[日時] 毎週月曜日15時から / [Date] Monday 15:00-
[場所] 合同C棟N507 大輪講室 / [Venue] Science Complex C N507
|1613||2019/02/18 (Tue)||Tilman Hartwig (Institute for Physics of Intelligence, U. Tokyo)||Machine Learning for Classification of Astronomical Data|
|1614||2019/03/11 (Wed)||Danilo Marchesini (Tufts University)||Ultra-massive Galaxies in the First 2 Gyr of Cosmic History|
2020/02/18 (Tue) 15:00-
Tilman Hartwig (Institute for Physics of Intelligence, U. Tokyo)
Machine Learning for Classification of Astronomical Data
Understanding the nature of the first stars is a major challenge of modern cosmology. Despite their importance for the formation of subsequent stars and galaxies, their nature is not well understood due to a lack of direct observations. I will show how we derive the multiplicity of the first stars from the abundance patterns of extremely metal-poor (EMP) stars in the Milky Way. Based on theoretical models of the chemical yields of the first supernovae, we train decision trees to classify EMP stars. This machine learning-based approach predicts if a certain abundance pattern is consistent with supernova enrichment by one or by several progenitor stars (mono- or multi-enriched). By applying the trained random forest to actual observations, we find both mono- and multi-enriched EMP stars. These results allow us to constrain the multiplicity and initial mass function of the first stars, which has significant consequences for the radiative and chemical signature of the first stars and galaxies. Such machine learning-based approaches are of great value with upcoming surveys and instruments, such as the Subaru Prime Focus Spectrograph, that will provide many more high-resolution spectra of stellar fossils.
2020/03/11 (Wed) 15:00-
Danilo Marchesini (Tufts University)
Ultra-massive Galaxies in the First 2 Gyr of Cosmic History
One of the most controversial questions regarding the formation and evolution of galaxies is when and how today’s most massive galaxies form. In the last decade, a surprising initial finding was that the number density of ultra-massive galaxies (UMGs; Mstar>3x10^11 Msun) evolves very little between z=4 to z=1.5. The formation of these massive galaxies so early in the Universe’s history puts very tight constraints on models of galaxy formation and evolution. I will present the characterization of the stellar population properties, number density, AGN incidence, and environments of the largest sample, to-date, of UMGs at z>3 constructed from state-of-the-art photometric catalogs over ~8 deg^2 in XMM and CDFS. This sample is the first representative stellar-mass complete sample of UMGs in the first 2 Gyr of cosmic history, including both quiescent and dusty star-forming galaxies. I will conclude presenting very recent results from a spectroscopic follow-up campaign of the monster galaxies with the Keck telescope.