Replacing lasers with less complex light sources could boost performance in some optical applications, such as light-driven AI technologies, new research suggests.
The discovery, made by the Universities of Oxford, Muenster, Heidelberg, and Ghent, opens the way for cheaper, and less energy-intensive light sources for applications that have typically relied on expensive, high-spec lasers.
The insight might also apply to optical communications, particularly in the emerging optical interconnect technology space.
Low coherence light sources function better in specific cases
The properties of a light source are often characterised by coherence: the degree to which the waves of light are consistent with each other in time and space. While low coherence light sources, such as the sun and light bulbs, emit light in a wide range of wavelengths, high quality engineered light sources (such as lasers) have a very narrow wavelength range and typically appear as a single colour.
The capability to engineer and use highly coherent light (lasers) has been a bedrock of modern applications such as optical communications, lidar, remote sensing technologies, and medical imaging technologies. Thus, it was natural to assume that using more coherent light sources enhances system performance and device functionalities, for instance, by enabling higher resolution and more precise measurements.
This new discovery challenges this conventional wisdom and reveals that low coherence light sources can actually function better in specific cases, such as a photonic AI accelerator – an emerging technology where photons are used instead of electrons to perform AI computations.
The team used a partially coherent light source by harnessing a narrow portion of the spectrum of incoherent light produced by an electrically-pumped erbium-doped fibre amplifier (a device used in optical communication to boost the strength of light signals travelling through optical fibres). This partially coherent light was evenly split and distributed into different input channels for a parallel AI computational array. Using such a light source, the parallelism of AI computation is surprisingly enhanced by N times in a photonic accelerator with N input channels.
Boost in computing power could be “transformational”
As a test case, the team used this system to identify Parkinson’s disease patients by analysing how they walked, achieving a classification accuracy of over 92%. The team also demonstrated how a simple system using only one partially coherent light source with 9 input channels could be used to perform high-speed AI tasks at around 100 billion operations per second. Normally, such a speed – equivalent to playing more than 2 hours of 4K video in one second – could only be achieved in a coherent photonic AI accelerator with multiple separate coherent lasers.
Ultimately, removing the need to add additional light sources could prove transformational in boosting computational power, as Dr Bowei Dong at the Department of Materials, University of Oxford, explained: “The benefit of using ‘poorer’ light sources has a scaling effect. You can run your AI models 100 times faster compared to a laser system, if the photonic accelerator scales to 100 input channels.”
The study has recently been published in Nature.
Credit for main image: sdecoret/Shutterstock
