Forecasting Constraint on the f(R) Theory with the CSST SN Ia and BAO Surveys

Abstract The f ( R ) 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 the f ( R ) theory using the mock data generated from the Chinese Space Station Telescope (CSST) Ultra-Deep Field Type Ia supernova (SN Ia) survey and wide-field slitless spectroscopic baryon acoustic oscillation (BAO) survey. We explore three popular f ( R ) models and introduce a parameter b to characterize the deviation of the f ( R ) theory from the ΛCDM theory. The Markov Chain Monte Carlo method is employed to constrain the parameters in the f ( R ) models, and the nuisance parameters and systematic uncertainties are also considered in the model fitting process. Besides, we also perform model comparisons between the f ( R ) models and the ΛCDM model. We find that the constraint accuracy using the CSST SN Ia+BAO data set alone is comparable to or even better than the result given by the combination of the current relevant observations, and the CSST SN Ia+BAO survey can distinguish the f ( R ) models from the ΛCDM model. This indicates that the CSST SN Ia and BAO surveys can effectively constrain and test the f ( R ) theory.