Photonic computers will boost the speed of modern day computing by at least twenty fold, but while converting data into light is easy, getting it back again has proved a challenge.


So far in the past few years we’ve turned light into a superfluid and figured out how to bring it to a standstill, now though another team of scientists have taken a big step towards creating the next generation of light based computers when, for the first time ever, they managed to store light based information as sound waves on a computer chip, and it’s a breakthrough that’s being equated to being able to “capture lightning as thunder.”


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While, obviously, that sounds strange, weird and possibly even some form of crude marketing ploy, this conversion is critical if we ever want to move away from today’s relatively slow and lethargic silicon based computing platforms to new light based ones that can move data at the speed of light, in other words via photons, rather than at the speed of electricity as we do, or via electrons.

Light based or as they’re more commonly known photonic computers have the potential to run at least 20 times faster than your average laptop, not to mention the fact that they won’t produce any heat or suck up anywhere near as much energy as today’s existing devices, and this is all thanks to the fact that in theory they’re swapping those electrons for photons.

I say in theory because despite companies such as IBM and Intel trying to build photonic computers the transition is easier said than done. Coding information into photons is actually easy and we already do that when we send information via optical fibre, but trying to find a way for a computer chip to retrieve and process information that’s stored in photons is tough, and it’s only made tougher thanks to the fact it’s moving so damned fast meaning that it’s hard for existing microchips to read.


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This is why photonic information that flies across internet cables is currently converted into slow electrons at either end but a better alternative, apparently, would be to slow down the light and convert it into sound. And that’s exactly what researchers from the University of Sydney in Australia have done.

“The information in our microchip in acoustic form travels at a velocity five orders of magnitude slower than in the optical domain,” said project supervisor Birgit Stiller, “it’s like the difference between thunder and lightning, one’s slower than the other.”

This new breakthrough also means that photonic computers could have the benefits of data delivered at light speed without any of the heat associated with electronic resistance and no interference from electromagnetic radiation, but it also means that the data could be slowed down enough so that computers chips could capture it and do something useful with it.

“For photonic computers to become a commercial reality photonic data on the chip needs to be slowed down so that they can be processed, routed, stored and accessed,” said one of the research team, Moritz Merklein.


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“This is an important step forward in the field of optical information processing as this concept fulfils all requirements for current and future generation optical communication systems,” added team member Benjamin Eggleton.

The team achieved their amazing feat by developing a memory system that accurately transfers between light and sound waves on a photonic microchip, the kind of chip that will be used in tomorrow’s photonic computers, and you can see how it works in the animation below:


How it works

First, photonic information enters the chip as a pulse of light (yellow), where it interacts with a ‘write’ pulse (blue), producing an acoustic wave that stores the data. Another pulse of light, called the ‘read’ pulse (blue), then accesses this sound data and transmits as light once more (yellow).

While unimpeded light will pass through the chip in 2 to 3 nanoseconds once stored as a sound wave information can remain on the chip for up to 10 nanoseconds, long enough for it to be retrieved and processed, and the fact that the team was able to convert the light into sound waves not only slowed the data down but also made data retrieval more accurate. And, unlike previous attempts, the system worked across a broad bandwidth.


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“Building an acoustic buffer inside a chip improves our ability to control information by several orders of magnitude,” said Merklein.

“Our system is not limited to a narrow bandwidth. So unlike previous systems this allows us to store and retrieve information at multiple wavelengths simultaneously, vastly increasing the efficiency of the device,” added Stiller.

The research was published in Nature Communications.

About author

Matthew Griffin

Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, Bloomberg, CNBC, Discovery, RT, Viacom, and WIRED, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Aon, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.

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