When optoelectronics and AI meet

Using machine-learning and an integrated photonic chip, researchers from INRS (Canada) and the University of Sussex (UK) can now customize the properties of broadband light sources. Also called “supercontinuum,” these sources are at the core of new imaging technologies and the approach proposed by the researchers will bring further insight into fundamental aspects of light-matter interactions and ultrafast nonlinear optics. The work is published in the journal Nature Communicationson November 20, 2018.

Such powerful and complex optical systems, and their associated processes, currently form the building blocks of widespread applications spanning from laser science and metrology to advanced sensing and biomedical imaging techniques. To keep pushing the limits of this optical technology, more tailoring capability of the light properties is needed.

Diverse patterns of femtosecond optical pulses can be prepared and judiciously manipulated. With such a large number of combinations to seed an optical system known to be highly sensitive to its initial conditions, the researchers have turned to a machine-learning technique in order to explore the outcome of light manipulation.

In particular, they have shown that the control and customization of the output light is indeed efficient, when conjointly using their system and a suitable algorithm to explore the multitude of available light pulse patterns used to tailor complex physical dynamics.

These exciting results will impact fundamental as well as applied research in a number of fields, as a large part of the current optical systems rely on the same physical and nonlinear effects as the ones underlying supercontinuum generation.

When optoelectronics and AI meet

News Source: http://www.inrs.ca/

Post time: Nov-30-2018
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