AI staring into the void: machine learning-assisted science with the empty universe

Research Project

Project/Area Number	24K22878
Research Category	Grant-in-Aid for Research Activity Start-up
Allocation Type	Multi-year Fund
Review Section	0203:Particle-, nuclear-, astro-physics, and related fields
Research Institution	The University of Tokyo
Principal Investigator	Thiele Leander 東京大学, カブリ数物連携宇宙研究機構, 特任助教 (00998487)
Project Period (FY)	2024-07-31 – 2026-03-31
Project Status	Granted (Fiscal Year 2024)
Budget Amount *help	¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000) Fiscal Year 2025: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2024: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords	cosmology / cosmic voids
Outline of Research at the Start	We will study the properties of the most underdense regions of the universe, cosmic voids, to learn more about the fundamental properties of Nature. Machine learning will be used to assist.