68 citations · 87 across the 20 of their papers we have counts for
7 papers · 1 filter
Catalogs of optically-selected clusters and photometric luminous red galaxies from the Hyper Suprime-Cam Subaru Strategic Program final year dataset
Masamune Oguri, Yen-Ting Lin, Nobuhiro Okabe +9
We construct samples of optically-selected clusters and photometric luminous red galaxies (LRGs) from the Hyper Suprime-Cam Subaru Strategic Program final year dataset covering $\s…
Sensitivity toward dark matter annihilation imprints on 21-cm signal with SKA-Low: A convolutional neural network approach
Pravin Kumar Natwariya, Kenji Kadota, Atsushi J. Nishizawa
This study investigates the sensitivity of the radio interferometers to identify imprints of spatially inhomogeneous dark matter annihilation signatures in the 21-cm signal during…
Cosmology and Source Redshift Constraints from Galaxy Clustering and Tomographic Weak Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model
Tianqing Zhang, Xiangchong Li, Sunao Sugiyama +13
The combination of galaxy clustering and weak lensing is a powerful probe of the cosmology model. We present a joint analysis of galaxy clustering and weak lensing cosmology using…
Modelling Galaxy Clustering and Tomographic Galaxy-Galaxy Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model and Redshift Self-Calibration
Tianqing Zhang, Sunao Sugiyama, Surhud More +13
The combination of galaxy-galaxy weak lensing and galaxy clustering is a powerful probe of the cosmological model, and exploration of how to best model and extract this information…
Searching optimal scales for reconstructing cosmological initial conditions using convolutional neural networks
Koichiro Nakashima, Kiyotomo Ichiki, Atsushi J. Nishizawa +1
Reconstructing the initial density field of the Universe from the late-time matter distribution is a nontrivial task with implications for understanding structure formation in cosm…
Insights into the dependence of galaxy properties on the environment with explainable machine learning models
Shun-ya S. Uchida, Suchetha Cooray, Atsushi J. Nishizawa +2
Galaxies reside within dark matter halos, but their properties are influenced not only by their halo properties but also by the surrounding environment. We construct an interpretab…
CMB lensing tomography with clustering estimation of lens redshift distributions
Shun Arai, John A. Peacock, Hironao Miyatake +1
We develop a clustering-based redshift estimation approach for CMB lensing tomography, focusing on the kernel function of the lensing galaxies. Within a linear galaxy bias framewor…