Spinning thermal radiation is a unique phenomenon observed in condensed astronomical objects, including the Wolf-Rayet star EZ-CMa and the red degenerate star G99-47, due to the existence of strong magnetic fields. Here, by designing symmetry-broken metasurfaces, we demonstrate that spinning thermal radiation with a nonvanishing optical helicity can be realized even without applying a magnetic field. We design nonvanishing optical helicity by engineering a dispersionless band that emits omnidirectional spinning thermal radiation, where our design reaches 39% of the fundamental limit. Our results firmly suggest that metasurfaces can impart spin coherence in the incoherent radiation excited by thermal fluctuations. The symmetry-based design strategy also provides a general pathway for controlling thermal radiation in its temporal and spin coherence.

Spectro-polarimetric imaging in the long-wave infrared (LWIR) region plays a crucial role in applications from night vision and machine perception to trace gas sensing and thermography. However, the current generation of spectro-polarimetric LWIR imagers suffers from limitations in size, spectral resolution, and field of view (FOV). While meta-optics-based strategies for spectro-polarimetric imaging have been explored in the visible spectrum, their potential for thermal imaging remains largely unexplored. In this work, we introduce an approach for spectro-polarimetric decomposition by combining large-area stacked meta-optical devices with advanced computational imaging algorithms. The co-design of a stack of spinning dispersive metasurfaces along with compressive sensing and dictionary learning algorithms allows simultaneous spectral and polarimetric resolution without the need for bulky filter wheels or interferometers. Our spinning-metasurface-based spectro-polarimetric stack is compact (<10×10×10cm) and robust, and it offers a wide field of view (20.5°). We show that the spectral resolving power of our system substantially enhances performance in machine learning tasks such as material classification, a challenge for conventional panchromatic thermal cameras. Our approach represents a significant advance in the field of thermal imaging for a wide range of applications including heat-assisted detection and ranging (HADAR).

The analytical model based on the quasi-single small-angle scattering approximation can efficiently simulate oceanic lidar signals with multiple scattering; thus, its accuracy is of particular interest to scientists. In this paper, the model is modified to include refraction at oblique incidence and is then compared with Monte Carlo (MC) simulations and experimental results. Under different conditions, the results calculated by the analytical model demonstrate good agreement with the MC simulation and experimental data. The coefficient of determination R² considering the logarithm of signals and the root mean square of the relative difference δ are R² = 0.998 and δ = 10% in comparison with the semi-analytic MC simulation and R² = 0.952 and δ = 46% for the lidar experiment. Thus, the results demonstrate the validity of the analytical model in the simulation of oceanic lidar signals.