Research Bits: Feb. 6

Photonics: Circuit laser printer; light propagation; optical neural network.

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Laser printer for photonic circuits

Researchers from the University of Washington and University of Maryland propose a faster, cheaper way to fabricate and reconfigure photonic integrated circuits. The method uses a laser writer to write, erase, and modify circuits into a thin film of phase-change material similar to what is used for recordable CDs and DVDs.

The researcher say the method could be particularly useful for students and researchers with limited access to nanofabrication facilities, as the low-cost device is about the size of a conventional desktop laser printer and could be deployed in labs, classrooms, and garage workshops.

A research team led by UW ECE and Physics Professor Mo Li has invented a new way to print and reconfigure photonic integrated circuits (microchips) using a speedy, low-cost device about the size of a conventional desktop laser printer. This device could enable students and researchers to bypass expensive nanofabrication facilities and produce photonic integrated circuits almost anywhere. The technology also has possible industrial applications. (Credit: Haoquin Deng / UW ECE)

“Being able to write a whole photonic circuit using only one single step, without a complicated fabrication process, is really exciting. And the fact that we can make any modification to any part of the circuit in our own lab and rewrite and redo it is amazing,” said Changming Wu, a graduate student at UW, in a release. “It’s a matter of minutes versus a full, day-long process. It’s a huge relief to be able to finish the whole fabrication process within a few minutes instead of what often is several days or even a week.”

The team plans to build a prototype with optimized performance and work to reduce optical loss in the phase-change material they are using through further research in material science and laser writing techniques. [1]

Light propagation

Researchers from Technion investigated how light propagates in silicon-based photonic integrated circuits. The method provides real-time images and video recordings of the light inside the photonic chip, without having to damage the chip and without losing any data.

The team harnessed the natural nonlinear optical characteristics of silicon to map the light’s propagation without requiring an invasive action of any sort, which perturbs or alters the chip. This process includes mapping the light waves’ electric field and defining the waveguides and beam splitters that affect the light’s movement.

They hope the process can be deployed to improve the design, production, and optimization of photonic chips. The method can be used to reveal the interference pattern within multimode interferometric splitters, detect enhancements occurring inside resonators, visualize the operation of active components such as modulators and lasers, and study nonlinear phenomena such as frequency combs and solitons. [2]

Optical neural network

Researchers from EPFL developed an optical neural network architecture that combines light propagation inside multimode fibers with a small number of digitally programmable parameters to achieve the same accuracy performance on image classification tasks with fully digital systems with more than 100 times more programmable parameters.

The approach uses wavefront shaping to precisely control the propagation of ultrashort pulses in multimode fibers. This allows for the implementation of nonlinear optical computations with microwatts of average optical power.

“In this study, we found out that with a small group of parameters, we can select a specific set of model weights from the weight bank that optics provides and employ it for the aimed computing task. This way, we used naturally occurring phenomena as a computing hardware without going into the trouble of manufacturing and operating a device specialized for this purpose,” said Ilker Oguz of EPFL in a statement. [3]

References

[1] Changming Wu et al. , Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films. Sci. Adv. 10, eadk1361 (2024). https://doi.org/10.1126/sciadv.adk1361

[2] Matan Iluz, Kobi Cohen, Jacob Kheireddine, Yoav Hazan, Amir Rosenthal, Shai Tsesses, and Guy Bartal, “Unveiling the evolution of light within photonic integrated circuits,” Optica 11, 42-47 (2024) http://dx.doi.org/10.1364/OPTICA.504397

[3] Ilker Oguz, Jih-Liang Hsieh, Niyazi Ulas Dinc, Uğur Teğin, Mustafa Yildirim, Carlo Gigli, Christophe Moser, and Demetri Psaltis “Programming nonlinear propagation for efficient optical learning machines,” Advanced Photonics 6(1), 016002 (25 January 2024). https://doi.org/10.1117/1.AP.6.1.016002



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