Integrated reconstructive spectrometer with programmable photonic circuits
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 rapidl...
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Published in | Nature communications Vol. 14; no. 1; p. 6376 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
11.10.2023
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-023-42197-3 |