Ultrafast optical imaging plays a key role in capturing transient time-evolving phenomena occurring on extremely fast timescales, driving breakthroughs in fields ranging from physics to biology. Conventional ultrafast imaging techniques, such as compressed ultrafast photography (CUP), can record transient events at hundreds of trillions of frames per second using chirped ultrashort pulses. However, these systems are usually large in size, limiting their versatility and practical use. How can ultrafast imaging systems be made more compact, reliable, and versatile without sacrificing performance? To address this issue, this study proposes integrating advanced nanophotonics, compressed sensing, and deep learning to develop single-exposure compressed ultra-compact femtosecond photography (CUF). The simulation shows that by utilizing a super-dispersive metalens, CUF combines focusing and dispersion functions in a compact device to achieve single-exposure ultrafast imaging, providing a transformative solution to overcome the limitations of conventional CUP technology in terms of system size. This work was recently published in Ultrafast Science and featured as the cover story.
Compressed ultrafast photography (CUP), invented in 2014, is a powerful single-shot ultrafast optical imaging technique that innovatively synergizes compressed sensing (CS) with streak imaging. CUP can record transient events at a rate of hundreds of trillions of frames per second. The working principle of CUP includes data acquisition and subsequent image reconstruction. During data acquisition, light from a dynamic scene is recorded in a two-dimensional measurement image through a compressed sensing method that includes spatial encoding, time shearing, and spatiotemporal integration. Subsequently, CUP is able to reconstruct a video of the instantaneous dynamic scene by algorithmically processing the recorded image. Despite its powerful ability to capture transient events, existing CUP-based systems are usually bulky and prone to optical misalignment, hindering their use in research and commercial scenarios.
A research team led by Professor Jinyang Liang and Professor Luca Razzari of the Institut National de la Recherche Scientifique (INRS) at the University of Quebec, Canada, has verified the feasibility of a single-shot real-time ultrafast imaging system based on a metalens through theoretical research. This newly proposed imaging paradigm is called compressed ultra-compact femtosecond photography (CUF). The technology integrates a super-dispersive metalens, an innovative optical element that combines the focusing and dispersive functions of traditional optics into a single ultra-compact device. Unlike traditional metalenses, which are optimized for a wide visible light spectrum but have relatively low spectral resolution, the CUF system is designed for actively illuminated CUPs, offering a compact alternative without compromising performance.
The research team designed a transmissive binary coding pattern to achieve uniform pixel intensity distribution, thereby enhancing the dynamic range of the system. To ensure optimal light transmission, the metalens uses a polarization-insensitive cylindrical meta-atom design that provides a full 2π phase coverage with a transmittance of about 90%. CUF uses this metalens together with the coding pattern to capture both temporal and spatial information in a single compressed recorded photo. The final dynamic event is reconstructed using a neural network-based algorithm. The authors simulated and tested the performance of the CUF system using three sensor configurations with different pixel sizes, demonstrating its powerful capabilities. "We envision CUF as a powerful tool for real-time monitoring of 2D transient light-matter interactions. Our demonstration of CUF's ultrafast imaging capabilities involved simulating Cherenkov waves propagating through nonlinear crystals and instantaneously chirped pulses that are tilted forward when propagating on a negative resolution target", explains Miguel Marquez, the co-first author of this work.
Summary and Outlook:
This research paves the way for the implementation of CUF in a variety of scientific and industrial applications, from fundamental physics research to advanced femtosecond photography applications. "We are excited about CUF's potential because it can reduce the size and complexity of single-shot ultrafast imaging devices. We believe that it will improve the stability and accuracy of measurements, making ultrafast imaging more accessible and applicable to more scenarios than ever before", says Jinyang Liang, a co-corresponding author of the article. CUF is expected to provide a versatile platform with scalable spatial resolution by combining it with various imaging modes such as microscopes and telescopes, as well as various CCD/sCMOS cameras.
Author Introduction:
First authors: Miguel Marquez and Giacomo Balistreri
Corresponding authors:
Jinyang Liang is an Associate Professor at the Institut National de la Recherche Scientifique (INRS)–Université du Québec, Canada. He holds Canada Research Chair in Ultrafast Computational Imaging (Tier II). He received his Ph.D. degree in Electrical Engineering from the University of Texas at Austin in 2012. From 2012 to 2017, he was a Postdoctoral Trainee with Washington University in St. Louis and the California Institute of Technology. His research interests include ultrafast imaging, computational optics, optical physics, and biophotonics.
Luca Razzari is a Full Professor at the Institut National de la Recherche Scientifique (INRS)–Université du Québec, Canada. He received his M.Sc (2001) and Ph.D (2004) degrees in Electronic Engineering from the University of Pavia (Italy). He completed part of his Ph.D research at the Institut d'Optique in Orsay, France (2004). From 2006 to 2010, he made his first move to Canada as a Marie Curie Fellow in the Ultrafast Optical Processing Group at the Institut National de la Recherche Scientifique – Centre Energie, Matériaux et Télécommunications (INRS-EMT). From 2010 to 2012, he was with the Nanostructures Department at the Italian Institute of Technology (IIT) in Genoa, Italy.
