Published in Science, the work details how the team used metasurfaces - nanoscale structures that interact with light at wavelength size-scales - to capture the polarisation. Current devices that produce similar results are bulky and expensive, but the Harvard device is about the size of a thumb. This means it could conceivably be installed in a smartphone, assisting in applications varying from machine vision and atmospheric chemistry to detecting objects that are camouflaged.
"If we want to measure the light's full polarisation state, we need to take several pictures along different polarisation directions," said first author Noah Rubin, from Harvard’s John A. Paulson School of Engineering and Applied Sciences (SEAS).
"Previous devices either used moving parts or sent light along multiple paths to acquire the multiple images, resulting in bulky optics. A newer strategy uses specially patterned camera pixels, but this approach does not measure the full polarisation state and requires a non-standard imaging sensor. In this work, we were able to take all of the optics needed and integrate them in a single, simple device with a metasurface."
The researchers designed a metasurface that uses an array of subwavelength spaced nanopillars to direct light based on its polarisation. The light then forms four images, each one showing a different aspect of the polarisation. Taken together, these give a full snapshot of polarisation at every pixel.
"This research is game-changing for imaging," said senior author Federico Capasso, the Robert L Wallace Professor of Applied Physics and Vinton Hayes Senior Research Fellow in Electrical Engineering at SEAS.
"Most cameras can typically only detect the intensity and colour of light but can't see polarisation. This camera is a new eye on reality, allowing us to reveal how light is reflected and transmitted by the world around us.
"This research opens an exciting new direction for camera technology with unprecedented compactness, allowing us to envision applications in atmospheric science, remote sensing, facial recognition, machine vision and more.”
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