World’s first ultra-fast photonic computing processor using polarization

In an article published today in Scientists progressOxford University researchers have developed a method using light polarization to maximize information storage density and computational performance using nanowires.

Light has an exploitable property – different wavelengths of light do not interact with each other – a characteristic used by optical fiber to carry parallel streams of data. Likewise, different polarizations of light also do not interact with each other. Each polarization can be used as an independent information channel, allowing more information to be stored in multiple channels, greatly improving the information density.

June Sang Lee, first author and PhD student, from the Department of Materials, University of Oxford, said: “We all know that the advantage of photonics over electronics is that light is faster and more functional over wide bandwidths, so our goal was to fully exploit these advantages of photonics combined with a tunable material to achieve faster and denser information processing.”

In collaboration with Professor C. David Wright of the University of Exeter, the research team developed a HAD (Hybrid Active Dielectric) nanowire, using a hybrid glassy material that exhibits switchable material properties upon illumination of optical pulses. Each nanowire shows selective responses to a specific polarization direction, so information can be processed simultaneously using multiple polarizations in different directions.

Using this concept, researchers developed the first photonic computing processor to use the polarizations of light.

Photonic computing is performed through multiple bias channels, leading to a multi-order computational density improvement over that of conventional electronic chips. Calculation speeds are faster because these nanowires are modulated by nanosecond optical pulses.

Since the invention of the first integrated circuit in 1958, fitting more transistors into a given size of electronic chip has been the preferred way to maximize computational density, the so-called “Moore’s Law”. However, with artificial intelligence and machine learning requiring specialized hardware beginning to push the boundaries of established computing, the dominant question in this area of ​​electronic engineering has been “How do we fit more functionality into a single transistor?”

For more than a decade, researchers in the laboratory of Professor Harish Bhaskaran in the Department of Materials at the University of Oxford have studied the use of light as a means of computation.

Professor Bhaskaran, who led the work, said: “This is just the beginning of what we would like to see in the future, namely the exploitation of all the degrees of freedom that light offers, including including biasing to greatly parallelize information processing stage work but super exciting ideas that combine electronics, non-linear materials and computing Lots of exciting perspectives to work on which is always a good place to be.”