Abstract:
    Cosmic magnification holds the same valuable information as cosmic shear, but its cosmological application is often hindered by the overwhelming noise from galaxy intrinsic clustering. In this talk, I will present a method designed to reconstruct the cosmic magnification signal, effectively minimizing galaxy intrinsic clustering. This approach has been validated and refined through extensive simulations and numerical studies. Recently, we applied this method to DECaLS and DES Y3 data, successfully reconstructing weak lensing convergence maps that cover a quarter of the sky. Our analysis demonstrates a significant suppression of galaxy intrinsic clustering and a robust detection of the cosmic magnification signal, achieving a signal-to-noise ratio (S/N) of 20. However, a multiplicative bias was identified in the reconstructed convergence maps for both DECaLS and DES Y3 data. Testing indicates that this bias arises from approximations in the galaxy selection function. Therefore, precise modeling of the galaxy selection function is essential for the effective application of cosmic magnification in weak lensing studies.