Benchmarking Reconstructive Spectrometer with Multiresonant Cavities

Recent years have seen the rapid development of miniaturized reconstructive spectrometers (RSs), yet they still confront a range of technical challenges, such as bandwidth/resolution ratio, sensing speed, and/or power efficiency. Reported RS designs often suffer from insufficient decorrelation between sampling channels, which, in essence, is due to inadequate engineering of sampling responses. This in turn results in poor spectral-pixel-to-channel ratios (SPCRs), typically restricted at single digits. So far, there lacks a general guideline for manipulating RS sampling responses for the effectiveness of spectral information acquisition. In this study, we shed light on a fundamental parameter from the compressive sensing (CS) theory-the average mutual correlation coefficient <i>ν</i>-and provide insight into how it serves as a critical benchmark in RS design. To this end, we propose a novel RS design with multiresonant cavities, consisting of a series of partial reflective interfaces. Such multicavity configuration allows the superlative optimization of sampling matrices to achieve minimized <i>ν</i>. Experimentally, we implement a single-shot, dual-band RS on a SiN platform, realizing an overall operation bandwidth of 270 nm and a <0.5 nm resolution with only 15 sampling channels per band. This leads to a record high SPCR of 18.0. Moreover, the proposed multicavity design can be readily adapted to various photonic platforms, ranging from optical fibers to free-space optics. For instance, we showcase that by employing multilayer coatings, an ultrabroadband RS can be optimized to exhibit a 700 nm bandwidth with an SPCR of over 100.