July 14, 2023

UCalgary researchers make strides toward quantum sensing technology

Algorithn could be useful for biomedical imaging and sensing, clinical applications, and materials science
Experimental setup used for quantum sensing.
Experimental setup used for quantum sensing. Mayte Li-Gomez

Researchers at the University of Calgary have made significant strides toward developing high-resolution quantum sensing, a breakthrough that continues the university’s trajectory as a world centre of excellence in quantum research and technology.

Led by Dr. Shabir Barzanjeh, PhD, the research team, including Mayte Li-Gomez and Taras Hrushevskyi, are based in the Department of Physics and Astronomy. Their work — done in collaboration with researchers in Mexico including Pablo Yepiz and Afred U’ren — has been published in Physical Review Research.

One of the most significant hurdles in the realm of quantum physics is the challenge of effectively distinguishing the signal from the noise and enhancing the signal-to-noise ratio. However, a potential solution lies in the utilization of entangled photon pairs.

Entanglement explained

Entanglement, a fundamental principle of quantum mechanics, establishes a profound correlation between the properties of two or more particles, regardless of their physical separation. In this entangled state, the state of one particle becomes reliant on the state of the other. Harnessing the unique properties of entanglement presents an invaluable resource for delving into the fundamental aspects of quantum mechanics and facilitating groundbreaking applications in the fields of quantum sensing and imaging.

In their breakthrough research on quantum sensing, Barzanjeh and his team have developed an experimental method, empowered by a genetic algorithm, which capitalizes on quantum entanglement to achieve non-destructive imaging of micrometre-sized samples. Genetic algorithms, as their name implies, take inspiration from evolutionary natural selection processes and apply a series of heuristics to find optimal solutions to a given problem.

Through the use of entangled light, the researchers successfully generated visual representations of the internal morphology of thin, multilayered samples adorned with intricate microscopic patterns. Specifically, the team opted for nanofabricated samples consisting of stacks of layers with thicknesses ranging from a few nanometres to hundreds of micrometres.

Imagine technique challenges

This imaging technique is not without its challenges, however. It encounters a significant obstacle manifested in the emergence of artifacts and echoes, wherein spurious structures appear in the final images, causing them to become fuzzy and lack clarity — akin to capturing a photo through a hazy camera lens.

By implementing quantum interferometric methods, the research team successfully formulated an extensive theoretical framework to anticipate the occurrence of these artifacts and echoes. Knowing where and when this interference will appear means it’s possible to cancel it out — and by leveraging this framework, the team’s Mexican collaborators devised the genetic algorithm to mitigate these distortions. The result is that these artifacts and echoes are automatically recognized and filtered out during the digital imaging process.

The researchers validated their initial results by using the proposed theoretical model and algorithm in a variety of test cases. As they imaged the various microscopic patterns on the samples, the results revealed a breakthrough — the entangled light combined with the algorithm was generating accurate, low-noise quantum images.

“The predictions of our approach closely matched the interferograms generated in the experiments,” Barzanjeh confirms.

Developing and implementing an algorithm to improve the clarity and precision of quantum sensing is a significant step toward scalable quantum optical coherence tomography (QOCT).

Excellent counterpoint to traditional imaging

“QOCT is like the quantum equivalent of the sensing equipment your optometrist uses to look at the insides of your eyes,” explains Li-Gomez. “But it uses much less light, and would be much less invasive.”

This kind of sensing would have a wide variety of applications and would make an excellent counterpart to traditional imaging. It would be useful for biomedical imaging and sensing, clinical applications, and materials science — allowing users to more easily see inside three-dimensional objects. Because it uses less far less light than classical imaging, it could also capture images of objects and tissues that are sensitive to light without damaging them.

“Imagine having an imaging device where you could flip a switch to go between classical and quantum imaging,” says Hrushevskyi. “You would have all the benefits of both — a complete picture of whatever you’re studying.”

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