activity
20172026
most citedCosmological inference from the emulator based halo model II: Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

6 citations · 19 across the 19 of their papers we have counts for

collaborators

21 papers

astro-ph.GA2026

The CAMELS-CROCODILE Simulation Suite: A New Cosmology--Astrophysics Playground for Machine Learning

Kentaro Nagamine, Yuri Oku, Atsushi J. Nishizawa +4

We present CAMELS-CROCODILE, a suite of cosmological hydrodynamic simulations that extends the CAMELS framework with the \gadget{} smoothed particle hydrodynamics code and the Osak…

hep-ph2026

Future of Artificial Intelligence for Science in Japan 2024 Community Report

Yoshitaka Itow, Jia Liu, Hirokazu Maesaka +16

This white paper summarizes scientific challenges and AI/ML research opportunities identified through the FAIRS Japan 2024 unconference process. The discussion focuses on three maj…

astro-ph.CO2026

Weak-lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: III. A precision cosmological sample enabled by optical confirmation

I-Non Chiu, Kai-Feng Chen, Masamune Oguri +9

We develop fCAMIRA (forced-mode CAMIRA), a tool for optical cluster confirmation, and apply it to a sample of 129 weak-lensing (WL) shear-selected galaxy clusters identified in ape…

astro-ph.CO2026

Standard Reconstruction Shifts the Optimal Input Scale for CNN-Based Density-Field Reconstruction

Koichiro Nakashima, Kiyotomo Ichiki, Atsushi J. Nishizawa

We investigate convolutional neural network (CNN) methods for reconstructing the high-redshift density field from late-time large-scale structure, focusing on how the physical scal…

astro-ph.CO2025

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…

astro-ph.CO2025★ 2 cited

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…