Abstract

Optical spectroscopic sensors are a powerful tool to reveal light-matter interactions in many fields. Miniaturizing the currently bulky spectrometers has become imperative for the wide range of applications that demand in situ or even in vitro characterization systems, a field that is growing rapidly. In this paper, we propose a novel integrated reconstructive spectrometer with programmable photonic circuits by simply using a few engineered MZI elements. This design effectively creates an exponentially scalable number of uncorrelated sampling channels over an ultra-broad bandwidth without incurring additional hardware costs, enabling ultra-high resolution down to single-digit picometers. Experimentally, we implement an on-chip spectrometer with a 6-stage cascaded MZI structure and demonstrate <10 pm resolution with >200 nm bandwidth using only 729 sampling channels. This achieves a bandwidth-to-resolution ratio of over 20,000, which is, to our best knowledge, about one order of magnitude greater than any reported miniaturized spectrometers to date.

Recent years have seen a growing need for miniaturized spectroscopic tools. Here, authors present a novel integrated spectrometer with programmable photonic circuits, achieving record-high resolution and bandwidth via only a few filtering components.

Details

Title
Integrated reconstructive spectrometer with programmable photonic circuits
Author
Yao, Chunhui 1 ; Xu, Kangning 2 ; Zhang, Wanlu 1 ; Chen, Minjia 1   VIAFID ORCID Logo  ; Cheng, Qixiang 3   VIAFID ORCID Logo  ; Penty, Richard 1 

 University of Cambridge, Centre for Photonic Systems, Electrical Engineering Division, Department of Engineering, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000 0001 2188 5934) 
 GlitterinTech Limited, Xuzhou, China (GRID:grid.5335.0) 
 University of Cambridge, Centre for Photonic Systems, Electrical Engineering Division, Department of Engineering, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000 0001 2188 5934); GlitterinTech Limited, Xuzhou, China (GRID:grid.5335.0) 
Pages
6376
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2875648278
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.