15 citations · 15 across the 4 of their papers we have counts for
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Supernova Classification using the Recurrent Neural Network in the CSST Ultra-Deep Field Survey
Minglin Wang, Yan Gong, Dejia Zhou +1
We study supernova (SN) classification using the Recurrent Neural Networks (RNNs) within the Chinese Space-station Survey Telescope Ultra-Deep Field (CSST-UDF) photometric survey a…
Future Cosmology: New Physics and Opportunity from the China Space Station Telescope (CSST)
Yan Gong, Haitao Miao, Xingchen Zhou +12
The China Space Station Telescope (CSST) is the next-generation Stage~IV survey telescope. It can simultaneously perform multi-band imaging and slitless spectroscopic wide- and dee…
Forecasting Constraint on the Theory with the CSST SN Ia and BAO Surveys
Jun-Hui Yan, Yan Gong, Minglin Wang +2
The modified gravity theory can explain the accelerating expansion of the late Universe without introducing dark energy. In this study, we predict the constraint strength on…
Cosmological Prediction of the CSST Ultra Deep Field Type Ia Supernova Photometric Survey
Minglin Wang, Yan Gong, Furen Deng +3
Type Ia supernova (SN Ia) as a standard candle is an ideal tool to measure cosmic distance and expansion history of the Universe. Here we investigate the SN Ia photometric measurem…