Nanophotonic media for artificial neural inference

作     者：ERFAN KHORAM ANG CHEN DIANJING LIU LEI YING QIQI WANG MING YUAN ZONGFU YU 

作者机构：Department of Electrical and Computer EngineeringUniversity of Wisconsin MadisonMadisonWisconsin53706USA Department of Aeronautics and AstronauticsMassachusetts Institute of TechnologyCambridgeMassachusetts02139USA Department of StatisticsColumbia UniversityNew YorkNew York10027USA 

出 版 物：《Photonics Research》 (光子学研究（英文版）)

年 卷 期：2019年第7卷第8期

页      面：823-827页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Defense Advanced Research Projects Agency(DARPA)(young faculty award) 

主　　题：image simulation Nanophotonic media 

摘      要：We show optical waves passing through a nanophotonic medium can perform artificial neural *** information is encoded in the wavefront of an input light. The medium transforms the wavefront to realize sophisticated computing tasks such as image recognition. At the output, the optical energy is concentrated in well-defined locations, which, for example, can be interpreted as the identity of the object in the *** computing media can be as small as tens of wavelengths and offer ultra-high computing density. They exploit subwavelength scatterers to realize complex input/output mapping beyond the capabilities of traditional nanophotonic devices.