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Dates: June 2-5, 2025
Location: Masukawa Hall, Yukawa Institute for Theoretical Physics, Kyoto University (YITP)
Large-scale galaxy surveys are being driven by various major international collaborative projects, such as the ongoing Subaru HSC, Euclid, JWST and DESI, as well as the planned Subaru PFS, LSST, and Roman. Over the next decade, these large surveys are expected to significantly advance our understanding of cosmology and galaxy formation.
To fully exploit the wealth of information from these observations, there is an urgent need to develop theoretical templates that can be directly compared to the data. Among the most essential are simulated mock galaxy and AGN catalogs, along with the large-volume cosmological simulations that underpin them. Today, the sheer size of these catalogs makes their analysis as challenging as the observations themselves. Extracting meaningful insights requires leveraging advanced information processing techniques, including big data analysis, machine learning, and statistical methods, while maintaining a comprehensive understanding of the theoretical background and the various systematic uncertainties present in the data.
This school will focus on cosmology and galaxy formation studies using large-scale survey and mock catalogs. The program combines theoretical lectures with practical exercises. Young researchers will engage in hands-on data analysis through group work and will have the opportunity to present their results at the end of the school.
Lectures include: Peter Behroozi (U. Arizona, USA), Anatoly Klypin (U. Virginia, USA), Takahiro Nishimichi (Kyoto Sangyo U., Japan), Teppei Okumura (ASIAA, Taiwan), Ken Osato (Chiba U., Japan), Francisco Prada (Instituto de Astrofisica de Andalucia, Spain), Atsushi Taruya (Kyoto U., Japan), Qiao Wang (NAOC, China), Xin Wang (UCAS, China).
mock-cosmology2025 at ml.chiba-u.jp
Yukawa Institute for Theoretical Physics, Kyoto University