Super-resolution Imaging of Telescopic Systems based on Optical-neural Network Joint Optimization

Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced resolution.This paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)network.To improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised networks.To reconstruct the PSF trained by the network in the optical path,a phase mask is introduced.It improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the network.The results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.

Damage and recovery of fiber Bragg grating under radiation environment

To develop the application of fiber Bragg gratings as temperature and strain sensors in space environments, it is necessary to understand the effect of high-energy radiation on the performance of the fiber Bragg grating. We performed an experiment involving Co（60）-γ ionizing irradiation with a total dose of 1.01 × 10~6 rad on two Ge-doped single-mode fiber Bragg gratings with central wavelengths of 825 and 835 nm, respectively. We found that, with the increase of radiation dose, the redshift of the peak wavelength of the reflection spectrum of the fiber Bragg gratings indicated the increase of the refractive index and the number of color centers. After irradiation, the refractive index decreased with the decreasing number of color centers. We analyzed the influence of ionizing irradiation on the transmission performance of the fiber Bragg gratings using a color-center model, which explained the experimental results. The proposed model was used to determine the creation rate and annihilation rates of the color center, which are foundational data for using the fiber Bragg gratings in space applications.