Optical computing: multiplying light signals could help solve complex computational problems

A new type of optical computing could lead to ultra-fast computers that solve highly complex computational problems by multiplying light signals.

According to researchers at the University of Cambridge and the Skolkovo Institute of Science and Technology in Russia, multiplying light signals can help solve a class of challenging computational problems, which could have applications in fields such as graph theory, Artificial Intelligence, neural networks and error-correcting codes.

In a paper published in the Physical Review Letters, researchers propose a new type of computation that has the potential to transform analogue computing by massively reducing the quantity of light signals needed, while simplifying the search for the best mathematical solutions, allowing for ultra-fast optical computers.

Optical computing, also known as photonic computing, uses photons produced by lasers or diodes for computation, whereas traditional computers use electrons for computation.

Photons are effectively devoid of mass, and can therefore travel much faster than electrons, meaning optical computing has the potential to be superfast, energy-efficient, and able to process information simultaneously through multiple temporal or spatial optical channels.

The computing element in an optical computer is represented by the continuous phase of the light signal, and  computation is normally achieved by adding two light waves coming from two different sources and then projecting the result onto ‘0’ or ‘1’ states.

However, in real life, highly nonlinear problems are presented, where multiple unknowns simultaneously change the values of other unknowns while interacting multiplicatively, and in these instances the traditional approach to optical computing – combining light waves in a linear manner – fails.

This new research may represent a different type of connection between the light waves. Professor Natalia Berloff, from Cambridge’s Department of Applied Mathematics and Theoretical Physics, and Nikita Stroev, a PhD student from Skolkovo Institute of Science and Technology, have found that optical systems can combine light by multiplying the wave functions describing the light waves, instead of adding them.

They demonstrated this phenomenon with quasi-particles called polaritons, which are half-light and half-matter, while extending the idea to a larger class of optical systems such as light pulses in a fibre. Tiny pulses or blobs of coherent, superfast-moving polaritons can be created in space and overlap with one another in a nonlinear way, due to the matter component of polaritons.

The researchers have also come up with a method that guides the system trajectories towards the solution by temporarily changing the coupling strengths of the signals.

Professor Natalia Berloff from Cambridge’s Department of Applied Mathematics and Theoretical Physics commented: “We should start identifying different classes of problems that can be solved directly by a dedicated physical processor. Higher-order binary optimisation problems are one such class, and optical systems can be made very efficient in solving them.

“Changing our framework to directly address different types of problems may bring optical computing machines closer to solving real-world problems that cannot be solved by classical computers.”

Currently, there are challenges to overcome, such as noise reduction, error correction, and improved scalability, before optical computing can be proven superior in solving hard problems in  comparison with modern electronic computers.

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