This study presents an experiment on diffuse light cooling of atoms in a cylindrical cavity. We focus on the controlling of the shape of the atom cloud by placing the cooling beams in appropriate positions. The Gauss-like shape of the atomic cloud is demonstrated. The number of cold atoms detected in the cavity is increased, thereby improving the signal-to-noise ratio of the clock signal.

The integrating sphere is used to generate the diffuse light for cooling atoms. The microwave field is produced in a cylindrical cavity on a TE011 mode. We have realized the microwave interrogation with the pulsed optically pumped ( POP ) scheme. The Ramsey fringe is demonstrated and some factors to affect the signal to noise ratio ( SNR ) and the contrast of the fringe are discussed. Optimization of the experimental parameters is still in progress.

In this paper, we present an experiment to measure the spatial distribution of cold atoms in a ceramic integrating sphere. An quadrupole field is applied after the atoms

Hyperspectral imaging that obtains the spatial-spectral information of a scene has been extensively applied in various fields but usually requires a complex and costly system. A single-pixel detector based hyperspectral system mitigates the complexity problem but simultaneously brings new difficulties on the spectral dispersion device. In this work, we propose a low-cost compressive single-pixel hyperspectral imaging system with RGB sensors. Based on the structured illumination single-pixel imaging configuration, the lens-free system directly captures data by the RGB sensors without dispersion in the spectral dimension. The reconstruction is performed with a pre-trained spatial-spectral dictionary, and the hyperspectral images are obtained through compressive sensing. In addition, the spatial patterns for the structured illumination and the dictionary for the sparse representation are optimized by coherence minimization, which further improve the reconstruction quality. In both spatial and spectral dimensions, the intrinsic sparse properties of the hyperspectral images are made full use of for high sampling efficiency and low reconstruction cost. This work may introduce opportunities for optimization of computational imaging systems and reconstruction algorithms towards high speed, high resolution, and low cost future.