Mid-infrared photoacoustic brain imaging enabled by cascaded gas-filled hollow-core fiber lasers.

Significance: Extending the photoacoustic microscopy (PAM) into the mid-infrared (MIR) molecular fingerprint region constitutes a promising route toward label-free imaging of biological molecular structures. Realizing this objective requires a high-energy nanosecond MIR laser source. However, existing MIR laser technologies are limited to either low pulse energy or free-space structure that is sensitive to environmental conditions.

Synthesizing gas-filled anti-resonant hollow-core fiber Raman lines enables access to the molecular fingerprint region.

The synthesis of multiple narrow optical spectral lines, precisely and independently tuned across the near- to mid-infrared region, is a pivotal research area that enables selective and real-time detection of trace gas species within complex gas mixtures. However, existing methods for developing such light sources suffer from limited flexibility and very low pulse energy, particularly in the mid-infrared domain. Here, we introduce a concept that is based on the combination of an appropriate design of near-infrared fiber laser pump and cascaded configuration of gas-filled anti-resonant hollow-core fiber technology.

Laser: A two-domain photon-phonon laser.

The laser is one of the greatest inventions in history. Because of its ubiquitous applications and profound societal impact, the concept of the laser has been extended to other physical domains including phonon lasers and atom lasers. Quite often, a laser in one physical domain is pumped by energy in another.

Unsupervised full-color cellular image reconstruction through disordered optical fiber.

Recent years have witnessed the tremendous development of fusing fiber-optic imaging with supervised deep learning to enable high-quality imaging of hard-to-reach areas. Nevertheless, the supervised deep learning method imposes strict constraints on fiber-optic imaging systems, where the input objects and the fiber outputs have to be collected in pairs. To unleash the full potential of fiber-optic imaging, unsupervised image reconstruction is in demand.

Adaptive inverse mapping: a model-free semi-supervised learning approach towards robust imaging through dynamic scattering media.

Imaging through scattering media is a useful and yet demanding task since it involves solving for an inverse mapping from speckle images to object images. It becomes even more challenging when the scattering medium undergoes dynamic changes. Various approaches have been proposed in recent years.