iTWire - Australian Union develops 'world's first' self-calibrated photonic chip

Melbourne-based research has led to the creation of a self-calibrated photonic chip.

Research led by Monash University and RMIT in Melbourne has found a way to replace bulky 3D optics with silicon chips.

“We have demonstrated a self-calibrating self-programmable photonic filter chip featuring a signal processing core and an integrated reference path for self-calibration,” explains Monash University’s ARC-winning lead researcher Professor Arthur Lowery.

“Self-calibration is very important because it makes tunable photonic integrated circuits useful in the real world; applications include optical communication systems that redirect signals to destinations based on their color, very fast similarity calculations (correlators), scientific instrumentation for chemical or biological analysis, and even astronomy.

“Electronics saw a similar improvement in radio filter stability using digital techniques, which led to many phones being able to share the same slice of spectrum: our optical chips have a similar architecture, but can operate on signals with a terahertz bandwidth.”

The researchers say applications include AI for driverless cars, medical diagnostics and natural language processing, plus smaller switches for reconfiguring optical networks.

This approach was conceived by Dr Mike Xu from Monash University’s Department of Electrical and Computer Systems Engineering and now at Beijing Post and Telecommunication University, Professor Arthur Lowery from Monash University’s Department of Electrical and Computer Systems Engineering, and Dr Andy Boes from RMIT and now at the University of Adelaide.

Professors Arnan Mitchell and Dr Guanghui Ren engineered the chip, and the project was funded by the Australian Research Council.

While photonic circuits manipulate and route optical information channels, they can also provide some computational capabilities, for example, pattern searching, something that is fundamental to many applications including medical diagnosis and internet security.

Traditional photonic chips have to be manufactured to nanometer tolerances – a difficult and expensive process – but self-calibration overcomes this problem.

“Our solution was to calibrate the chip after manufacturing, to tune it using an on-chip reference, not by using external equipment,” Lowery said.

“We used the beauty of causality, effect following cause, which determines that the optical delay of the path through the chip can be uniquely inferred from intensity versus wavelength, which is much easier to measure than exact time delay. We’ve added a robust reference path to our chip. and calibrate it. This gives us all the necessary settings for the desired ‘dial up’ and switching function or spectral response.”

This approach opens up other applications, including optical correlators that can almost instantly find data patterns in data streams, such as images, and this is something the group is also working on.

“As we integrate more and more bench-sized devices onto fingernail-sized chips, it becomes increasingly difficult to get them all to work together to achieve the speed and functionality they did when they were bigger. We overcame this challenge by creating a chip that was smart enough to calibrate itself. itself so that all components can work at the speed they need simultaneously,” said Boes.

The self-calibrating chip is said to complement the optical microcomb chip – also developed at Monash University and RMIT – which achieves the world’s fastest internet speeds from a single chip the size of a fingernail.

“This research is a major breakthrough – our photonic technology is now advanced enough that truly complex systems can be integrated on a single chip. The idea that a device can have an on-chip reference system that allows all of its components to work as a single unit, is a technological breakthrough that will allow us to solve the problem of internet congestion by reconfiguring the optical network that carries our internet quickly to get data where it is needed most,” said Mitchell.

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