activity
20122023
most citedThe Missing Satellite Problem Outside of the Local Group. II. Statistical Properties of Satellites of Milky Way-like Galaxies

21 citations · 55 across the 9 of their papers we have counts for

collaborators

10 papers

astro-ph.GA2024

Triangulum IV: A Possible Ultra-Diffuse Satellite of M33

Itsuki Ogami, Yutaka Komiyama, Masashi Chiba +8

We report the detection of a dwarf satellite candidate (Triangulum IV: Tri IV) of the Triangulum galaxy (M33) using the deep imaging of Subaru/Hyper Suprime-Cam (HSC). From the app…

astro-ph.HE20232 cited

Performance of the Large-Sized Telescope prototype of the Cherenkov Telescope Array

Daniel Morcuende, Rubén López-Coto, Abelardo Moralejo +2

The next-generation ground-based gamma-ray Cherenkov Telescope Array Observatory (CTAO) will consist of imaging atmospheric Cherenkov telescopes (IACTs) of three different sizes di…

astro-ph.HE20232 cited

LST-1 observations of an enormous flare of BL Lacertae in 2021

Seiya Nozaki, Katsuaki Asano, Juan Escudero +2

The first prototype of LST (LST-1) for the Cherenkov Telescope Array has been in commissioning phase since 2018 and already started scientific observations with the low energy thre…

astro-ph.CO2023

Indirect Detection of Decaying Dark Matter with High Angular Resolution: Case for axion search by IRCS at Subaru Telescope

Wen Yin, Kohei Hayashi

Recent advances in cosmic-ray detectors have provided exceptional sensitivities of dark matter with high angular resolution. Motivated by this, we present a comprehensive study of…

astro-ph.GA20231 cited

Revealing mass distributions of dwarf spheroidal galaxies in the Subaru-PFS era

Kohei Hayashi, Laszlo Dobos, Carrie Filion +4

The Galactic dwarf spheroidal galaxies (dSphs) provide valuable insight into dark matter (DM) properties and its role in galaxy formation. Their close proximity enables the measure…

cs.LG2023

TabRet: Pre-training Transformer-based Tabular Models for Unseen Columns

Soma Onishi, Kenta Oono, Kohei Hayashi

We present \emph{TabRet}, a pre-trainable Transformer-based model for tabular data. TabRet is designed to work on a downstream task that contains columns not seen in pre-training.…