High-performance and scalable on-chip digital Fourier transform spectroscopy

Abstract

On-chip spectrometers have the potential to offer dramatic size, weight, and power advantages over conventional benchtop instruments for many applications such as spectroscopic sensing, optical network performance monitoring, hyperspectral imaging, and radio-frequency spectrum analysis. Existing on-chip spectrometer designs, however, are limited in spectral channel count and signal-to-noise ratio. Here we demonstrate a transformative on-chip digital Fourier transform spectrometer that acquires high-resolution spectra via time-domain modulation of a reconfigurable Mach-Zehnder interferometer. The device, fabricated and packaged using industry-standard silicon photonics technology, claims the multiplex advantage to dramatically boost the signal-to-noise ratio and unprecedented scalability capable of addressing exponentially increasing numbers of spectral channels. We further explore and implement machine learning regularization techniques to spectrum reconstruction. Using an ‘elastic-D1’ regularized regression method that we develop, we achieved significant noise suppression for both broad (>600 GHz) and narrow (<25 GHz) spectral features, as well as spectral resolution enhancement beyond the classical Rayleigh criterion.

On‐Chip Measurement of Photoluminescence with High Sensitivity Monolithic Spectrometer

“…[ 11–14 ] In such devices, the primary shortcoming lies in key sensor performance metrics, including sensitivity and resolution, scale inversely with the effective optical path length, and light–matter interaction volume. [ 3,15–17 ] As a consequence, simple size down‐scaling of conventional spectroscopic sensor designs makes it against the urgent need of on‐chip probing and characterizing a small amount of light emission, such as measuring photoluminescence (PL), Raman analysis, and single particle scattering.…”

Ultra-high resolution and broadband chip-scale speckle enhanced Fourier-transform spectrometer

“…If the number of measurements is smaller than the wavelength points to be reconstructed, the system of linear equations is underconstrained. Such constrained linear equations can be solved using least square minimization [22], such as the elastic-net regularization technique [11],…”

“…A detailed analysis on the signal reconstruction technique and the effect of regularization on computational spectrometers are given in Refs. [11,24].…”

“…Silicon-on-insulator (SOI) discrete Fourier transform (DFT) [7][8][9][10][11] and multimode waveguide (MMW) based speckle spectrometers [12][13][14][15][16] are two promising architectures. Despite their versatile performance, both technologies suffer from a bandwidth-resolution tradeoff [8][9][10]17].…”

“…Similarly, the spectral resolution of a speckle spectrometer derived from a MMW is inversely proportional to its length and its bandwidth is given by ∆λ ∼ (N m − 1)δλ, where the finesse is set by the number of distinct speckle modes (N m ) available for the measurement [17]. As constructing a single spectrometer with a large finesse will require fabricating thousands of interferometers or spectral multiplexing or other exotic configurations, the finesses of the current state-of-the art * uttam.paudel@aero.org chip-scale DFT and MMW speckle devices are limited to few hundred [7][8][9][10][11][12][13][14][15][16] thus a larger finesse device would be highly desirable.…”