Applied Physics Seminar
Metasurface Computational Imaging
Abstract: Modern image sensors consist of systems of cascaded and bulky spherical optics for imaging with minimal aberrations. While these systems provide high quality images, the improved functionality comes at the cost of increased size and weight. One route to reduce a system's complexity is via computational imaging, in which much of the aberration correction and functionality of the optical hardware is shifted to post-processing in the software realm. Alternatively, a designer could miniaturize the optics by replacing them with diffractive optical elements, which mimic the functionality of refractive systems in a more compact form factor. Metasurfaces are an extreme example of such diffractive elements, in which quasiperiodic arrays of resonant subwavelength optical antennas impart spatially-varying changes on a wavefront. While separately both computational imaging and metasurfaces are promising avenues toward simplifying optical systems, a synergistic combination of these fields can further enhance system performance and facilitate advanced capabilities. In this talk, I will present a method to combine these two techniques to perform full-color imaging across the whole visible spectrum . I will also discuss the use of computational techniques to design new metasurfaces , and using metasurfaces to perform computation on wavefronts, with applications in optical information processing and sensing.
 S. Colburn, A. Zhan, and A. Majumdar, "Metasurface optics for full-color computational imaging," Science Advances, vol. 4, 2018.
 A. Zhan, T. K. Fryett, S. Colburn, and A. Majumdar, "Inverse design of optical elements based on arrays of dielectric spheres," Applied Optics, vol. 57, pp. 1437-1446, 2018/02/20 2018.
More about the Speaker: Prof. Arka Majumdar is an Assistant Professor in the departments of Electrical and Computer Engineering and Physics at the University of Washington, Seattle. He received his B. Tech. degree from the Indian Institute of Technology, Kharagpur in 2007, where he was honored with the President's Gold Medal. Majumdar completed his master's degree (2009) and Ph.D. (2012) in Electrical Engineering at Stanford University. He spent one year at the University of California, Berkeley (2012-13) and Intel Labs as a postdoc in Santa Clara, CA (2013-14). His research interests include developing a hybrid integrated nanophotonic platform using emerging material systems for applications in ultra-low power optical information science, imaging, and microscopy. Majumdar is the recipient of the Young Investigator Award from the Air Force Office of Scientific Research (2015), Intel early career faculty award (2015), Alfred P. Sloan research fellowship for physics (2018) and NSF CAREER Award (2019).
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