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The Genetic Codes That Create Optical Computers
FIP researchers are using self-assembling DNA to form the basic components for optical computing
Researchers at Duke University can use photons instead of electrons to store data, drastically increasing the storage capacity of the optical analog of Blu-Ray discs.
So what are your top 5,000 movies?
“That’s the kind of ridiculous thing we can do, but I don’t know how we’re going to use it,” said Chris Dwyer, associate professor of electrical and computer engineering and of computer science at Duke.
Like his Fitzpatrick Institute for Photonics colleague Jungsang Kim, Dwyer is working to bring an entirely new type of computer hardware into our day-to-day lives. But unlike Kim’s, his technology isn’t based on the quantum state of individual atoms.
Optical computing has been around for decades, but the physical properties of light have limited their use to large scales. Wave guides that interact with and manipulate light have to be of the same order of magnitude in size. And for photons, that means nothing can be much smaller than a micron, which is huge compared to conventional silicon systems.
Dwyer, however, and others in his field have found a way around this problem—excitons.
When individual molecules called chromophores interact with light, they quantum-mechanically absorb some of its energy, which gets turned into an exciton. And when that little nugget of energy moves from chromophore to chromophore in specific patterns, it creates light-based computational components.
“For my group, it’s about applying this kind of photoluminescence to building memory systems, sensors and computational logic,” said Dwyer. “And we build these components with self-assembling nanostructures using DNA.”
This approach has several benefits.
For one, Dwyer and his group can use DNA structures to piece together logic gates just two nanometers wide. This leads to memory systems that are very dense. And the way light propagates also means that the amount of energy required to perform an operation is radically lower than a conventional computer.
Or at least it could be, once Dwyer’s group gets all of the components talking to one another. They can currently build logic gates and memory elements and network them together, but they still have to figure out how to optimize these devices so that they can compete with electrical silicon technologies.
“These devices blow silicon processors out of the water on paper, but getting the real world in line with the theory is easier said than done,” said Dwyer. “On the flip side, we can figure out how to use these devices just as they are in spaces where conventional technologies can’t go.”
For example, being made out of DNA, these tiny computational networks are biologically compatible. Perhaps scientists could put some computing power on a diagnostic assay inside the body—a feat which would greatly reduce the costs of such tests. Or in a future science fiction world, maybe scientists could conduct computations inside the bloodstream itself.
Dwyer also notes the idea of an encryptable drug, which would have a cryptographic algorithm run by a molecular-scale computer that would render it ineffective if it wasn’t presented with the correct challenge or response.
“I spent a great deal of my career trying to simply replace silicon in computing technology,” said Dwyer. “It probably took me the better part of six years , or half my career in academics, to figure out that a much better use of this technology is to bring computation to every niche of the physical world where silicon can’t go. I think that’s a much better use of our technology.”