Universal linear intensity transformations using spatially incoherent diffractive processors  

作　　者：Md Sadman Sakib Rahman Xilin Yang Jingxi Li Bijie Bai Aydogan Ozcan 

机构地区：[1]Electrical and Computer Engineering Department,University of California,Los Angeles,CA 90095,USA [2]Bioengineering Department,University of California,Los Angeles,CA 90095,USA [3]California NanoSystems Institute(CNSI),University of California,Los Angeles,CA 90095,USA

出　　处：《Light(Science & Applications)》2023年第9期1830-1856,共27页光（科学与应用)（英文版）

基　　金：The Ozcan Research Group at UCLA acknowledges the support of U.S.Department of Energy(DOE),Office of Basic Energy Sciences,Division of Materials Sciences and Engineering under Award#DE-SC0023088.

摘　　要：Under spatially coherent light,a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view(FOVs)if the total number(N)of optimizable phase-only diffractive features is≥~2N_(i)N_(o),where Ni and No refer to the number of useful pixels at the input and the output FOVs,respectively.Here we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output FOVs.Under spatially incoherent monochromatic light,the spatially varying intensity point spread function(H)of a diffractive network,corresponding to a given,arbitrarily-selected linear intensity transformation,can be written as H(m,n;m′,n′)=|h(m,n;m′,n′)|^(2),where h is the spatially coherent point spread function of the same diffractive network,and(m,n)and(m′,n′)define the coordinates of the output and input FOVs,respectively.Using numerical simulations and deep learning,supervised through examples of input-output profiles,we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N≥~2N_(i)N_(o).We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths,operating simultaneously.Finally,we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination,achieving a test accuracy of>95%.Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.

关 键 词：spatially INTENSITY ARBITRARY 

分 类 号：O43[机械工程—光学工程]