Extending CSST Emulator to post-DESI era
Zhao Chen, Yu Yu
TL;DR
This work addresses the need for fast, percent-level predictions of the nonlinear matter power spectrum in dynamical dark energy scenarios ($w_0w_a$CDM) to capitalize on DESI DR2+CMB data. It extends the spectral equivalence method to use auxiliary $w_0w_a$CDM models (beyond $w$CDM), enabling sub-percent accuracy ($\lesssim1\%$) over the $z\le3$ range and expanding applicability to the full $2\sigma$ DESI posterior. Validation against the Kun $N$-body suite and extended dynamic dark energy simulations confirms robustness across an 8D cosmological space including massive neutrinos, with only minor extrapolation effects. This approach enhances the CSST Emulator’s utility for post-DESI cosmology, enabling precise, rapid likelihood analyses and motivating extensions to other statistics and DE models.
Abstract
The recent DESI BAO measurements have revealed a potential deviation from a cosmological constant, suggesting a dynamic nature of dark energy. To rigorously test this result, complementary probes such as weak gravitational lensing are crucial, demanding highly accurate and efficient predictions of the nonlinear matter power spectrum within the $w_0w_a$CDM framework. However, most existing emulators fail to cover the full parameter posterior from DESI DR2+CMB constraints in the $w_0\mbox{-}w_a$ plane. In this work, we extend the spectral equivalence method outlined in Casarini et al. 2016 to use auxiliary $w_0w_a$CDM models for approximating the power spectrum of a target $w_0w_a$CDM cosmology, moving beyond the previous use of $w$CDM auxiliaries. Incorporating this enhanced module, the extended CSST Emulator achieves a prediction accuracy of $\leq1\%$ over the $1σ$ confidence region from DESI DR2+CMB constraints for $z\leq3$, validated by additional dynamic dark energy simulations. The emulator's applicable parameter space has been generalized to fully encompass the $2σ$ region, greatly enhancing its utility for cosmological analysis in the post-DESI era.
