallel. This design sidesteps the physical limits of traditional electronics and opens a path to greater scalability.
The study draws a distinction between two emerging approaches: classical photonic computing, which is optimized for high-throughput data tasks, and quantum photonic computing, which is better suited for complex problems that outstrip the capacity of conventional systems.
“The complementary nature of these approaches suggests a promising path towards multidimensional, neuromorphic photonic quantum computing as a flexible and efficient architecture to meet future computational demands,” the researcher write in the study.
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