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東京確率論セミナー
過去の記録 ～04/24｜次回の予定｜今後の予定 04/25～
| 開催情報 | 月曜日 16:00～17:30 数理科学研究科棟(駒場) 126号室 |
|---|---|
| 担当者 | 佐々田槙子、中島秀太（明治大学） |
| セミナーURL | https://sites.google.com/view/tokyo-probability-seminar23/2024年度 |
2016年07月11日(月)
15:00-18:20 数理科学研究科棟(駒場) 128号室
時間がいつもと異なります．ご注意ください(この日は2つ講演があります)．
Jin Feng 氏 (University of Kansas) 15:00-16:30
An introduction to Hamilton-Jacobi equation in the space of probability measures (English)
ある化学反応系のモデリングとそのシミュレーション解析
時間がいつもと異なります．ご注意ください(この日は2つ講演があります)．
Jin Feng 氏 (University of Kansas) 15:00-16:30
An introduction to Hamilton-Jacobi equation in the space of probability measures (English)
[ 講演概要 ]
I will discuss Hamilton-Jacobi equation in the space of probability measures.
Two types of applications motivate the issue: one is from the probabilistic large deviation study of weakly interacting particle systems in statistical mechanics, another is from an infinite particle version of the variational formulation of Newtonian mechanics.
In creating respective well-posedness theories, two mathematical observations played important roles: One, the free-particle flow picture naturally leads to the use of the optimal mass transportation calculus. Two, there is a hidden symmetry (particle permutation invariance) for elements in the space of probability measures. In fact, the space of probability measures in this context is best viewed as an infinite dimensional quotient space. Using a natural metric, we are lead to some fine aspects of the optimal transportation calculus that connect with the metric space analysis and probability.
Time permitting, I will discuss an open issue coming up from the study of the Gibbs-Non-Gibbs transitioning by the Dutch probability community.
The talk is based on my past works with the following collaborators: Markos Katsoulakis, Tom Kurtz, Truyen Nguyen, Andrzej Swiech and Luigi Ambrosio.
上山 大信 氏 (明治大学大学院先端数理科学研究科) 16:50-18:20I will discuss Hamilton-Jacobi equation in the space of probability measures.
Two types of applications motivate the issue: one is from the probabilistic large deviation study of weakly interacting particle systems in statistical mechanics, another is from an infinite particle version of the variational formulation of Newtonian mechanics.
In creating respective well-posedness theories, two mathematical observations played important roles: One, the free-particle flow picture naturally leads to the use of the optimal mass transportation calculus. Two, there is a hidden symmetry (particle permutation invariance) for elements in the space of probability measures. In fact, the space of probability measures in this context is best viewed as an infinite dimensional quotient space. Using a natural metric, we are lead to some fine aspects of the optimal transportation calculus that connect with the metric space analysis and probability.
Time permitting, I will discuss an open issue coming up from the study of the Gibbs-Non-Gibbs transitioning by the Dutch probability community.
The talk is based on my past works with the following collaborators: Markos Katsoulakis, Tom Kurtz, Truyen Nguyen, Andrzej Swiech and Luigi Ambrosio.
ある化学反応系のモデリングとそのシミュレーション解析
