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Constraining the Spatial Curvature of the Local Universe with Deep Learning 被引量:1
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作者 Liang Liu Li-Juan Hu +1 位作者 Li Tang Ying Wu 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2023年第12期153-163,共11页
We use the distance sum rule method to constrain the spatial curvature of the Universe with a large sample of 161strong gravitational lensing systems,whose distances are calibrated from the Pantheon compilation of typ... We use the distance sum rule method to constrain the spatial curvature of the Universe with a large sample of 161strong gravitational lensing systems,whose distances are calibrated from the Pantheon compilation of typeⅠa supernovae using deep learning.To investigate the possible influence of mass model of the lens galaxy on constraining the curvature parameterΩ_(k),we consider three different lens models.Results show that a flat Universe is supported in the singular isothermal sphere(SIS)model with the parameterΩ_(k)=0.049_(-0.125)^(+0.147).While in the power-law(PL)model,a closed Universe is preferred at the~3σconfidence level,with the parameterΩ_(k)=-0.245_(-0.071)^(+0.075).In the extended PL model,the 95%confidence level upper limit ofΩ_(k)is<0.011.As for the parameters of the lens models,constraints on the three models indicate that the mass profile of the lens galaxy could not be simply described by the standard SIS model. 展开更多
关键词 (cosmology:)cosmological parameters-(cosmology:)distance scale-(stars:)supernovae GENERAL
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