With the rapid development of information technology, artificial intelligence and large-scale models have exhibited exceptional performance and widespread applications. Photonic hardware offers a prom...

The speed, dimensions, and immersive quality of communication have been continuously transformed by advances in information technology: from letters to telegraphs, telephones to video calls, and on-sc...

Correlated twin combs generated by seeded four-wave mixing enable quantum correlation-enhanced dual-comb spectroscopy. High signal-to-noise ratio and comb-line-resolvable spectra in the mid-infrared molecular fingerprinting region is achieved by bridging intensity-difference squeezing and dual-comb spectroscopy.

Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The emergence of reconstructive spectrometers represents a transformative leap in spectral analysis, combining miniaturized encoding hardware with advanced computational algorithms to revolutionize conventional approaches. These devices encode unknown spectral data into measurable signals, for which sophisticated algorithms then decode to reconstruct the original spectrum with high fidelity—all achieved within an ultra-compact footprint. In this review, we first establish the mathematical foundations governing spectral encoding and decoding. We then provide a detailed analysis of encoding strategy and state-of-the-art decoding techniques, followed by recent breakthroughs in hardware design for optimized spectral reconstruction systems. Finally, we address key challenges and future opportunities, offering insights into how reconstructive spectrometers may redefine spectroscopy beyond traditional laboratory settings.

Acoustic perception is a fairly basic but extraordinary feature in nature, relying on multidimensional signal processing for detection, localization, and recognition. Replicating this capability in compact artificial systems, however, remains a formidable challenge due to limitations in scalability, sensitivity, and integration. Here, imitating the auditory system of insects, we introduce an opto-acoustic perception paradigm using fully-stabilized dual-soliton microcombs. By integrating digitally stabilized on-chip dual-microcombs, silicon optoelectronics and bionic fiber-microphone arrays on a single platform, we achieve parallelized interrogation of over 100 sensors. Leveraging the low-noise, multi-channel coherence of fully-stabilized soliton microcombs, this synergy enables ultra-sensitive detection of 29.3 nPa/Hz1/2, sub centimeter precise localization, real-time tracking and identification for versatile acoustic targets. Bridging silicon photonics, optical fiber sensing and intelligent signal processing in a chiplet microsystem, our scheme delivers out-of-lab deployable capability on autonomous robotics. This work not only deepens the understanding of frequency comb science, but also establishes a concept of dual-comb-driven sensor networks as a scalable foundation for next-generation opto-acoustic intelligence.

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive ...