Bio-Inspired Photonic Spectral Encoders

TL;DR

This paper introduces a bio-inspired, information-theoretic spectral encoding framework for compact spectrometers, enabling high-fidelity, reconfigurable spectral reconstruction with superior resolution and adaptability.

Contribution

It presents the first generic, reconfigurable spectral encoder based on Bayesian expected information gain, optimizing physical attributes for enhanced spectrometer performance.

Findings

Achieved ultra-high resolution of 6 pm in experiments.

Demonstrated broad measurable bandwidth of 30 nm.

Validated superior reconstruction fidelity across spectral regimes.

Abstract

Compact spectrometers promise to revolutionize sensing applications, offering a unique pathway to laboratory-grade analysis within a miniaturized footprint. Central to their performance is the encoding strategy to unknown spectra, which determines the efficiency, accuracy, and adaptability of spectral reconstruction. However, the absence of a unified spectral encoding framework has hindered the realization of optimal, high-performance compact spectrometers. We propose a transformative approach: an information-theoretic framework grounded in bio-inspired Bayesian expected information gain that defines the first generic light encoder for computational spectrometers. By optimizing three fundamental attributes at the lowest level of physical hierarchy, (1) orthogonality, (2) completeness, and (3) sparsity, we establish a design paradigm that transcends conventional encoding hardware limitations. We validate this paradigm with the first generic encoder capable of dynamically reconfiguring its response matrices. Experiments show superior reconstruction fidelity across diverse spectral regimes, enabling tunable spectral encoding tailored to varied input features. An ultra-high resolution of 6 pm and a broad measurable bandwidth of 30 nm are experimentally validated. By bridging the gap between theoretical encoding principles and reconfigurable hardware, our framework defines a coherent basis for future advances in compact spectrometry.