SCIENTIFIC RATIONALE

The field of galaxy evolution covers a wide range of astrophysical scales: from the cosmic large-scale structure to the central black hole of the Milky Way. This is a rapidly evolving field and thus it is important to understand astrophysical processes operating on various physical scales to draw a complete picture of galaxy evolution. While a classical workshop focusing on some specific aspects of galaxies is already useful, a workshop with a broader scope, essentially on everything about galaxies, is highly complementary. Motivated by this, we decided to hold a “Galaxy Evolution Workshop" every year to improve our understanding of the complex nature of galaxies and their evolution over the cosmic time. In this year, considering the world-wide pandemic situation, we have decided to hold it with a slight delay in February 2022. (This is basically an online workshop, but we provide an option for Japanese domestic participants to be onsite at NAOJ)

The goals of the workshop are:

1. to present and discuss recent (and new!) results, and
2. to discuss what the next steps will be.

Continuing from the last time, this workshop 2021 is jointly hosted by Japan, Taiwan, and Korea communities, to spark cooperations among East-Asia. We therefore very much appreciate presentations by young postdocs and students. Any presentations related to galaxies (from the Milky Way to the most distant galaxies) are welcome.

In addition to general science sessions, we will have a focused session. This time our main theme is ‘Data Science in Astronomy’. This is one of the hottest topics/applications of the galaxy evolution field these years. We invite several keynote speakers to provide a broad context. We also welcome oral/poster contributions about this focused topic. We look forward to seeing you at the workshop!

KEYNOTE SPEAKERS (and main topic)

Masayuki Tanaka (NAOJ)

Citizen Science

Shiro Ikeda (The Institute of Statistical Mathematics)

Overview of data science in Astronomy

Ting-Wen Lan (NTU)

Galaxy evolution, big data, and cross-correlation

Yen-Ting Lin (ASIAA)

Assembly of massive clusters and galaxies

Min-Su Shin (KASI)

Analysis of big astronomical data

Sungwook E. Hong (KASI)

Applications of machine learning in astronomy

CODE OF CONDUCT

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