Milestone in quantum sensing: A prototype quantum optical microscope

UCalgary researcher Shabir Barzanjeh leads collaborative microscope project, delivering high-resolution images under ultra-low light
Red more here:https://nrc.canada.ca/en/stories/under-microscope-quantum-sensing-biochemical-applications?utm_campaign=quantumsensingsuccessstory&utm_medium=smo&utm_source=lnkn-e
and
https://ucalgary.ca/news/milestone-quantum-sensing-prototype-quantum-optical-microscope

Congratulations to Our Recent Scholarship Recipients!

Three of our outstanding graduate students have received awards recognizing their academic achievements and providing valuable support for their ongoing studies. Join us in congratulating Mayte Li-Gomez (T. Chen Fong Doctoral Entrance Scholarship), Armin Tabesh (Alberta Innovates), and Brendan MacKay (Alberta Graduate Excellence Scholarship)!

Congratulations MSc. Armin Tabesh!

29 August, 2023 – Shabir Barzanjeh

Big congratulations to now MSc. Armin Tabesh, who has successfully defended his Master’s thesis on Cryogenic Electromechanical System this past week.

As the first student to be admitted into the IHQC Lab, this is a huge achievement for our research group as we further expand our research achievements. He will continue with the IHQC team as he further pursues his Ph.D. on the beginning of September 2023.

Advancements in Quantum Imaging

14 July, 2023 – Shabir Barzanjeh

Our paper Quantum enhanced probing of multilayered samples, done in collaboration with researchers in Mexico and Colombia, has been published in Physical Review Research.

Quantum sensing exploits quantum phenomena to enhance the detection and estimation of classical parameters of physical systems and biological entities, particularly so as to overcome the inefficiencies of its classical counterparts. A particularly promising approach within quantum sensing is quantum optical coherence tomography which relies on nonclassical light sources to reconstruct the internal structure of multilayered materials. Compared to traditional classical probing, quantum optical coherence tomography provides enhanced-resolution images and is unaffected by even-order dispersion. One of the main limitations of this technique lies in the appearance of artifacts and echoes, i.e., fake structures that appear in the coincidence interferogram, which hinder the retrieval of information required for tomography scans.

Here, by utilizing a full theoretical model, in combination with a fast genetic algorithm to postprocess the data, we successfully extract the morphology of complex multilayered samples and thoroughly distinguish real interfaces, artifacts, and echoes. We test the effectiveness of the model and algorithm by comparing its predictions to experimentally generated interferograms through the controlled variation of the pump wavelength. Our results could potentially lead to the development of practical high-resolution probing of complex structures and noninvasive scanning of photodegradable materials for biomedical imaging/sensing, clinical applications, and materials science.