| Project/Area Number |
23K13095
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 15010:Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
LIU Jia 東京大学, カブリ数物連携宇宙研究機構, 特任准教授 (60962016)
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| Project Period (FY) |
2023-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2024: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2023: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | Cosmology / HSC / Weak lensing / Machine learning / Graph neural network / neutrino / cosmology / simulation |
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| Outline of Research at the Start |
I will build cosmological massive neutrino simulations that jointly model galaxies and CMB. The planned projects will help answer the key scientific question: what are the absolute masses of the neutrinos? The results will be directly applied to HSC, PFS, DESI, LSST, SO, CMB-S4, and LiteBIRD.
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| Outline of Annual Research Achievements |
I advised and contributed to 4 papers on cosmological analysis of the Hyper Suprime-Cam Year 1 data. Using weak lensing non-Gaussian statistics such as peaks, minima, PDF, and scattering transform, we achieved 30% improvement in cosmological constraints compared to the past work.
I advised a project using machine learning method graph neural networks -- a type of deep neural network designed to analyze sparse, unstructured data -- to reconstruct velocity field, achieving 10% improvement compared to existing methods.
I advised a project investigating and confirming the importance of super-sample covariance for non-Gaussian observables, such as the bispectrum, halos, voids, and their cross covariances.
I reported these results in 12 domestic and international conferences and research seminars.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The planned research project for year 1 is accomplished. We generated N-body simulations of the dark matter and neutrino fields with FastPM. The neutrino field was modeled using the “linear response” method developed by the PI and collaborators and has been implemented in the FastPM N-body code. We also generated halo catalogs in preparation for Year 2.
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| Strategy for Future Research Activity |
The project is going smoothly as planned. 3 more publications are in preparation, expected to be submitted within 2024, including: (1) "Cosmological constraints from weak lensing scattering transform using HSC Y1 data"; (2) "Void shape is important: neutrino mass from Voronoi void-halos"; and (3) "HalfDome Cosmological Simulations for Stage IV Surveys: N-body Simulations".
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