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東京確率論セミナー
過去の記録 ～01/10｜次回の予定｜今後の予定 01/11～
| 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）、星野壮登（東京科学大学） |
| セミナーURL | https://sites.google.com/view/tokyo-probability-seminar23/ |
今後の予定
2026年01月14日(水)
15:00-17:30 数理科学研究科棟(駒場) 126号室
Xia Chen 氏 (University of Tennessee) 15:00-16:00
Hyperbolic Anderson equations and Brownian intersection local times
Moderate deviations for the capacity of the random walk range
Xia Chen 氏 (University of Tennessee) 15:00-16:00
Hyperbolic Anderson equations and Brownian intersection local times
[ 講演概要 ]
An idea recently merged from the investigation of hyperbolic Anderson equations is
to represent the chaos expansion of the solution in terms of Brownian intersection local
times. In this talk, I will address effeteness, current state, potentials and challenge about
this method.bPart of the talk comes from the work joined with Yaozhong Hu
Jiyun Park 氏 (Stanford University) 16:30-17:30An idea recently merged from the investigation of hyperbolic Anderson equations is
to represent the chaos expansion of the solution in terms of Brownian intersection local
times. In this talk, I will address effeteness, current state, potentials and challenge about
this method.bPart of the talk comes from the work joined with Yaozhong Hu
Moderate deviations for the capacity of the random walk range
[ 講演概要 ]
It is known that the capacity of the range of a random walk in d dimensions behaves similarly to the volume of the random walk in d-2 dimensions. In this talk, we extend this analogy to the moderate deviations of the capacity in dimension 5. In particular, we demonstrate that the large deviation principle transitions from a Gaussian tail to a non-Gaussian tail depending on the deviation scale. We also improve previously known results for dimension 4. Based on joint work with Arka Adhikari.
It is known that the capacity of the range of a random walk in d dimensions behaves similarly to the volume of the random walk in d-2 dimensions. In this talk, we extend this analogy to the moderate deviations of the capacity in dimension 5. In particular, we demonstrate that the large deviation principle transitions from a Gaussian tail to a non-Gaussian tail depending on the deviation scale. We also improve previously known results for dimension 4. Based on joint work with Arka Adhikari.
