Researchers improve tunability in optical differentiation

A new technique may make it easier for researchers to create real-time images of microscopic samples by considering the waves that propagate through sample surfaces as light interacts with them.

Optical differentiation is a useful technique for analyzing images of microscopic samples in real time. Currently, however, it lacks the ability to fine-tune the resolution in the images it produces.

In a new article published in The European Physical Journal D, a team led by Jian Wu at the National University of Defense Technology in Changsha, China, proposes a new approach that enabled them to tune the wavelengths reflected from crystal samples. Their technique could allow researchers to extract far more detailed images of their samples, and would be especially useful for analyzing systems of cells and large molecules.

Optical differentiation involves calculating the rate of change in key properties of a light signal—including its intensity, phase, and amplitude—after it interacts with a sample. This is particularly useful for distinguishing features around sample edges, where there are sharp discontinuities in the brightness, color, and texture of the reflected light.

In their study, Wu’s team investigated the behavior of Bloch surface waves, which propagate along the surfaces of insulating materials with periodic crystal structures. By incorporating these waves into their calculations, the team found they could substantially improve the tuneability of the wavelengths reflected from the surface.

This was possible since Bloch wave propagation can be affected even by tiny variations in incoming wavelength, causing dramatic changes in the positions of reflected light beams. As a result, the team could calculate detailed image features in real time through a simple mathematical relationship between the incoming and reflected light, which accounts for changes in polarization and intensity as the light interacts with the sample.

In their future research, Wu’s team aims to extend their approach to 2D crystal samples, potentially bringing its practical application a step closer to reality.