activity
20012026
most citedImproved low Q2 model for neutrino and electron nucleon cross sections in few GeV region

92 citations · 243 across the 18 of their papers we have counts for

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Showing astro-ph.COShow all

6 papers · 1 filter

astro-ph.CO2026

Climbing the -point Ladder Part I: Information in the Higher-Order Configuration-Space Clustering of Dark Matter Halos

Sumi Kim, Cristiano G. Sabiu, Inkyu Park

We quantify the information content of the configuration-space two-, three-, and connected four-point correlation functions of Quijote dark-matter haloes at and fixed number…

astro-ph.CO2023

The Universe is worth pixels: Convolution Neural Network and Vision Transformers for Cosmology

Se Yeon Hwang, Cristiano G. Sabiu, Inkyu Park +1

We present a novel approach for estimating cosmological parameters, , , , and one derived parameter, , from 3D lightcone data of dark matter halos in redshift s…

astro-ph.CO2022★ 6 cited

Analyzing Planar Galactic Halo Distributions with Fuzzy/Cold Dark Matter Models

Sangnam Park, Dongsu Bak, Jae-Weon Lee +1

We perform a numerical comparison between the fuzzy dark matter model and the cold dark matter model, focusing on formation of satellite galaxy planes around massive galaxies. Such…

astro-ph.CO2022★ 15 cited

Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments

Hannah Jhee, Hyunmi Song, Rory Smith +3

We have explored the dynamical and mass evolution of halos driven by large-scale filaments using a dark matter-only cosmological simulation with the help of a phase-space analysis.…

astro-ph.CO2021★ 7 cited

Probing Ultra-light Axion Dark Matter from 21cm Tomography using Convolutional Neural Networks

Cristiano G. Sabiu, Kenji Kadota, Jacobo Asorey +1

We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21cm radio observations around the epoch of reionization (EoR). We show that the ax…

astro-ph.CO2020★ 16 cited

Deep-Learning Study of the 21cm Differential Brightness Temperature During the Epoch of Reionization

Yungi Kwon, Sungwook E. Hong, Inkyu Park

We propose a deep learning analyzing technique with convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm different…