New work sheds light on nonlinear encoding in diffractive optical processors based on linear materials

UCLA researchers have conducted an in-depth analysis of nonlinear information encoding strategies for diffractive optical processors, offering new insights into their performance and utility. Their study, published in Light: Science & Applications, compared simpler-to-implement nonlinear encoding strategies that involve phase encoding with the performance of data repetition-based nonlinear information encoding methods, shedding light on their advantages and limitations in the optical processing of visual information.