Chen Su

We present a simulation-based inference (SBI) framework for cosmological parameter estimation via a void-lensing analysis. Despite the absence of an analytical model of void lensing, SBI can effectively learn posterior distributions through forward modeling of mock data. We developed a forward modeling pipeline that accounts for both the cosmology and the galaxy-halo connection. By training a neural density estimator (NDE) on simulated data, we were able to infer the posteriors of two cosmological parameters, $\Omega_m$ and $S_8$. Validation tests were conducted on posteriors derived from different cosmological parameters and a fiducial sample. The results demonstrate that SBI provides unbiased estimates of mean values and accurate uncertainties. These findings also highlight the potential for applying void-lensing analyses to observational data – even without an analytical void-lensing model.

Weak-lensing studies via cosmic voids are a promising probe of modified gravity (MG). The excess surface mass density (ESD) is widely used as a lensing statistic in weak-lensing research. In this paper, we use the ray-tracing method to study the ESD around voids in simulations based on cubic Galileon (CG) gravity. With the compilation of an N-body simulation and the ray-tracing method, changes in structure formation and deflection angle resulting from MG can both be considered, making the extraction of lensing signals more realistic. We find good agreements between the measurement and theoretical prediction of ESD for CG gravity. However, the lensing signals are much less affected by the change in the deflection angle than by the change in the structure formation, indicating a good approximation of the ESD (statistics) as the projection of the 3D dark matter density field. Finally, we demonstrate that it is impossible to distinguish CG and general relativity in our simulation, but in the next-generation survey, thanks to the large survey area and the increased galaxy number density, detecting the differences between these two models is possible. The method employed in this paper, which combines an N-body simulation and the ray-tracing method, can be a robust way to measure the lensing signals from simulations based on the MGs, and especially on that which significantly modifies the deflection angle.