Customer care
+34 913 67 09 92
Follow us

The future of ultrafast technology is here: the advanced chip that is light years ahead of the curve

Research led by Monash University, RMIT and the University of Adelaide has developed an accurate method for controlling optical circuits in photonic integrated circuits the size of a fingernail. This research, published in the journal Optica, builds on the work of the same team that recently created the world’s first self-calibrating photonic circuit.

Photonics, the use of light particles to store and transmit information, is a booming field that supports our need to create faster, better, more efficient and sustainable technology. Programmable photonic integrated circuits (PICs) offer diverse signal processing functions within a single chip and present promising solutions for applications ranging from optical communications to artificial intelligence.

Whether it’s downloading movies or keeping a satellite on course, photonics is radically changing the way we live, revolutionizing the processing power of large-scale equipment on a chip the size of a human fingernail.

Earlier this year, researchers at Monash University, RMIT and the University of Adelaide developed an advanced photonic circuit that could transform the speed and scale of photonics technology. However, as the scale and complexity of PICs increases, characterizing, and therefore calibrating, them becomes increasingly challenging.

“We have added a common reference path to the chip, which allows stable and accurate measurements of the lengths (phases, time delays) and losses of the ‘worker’ paths.”

Monash University researcher Professor Mike Xu.

Previously, chips have been measured/calibrated by connecting them to complex and expensive external equipment (called vector network analyzers); however, connections to them introduce phase errors caused by vibrations and temperature changes. By placing the reference on the actual chip, the measurement is immune to these phase errors.

“By inventing a new method, the fractional delay method, we have been able to separate the desired information from the undesired information, allowing for more accurate applications.”

Credits: Monash University