Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse p...Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse problem.Reconstructing dirty images into clean ones is crucial for subsequent scientific analysis.To address these challenges,we propose a U-Net based method that extracts high-level information from the dirty image and reconstructs a clean image by effectively reducing artifacts and sidelobes.The U-Net architecture,consisting of an encoder-decoder structure and skip connections,facilitates the flow of information and preserves spatial details.Using simulated data of radio galaxies,we train our model and evaluate its performance on the testing set.Compared with the CLEAN method and the visibility and image conditioned denoising diffusion probabilistic model,our proposed model can effectively reconstruct both extended sources and faint point sources with higher values in the structural similarity index measure and the peak signal-to-noise ratio.Furthermore,we investigate the impact of noise on the model performance,demonstrating its robustness under varying noise levels.展开更多
Numerous experiments have been designed to investigate the Cosmic Dawn(CD)and Epoch of Reionization(EoR)by examining redshifted 21 cm emissions from neutral hydrogen.Detecting the global spectrum of redshifted 21 cm s...Numerous experiments have been designed to investigate the Cosmic Dawn(CD)and Epoch of Reionization(EoR)by examining redshifted 21 cm emissions from neutral hydrogen.Detecting the global spectrum of redshifted 21 cm signals is typically achieved through single-antenna experiments.However,this global 21 cm signal is deeply embedded in foreground emissions,which are about four orders of magnitude stronger.Extracting this faint signal is a significant challenge,requiring highly precise instrumental calibration.Additionally,accurately modelling receiver noise in single-antenna experiments is inherently complex.An alternative approach using a short-spacing interferometer is expected to alleviate these difficulties because the noise in different receivers is uncorrelated and averages to zero upon cross-correlation.The Short-spacing Interferometer Array for Global 21 cm Signal Detection(SIGMA)is an upcoming experiment aimed at detecting the global CD/EoR signal using this approach.We describe the SIGMA system with a focus on optimal antenna design and layout,and propose a framework to address cross-talk between antennas in future calibrations.The SIGMA system is intended to serve as a prototype to gain a better understanding of the system’s instrumental effects and to optimize its performance further.展开更多
基金supported by the National SKA Program of China(2020SKA0110300,2020SKA0110201)the National Natural Science Foundation of China(NSFC,grant Nos.12433012 and 12373097)+1 种基金the Guangdong Province Project of the Basic and Applied Basic Research Foundation(2024A1515011503)the Guangzhou Science and Technology Funds(2023A03J0016).
文摘Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse problem.Reconstructing dirty images into clean ones is crucial for subsequent scientific analysis.To address these challenges,we propose a U-Net based method that extracts high-level information from the dirty image and reconstructs a clean image by effectively reducing artifacts and sidelobes.The U-Net architecture,consisting of an encoder-decoder structure and skip connections,facilitates the flow of information and preserves spatial details.Using simulated data of radio galaxies,we train our model and evaluate its performance on the testing set.Compared with the CLEAN method and the visibility and image conditioned denoising diffusion probabilistic model,our proposed model can effectively reconstruct both extended sources and faint point sources with higher values in the structural similarity index measure and the peak signal-to-noise ratio.Furthermore,we investigate the impact of noise on the model performance,demonstrating its robustness under varying noise levels.
基金supported by the National SKA Program of China(No.2020SKA0110200 and No.2020SKA0110100)Y.Y.acknowledges the support of the Key Program of National Natural Science Foundation of China(12433012)。
文摘Numerous experiments have been designed to investigate the Cosmic Dawn(CD)and Epoch of Reionization(EoR)by examining redshifted 21 cm emissions from neutral hydrogen.Detecting the global spectrum of redshifted 21 cm signals is typically achieved through single-antenna experiments.However,this global 21 cm signal is deeply embedded in foreground emissions,which are about four orders of magnitude stronger.Extracting this faint signal is a significant challenge,requiring highly precise instrumental calibration.Additionally,accurately modelling receiver noise in single-antenna experiments is inherently complex.An alternative approach using a short-spacing interferometer is expected to alleviate these difficulties because the noise in different receivers is uncorrelated and averages to zero upon cross-correlation.The Short-spacing Interferometer Array for Global 21 cm Signal Detection(SIGMA)is an upcoming experiment aimed at detecting the global CD/EoR signal using this approach.We describe the SIGMA system with a focus on optimal antenna design and layout,and propose a framework to address cross-talk between antennas in future calibrations.The SIGMA system is intended to serve as a prototype to gain a better understanding of the system’s instrumental effects and to optimize its performance further.
