Tracing the SMBH growth: outlook beyond the HSC-SSP, and future collaborations

SCIENTIFIC RATIONALE

One of the most critical issues in astronomy today is to understand when and how supermassive black holes (SMBHs) have formed and evolved in the history of the universe. In order to advance that understanding, it is necessary to examine active galactic nuclei (AGN) in various evolutionary stages in all epochs without any selection bias, and to reveal their statistical properties by comparing with theoretical models.

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) has started in 2014 and just completed observations over the allocated 330 nights. The following legacy projects by PFS and unprecedented follow-up opportunities with JWST are getting closer to begin. In this conference, we aim to share what we have learned about the growth history of SMBHs through the HSC-SSP and discuss strategies to advance our knowledge gained so far toward the future.

We invite to this conference researchers who are leading or interested in AGN studies using the HSC. Given the recent remarkable progress in the use of machine learning (ML) in astronomy, we will also discuss how to make the best use of the wide-and-deep, high-quality imaging data from HSC-SSP with ML techniques.

The following discussion topics will be covered in this meeting:

• Progress of AGN-related projects using the HSC data, especially those made in the last two years

• AGN researches with ML techniques and possible future developments

• Synergies with forthcoming observing missions in the next few years (e.g., JWST, PFS, Euclid, and LSST)

A hands-on session "machine learning counseling booth"

As a new attempt in this series of conferences, we plan to have a hands-on session, "machine learning counseling booth". It serves for researchers who are interested in but are not familiar with ML, to provide opportunities to consult with experts and thus to encourage new collaborations. This special session will be held in parallel to the poster session.

The poster session and machine learning counseling booth are limited to local participants.

ORGANIZING COMMITTEE

• Masayuki Akiyama (Tohoku Univ.)

• Shunsuke Baba (Kagoshima Univ.)

• Masatoshi Imanishi (NAOJ)

• Yoshiki Matsuoka (Ehime Univ.)

• Tohru Nagao (Ehime Univ.)

• Taira Oogi (Ehime Univ.)

• Yoshiki Toba (NAOJ, chair)

• Keiichi Wada (Kagoshima Univ.)

WiFi Service

You can use eduroam in the conference site. In addition, we will issue temporary eduroam accounts.

CONTACT

yoshiki.toba (at) nao.ac.jp

CODE OF CONDUCT

HSC Survey Collaboration Meeting Code of Conduct