3 citations · 4 across the 5 of their papers we have counts for
6 papers
Machine-learning applications for weak-lensing cosmology
Masato Shirasaki
This article reviews recent advances in the application of machine learning to weak-lensing cosmology. Weak gravitational lensing provides a unique and powerful probe of the total…
Cross-correlating galaxies and cosmic dispersion measures: Constraints on the gas-to-halo mass relation from 2MASS galaxies and 133 localized fast radio bursts
Masato Shirasaki, Ryuichi Takahashi, Ken Osato +1
We conduct a cross-correlation analysis between large-scale structures traced by the Two Micron All Sky Survey (2MASS) galaxy catalog and the cosmic dispersion measures of 133 loca…
Denoising weak lensing mass maps with diffusion model and generative adversarial network
Shohei D. Aoyama, Ken Osato, Masato Shirasaki
The matter distribution of the Universe can be mapped through the weak gravitational lensing (WL) effect: small distortions of the shapes of distant galaxies, which reflects the in…
Measurement of angular cross-correlation between the cosmological dispersion measure and the thermal Sunyaev--Zeldovich effect
Ryuichi Takahashi, Kunihito Ioka, Masato Shirasaki +1
The dispersion measures () from fast radio bursts (FRBs) and the thermal Sunyaev--Zeldovich (tSZ) effect probe the free-electron density and thermal pressure, respective…
Denoising weak lensing mass maps with diffusion model: systematic comparison with generative adversarial network
Shohei D. Aoyama, Ken Osato, Masato Shirasaki
Removing the shape noise from the observed weak lensing field, i.e., denoising, enhances the potential of WL by accessing information at small scales where the shape noise dominate…
Neural style transfer of weak lensing mass maps
Masato Shirasaki, Shiro Ikeda
We propose a new generative model of projected cosmic mass density maps inferred from weak gravitational lensing observations of distant galaxies (weak lensing mass maps). We const…