Abstract
Multimode fiber (MMF) spectrometers suffer from the resolution-bandwidth trade-off due to the limited spatial speckle information used for spectral recovery. We demonstrate a design of an MMF spectrometer with scalable bandwidth using space-division multiplexing. A multicore fiber (MCF) is used to integrate with the MMF. The spatial degrees of freedom at the input are exploited to provide the independent speckle pattern, thus multiplying the spatial information and scaling the bandwidth. We have experimentally achieved 30 nm bandwidth with 0.02nm resolution at wavelength 1550 nm, only using 3 cores of a 7-core fiber and a single MMF. An efficient algorithm is developed to reconstruct the broadband sparse and dense spectrums accurately. The approach can enhance the operating bandwidth of MMF spectrometers without sacrificing the resolution, and simultaneously ensure the system complexity and stability.
Highlights
Spectrometers are widely used in sensing and measuring applications
Multimode fiber (MMF) spectrometers suffer from the resolution-bandwidth trade-off due to the limited spatial speckle information used for spectral recovery
We demonstrate a design of an multimode fiber (MMF) spectrometer with scalable bandwidth using space-division multiplexing
Summary
Spectrometers are widely used in sensing and measuring applications. The conventional spectrometers based on spatial dispersion use gratings or prisms to provide the linear mapping in which the spectral and spatial match oneto-one. An on-chip spectrometer has been completed using disordered photonic crystal, and an fm-resolved wavelength detection is achieved by a special integrating sphere.. An on-chip spectrometer has been completed using disordered photonic crystal, and an fm-resolved wavelength detection is achieved by a special integrating sphere.14 They take the advantages of the compact size, light weight, and low cost due to the high space utilization and easy fabrication. Similar to the grating spectrometer, their spectral resolutions scale with the longitudinal pathlength of scattering and their operating bandwidth is limited to the transverse size which determines the spatial information capacity. The number of spectral channels is determined by the amount of spatial information of speckle patterns, which. The speckle patterns corresponding to the different input conditions are captured sequentially and combined for spectrum reconstruction. We have developed an efficient spectral reconstruction algorithm that has a high reconstruction accuracy against the measurement noise
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