All Optical Digital to Analog Converter

Using a silicon photonic chip platform, Volker J. Sorger and other researchers at the George Washington University and University of California, Los Angeles, have created an all optical digital-to-analog converter. It does not require the signal to be converted in the electrical domain. It can have higher data-processing capabilities while acting on optical data, interfacing to digital systems, and performing in a compact footprint, with both short signal delay and low power consumption.

The new converters can advance next-generation data processing hardware with high relevance for data centers, 6G networks, artificial intelligence and more.

Advanced Photonics Research – Electronic Bottleneck Suppression in Next-Generation Networks with Integrated Photonic Digital-to-Analog Converters

Digital-to-analog converters (DAC) are indispensable functional units in signal processing instrumentation and wide-band telecommunication links for both civil and military applications. As photonic systems are capable of high data throughput and low latency, an increasingly found system limitation stems from the required domain crossing such as digital to analog and electronic to optical. A photonic DAC implementation, in contrast, enables a seamless signal conversion with respect to both energy efficiency and short signal delay, often requiring bulky discrete optical components and electric–optic transformation, hence introducing inefficiencies. Herein, a novel coherent parallel photonic DAC concept along with a 4-bi t experimental prototype capable of performing this DAC without optic–electric–optic domain crossing is introduced. This new paradigm guarantees a linear intensity weighting among bits when operating at high sampling rates (50 GHz), featuring an exceptional sampling efficiency (over 100 GS per joule) and small footprint (0.1 square millimeters) in an 8-bit implementation. Importantly, this photonicDAC enables seamless interfaces of next-generation data processing hardware with high relevance in data centers, task-specific compute accelerators such as neuromorphic engines, and network edge processing applications.

SOURCES- George Washington University, Advanced Photonics Research
Written By Brian Wang,