activity
20062023
most citedThe Hyper Suprime-Cam SSP Survey: Overview and Survey Design

1.1k citations · 11.4k across the 167 of their papers we have counts for

collaborators

167 papers

gr-qc2023

Physically consistent gravitational waveform for capturing beyond general relativity effects in the compact object merger phase

Daiki Watarai, Atsushi Nishizawa, Kipp Cannon

The merger phase of compact binary coalescences is the strongest gravity regime that can be observed. To test the validity of general relativity (GR) in strong gravitational fields…

astro-ph.CO2023★ 3 cited

Robustness of Baryon Acoustic Oscillations Measurements with Photometric Redshift Uncertainties

Keitaro Ishikawa, Tomomi Sunayama, Atsushi J. Nishizawa +2

We investigate the robustness of baryon acoustic oscillations (BAO) measurements with a photometric galaxy sample using mock galaxy catalogues with various sizes of photometric red…

astro-ph.CO2023★ 1 cited

Line-of-sight structure of troughs identified in Subaru Hyper Suprime-Cam Year 3 weak lensing mass maps

Takumi Shimasue, Ken Osato, Masamune Oguri +2

We perform the weak lensing mass mapping analysis to identify troughs, which are defined as local minima in the mass map. Since weak lensing probes projected matter along the line-…

astro-ph.GA2023★ 64 cited

Quasar Luminosity Function at z = 7

Yoshiki Matsuoka, Masafusa Onoue, Kazushi Iwasawa +41

We present the quasar luminosity function (LF) at , measured with 35 spectroscopically confirmed quasars at . The sample of 22 quasars from the Subaru High-…

astro-ph.CO2023★ 4 cited

Non-Linearity-Free prediction of the growth-rate using Convolutional Neural Networks

Koya Murakami, Indira Ocampo, Savvas Nesseris +2

The growth-rate of the large-scale structure of the Universe is an important dynamic probe of gravity that can be used to test for deviations from General Relativity. How…

astro-ph.CO2023★ 1 cited

Impact of astrophysical effects on the dark matter mass constraint with 21cm intensity mapping

Koya Murakami, Atsushi J. Nishizawa, Kentaro Nagamine +1

We present an innovative approach to constraining the non-cold dark matter model using a convolutional neural network (CNN). We perform a suite of hydrodynamic simulations with var…