4月10日（火）13：30～15：00 太陽系小天体セミナー 南棟２階会議室
Apr 10 Tue Solar System Minor Body Seminar Conference Room, South Bldg.2F
4月10日（火）15：30～16：30 国立天文台 野辺山 談話会 野辺山宇宙電波観測所 本館 輪講室
Apr 10 Tue Nobeyama NAOJ Seminar Seminar Room, Nobeyama
4月13日（金）13：30～15：00 太陽天体プラズマセミナー 院生セミナー室
Apr 13 Fri Solar and Space Plasma Seminar Student Seminar Room, Subaru Bldg.
4月13日（金）16：00～17：00 国立天文台談話会 大セミナー室
Apr 13 Fri NAOJ Seminar Large Seminar Room
詳細は以下をご覧下さい。
4月10日（火）
- キャンパス
- 三鷹
- セミナー名
- 太陽系小天体セミナー
- 定例・臨時の別
- 定例
- 日時
- 4月10日（火曜日）13時30分～15時
- 場所
- 南棟２階会議室
- 講演者
- 土屋智恵／藤原康徳／古荘玲子
- 連絡先
- 名前：渡部潤一
- 備考
- テレビ会議またはスカイプによる参加も可
4月10日（火）
- Campus
- Nobeyama Radio Observatory
- Seminar
- NRO seminar
- Regular・Special
- regular
- Date
- 10th April（Tue） 15:30 ～16:30
- Room
- seminar room in NRO main building
- Speaker
- Gary Fuller
- Affiliation
- University of Manchester
- Title
- From Dark to Light: The Evolution from Molecular Clouds to Massive Protostars & Clusters
- Abstract
- Stars are the fundamental building blocks of the Universe and most stars in our Galaxy form in clusters, some of which also produce high mass stars. Although relatively rare, from their birth to their ultimate death as supernovae, these high mass stars dominate the chemical and mechanical evolution of the interstellar medium of galaxies. Despite their importance for understanding phenomena ranging from the dispersal of molecular clouds to the origin of gamma-ray bursts and black holes, the formation and early evolution of these massive stars are poorly understood. Key issues include understanding how gas accumulates into highly condensed clumps, the precursors to clusters, and how these then fragment into cores, the precursors of individual stars, as well as how massive protostars evolve. Studies of regions which are not yet dominated by star formation and effects of stellar feedback are essential for understanding these processes. In this seminar, I will discuss our recent work on such regions selected from the Spitzer Dark Cloud catalogue and the insights they provide into how clusters and massive stars form.
- Facilitator
- name：Gwanjeong Kim
- comment
- remarks：teleconference available
4月13日（金）
- Campus
- Mitaka
- Seminar
- Solar and Space Plasma Seminar
- Regularly Scheduled/Sporadic
- Regular
- Date and time
- 13 April (Fri), 13:30-15:00
- Place
- Student Seminar Room, Subaru Bldg.
- Speaker
- Kosuke Namekata
- Affiliation
- Kyoto University
- Title
- Lifetime, Emerging and Decay Rates of Star Spots on Solar-type Stars
- Abstract
- Recently, many superflares on solar-type stars were discovered by the Kepler Space Telescope (Maehara et al. 2012). Such active stars are thought to have large star spots (Notsu et al. 2013), and superflares are considered to occur through magnetic reconnection like solar flares (Namekata et al. 2017). The emergence and decay of such large star spots are important for the understanding of superflare events as well as underlying stellar dynamo. However, there are few study which reported the temporal evolution of star spots because of its difficulty in measurements. Here, we have developed a simple method to measure temporal evolutions of star spots area with Kepler data by tracing local minima of the light curves (cf, Maehara et al. 2017). We will report the statistical properties of lifetimes, emerging and decay rates of star spots on solar-type stars. We will compare them with those of sunspots and discuss how to understand them on the basis of sunspot physics.
- Facilitator
- -Name：Shin Toriumi
- Comment
4月13日（金）
- Campus
- Mitaka
- Seminar
- NAOJ seminar
- Regularly Scheduled/Sporadic
- Scheduled
- Date and time
- Fri 13 Apr. 16:00~17:00
- Place
- Large Seminar Room
- Speaker
- Elizabeth Tasker
- Affiliation
- JAXA
- Title
- Finding Patterns in Planets: A neural network approach to the exoplanet dataset
- Abstract
-
We now know of over 3,500 exoplanets; an explosion in growth since the 1990s that
shows no sign of abating. 96% of these new worlds have been discovered by either
the radial velocity technique (that measures the doppler wobble of the star as it orbits
with the planet) or the transit technique (the dip in brightness as the exoplanet crosses
the line-of-sight between the star and Earth). However, both these techniques provide
only a single measurement of the planet’s bulk properties; either the planet’s minimum
mass or the radius. As we step into a new era of exoplanet observations where
instruments such as the JWST aim to probe the atmosphere of these worlds, we are left
with using this scant information to select the best candidates from a huge dataset for
these time-intensive observations.
However, while the information per planet is small, the number of discoveries allows
the potential for meaningful statistical analysis. Such techniques can identify relationships
between properties to infer missing information. One pathway is to take advantage of
the capabilities of neural networks. The principal behind such algorithms is to present
the computer with a dataset but no a priori knowledge about links between the elements,
allowing the network to locate its own patterns. This technique is particularly strong at
finding connections between multiple elements at once (hard to view on a graph) and
also at identifying connections that have been missed as they fall outside expectations
(a real risk with planet formation!). This research looks at one example of a neural network
for estimating the mass and radius of a planet, based on properties available from both
radial velocity and transit observations. This could be an added tool to guide sample
selection in the future. - Facilitator
- -Name：Yano, Taihei