Dr. Elena Goi from IPC Made New Acievements in Optical Research

Recently, Dr.Elena Goi, Research Fellow from Institute of Photonic Chips ( IPC ) published the latest research titled “holographic nanostructures on CMOS chips for direct retrieval of Zernike-based pupil functions” in Nature Communications as the first author. It made the first experimental demonstration of direct extraction of arbitrary pupil phase by optical diffractive neural network integrated in a single compact photoelectric sensor. The corresponding author of the paper was Academician Gu Min and Elena Goi from IPC; USST was the first unit. Academician Gu Min pointed out that the breakthrough can be applied in precision medical technology.
Retrieving the phase distribution of an incoming wavefront is a pro blem of central interest for imaging systems across scales. On one hand, this phase information can be used in the context of phase contrast imaging, the characterization of near-transparent specimen in biology and medical research1 , which has led to significant advances in live cell monitoring2 and tissue imaging3 . On the other hand, unwanted distortions of the wavefront result in the limited performance of imaging systems of any scale from microscopes to telescopes4,5 , which can be corrected for if known. The phase distribution across a wave front can thereby be conveniently described by Zernike polynomials6 , which were first introduced by Frits Zernike (1953 Nobel Prize in Phy sics) in 1934 to describe the diffracted wavefronts in phase contrast microscopy. The Zernike polynomials form a complete basis set of functions that are orthogonal over a circle of unit radius, and therefore their linear combination offer a mathematical description of arbitrary pupil phase distributions of an optical system while yielding minimum variance over a circular pupil.
Hence, Dr. Elena Goi presents a compact optical-electronic module based on multi-layered diffractive neural networks printed on imaging sensors, capable of directly retrieving Zernike-based pupil phase distributions from an incident point spread function. They demonstrate this concept numerically and experimentally, showing the direct pupil phase retrieval of superpositions of the first 14 Zernike polynomials. The integrability of the diffractive elements with CMOS sensors shows the potential for the direct extraction of the pupil phase information from a detector module without additional digital post-processing.
The research is granted by Shanghai Natural Science Foundation, Shanghai Rising-star Program, the Science and Technology Commission of Shanghai Municipality. and the Shanghai Frontiers Science Center Program.