News&Events

Math-Fi seminar on 23 May (Co-organized as a Quantum Walk Seminar)

2024.05.21 Tue up
  • Date: 23 May (Thu.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker:Daiju Funakawa(Hokkai-Gakuen University)
  • Title:量子ウォークにおけるスペクトル写像定理とこれを用いた展望
  • Abstract : 量子ウォークはデバイスにレーザーを透過・偏極させることで実装される数理モデルであり,量子探索アルゴリズムやトポロジカル絶縁体などへの応用が期待されている。量子ウォークの記述する時間発展作用素の性質を調べる際,そのスペクトルを計算し関数解析学の観点から研究することができる。さて,スペクトル写像定理は量子ウォークのスペクトルとランダムウォークとユニタリ同値なdiscriminant作用素のスペクトルとの対応を述べた定理であり,これを用いてSplit-Step量子ウォークなどのスペクトルも調べられている。このスペクトル写像定理は量子ウォークが閉鎖系でカイラル対称な場合,2019年に一般論として瀬川らによって証明されている。さらに2023年には,浅原らによって一部の開放系量子ウォークのための拡張が行われた。本講演ではこれらの定理や応用などを紹介しつつ,更なる拡張についてお話する。

Math-Fi seminar on 25 Apr. (Co-organized as a Quantum Walk Seminar)

2024.04.24 Wed up
  • Date: 25 Apr. (Thu.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker: 楯 辰哉 (東北大学)
  • Title: 1 次元 2 状態量子ウォークの一般固有関数展開
 

Math-Fi seminar on 18 Apr.

2024.04.16 Tue up
Date: 18 Apr. (Thu.)
Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
Time: 16:30 – 18:30
 
Speaker 1: Jie Yen Fan (Monash University)
Title: Mimicking: Martingales with Matching Marginals (Lecture 2)
Abstract: Click here

Speaker 2: Ju-YI Yen (University of Cincinnati)
Title : A brief discussion on Brownian motion and related processes with applications (Lecture 2)
Abstract: Click here

Math-Fi seminar on 11 Apr.

2024.04.10 Wed up
Date: 11 Apr. (Thu.)
Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
Time: 16:30 – 18:30
 
Speaker 1: Gabriel Berzunza Ojeda (University of Liverpool)
Title: Fragmentation Process derived from $\alpha$-stable Galton-Watson trees (Lecture 2) 
Abstract: Click here

Speaker 2: Ronnie Loeffen  (University of Liverpool)
Title : Optimal control of risk processes in insurance  (Lecture 2)
Abstract: Click here
 

Symposium [April 2-5, 2024]

2024.03.21 Thu up
”8th Ritsumeikan-Monash Symposium on Probability and Related Fields”
 
Date: April 2(Tue)–5(Fri), 2024
Place: Ritsumeikan University, Biwako-Kusatsu Campus, West Wing 6F,  Colloquium Room 
 

Math-Fi seminar on 21 Dec.

2023.12.19 Tue up
  • Date: 21 Dec. (Thu.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker: Noriyoshi Sakuma (Nagoya City University)
  • Title: The Outlier Problem from a View of non-commutative Probability Theory I
  • Abstract:
The outlier problem in random matrix theory is one of the important topics. In this talk, I will explain a non-commutative probabilistic method for considering the outlier problem. The notion of cyclic monotone independence plays a similar role to that of free independence. If time permits, I will also introduce nonrandom models.
 

Math-Fi seminar on 18 Dec.

2023.12.12 Tue up
  • Date: 18 Dec. (Mon.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker: Hau-Tieng Wu (Courant Institute of Mathematical Sciences at New York University)
  • Title: Nonstationary biorhythm analysis through landmark diffusion with clinical application
  • Abstract:
Compared with the commonly collected health information, long-term and high-frequency physiological time series that exhibit nonstationary traits provide abundant information from an alternative perspective. However, it is challenging to extract clinically applicable data from these raw time series due to various impediments. Fueled by clinical necessities, physiological expertise, and clinical observations, we introduce a novel latent diffusion geometry-based signal processing method. The algorithm is explicitly designed to handle enormous datasets, including ultra-long and high-frequency time series, with ease, while remaining resilient to color and heterogeneous noise, underpinned by sound theoretical support. We will discuss an application of this method to assess the clinical outcome of liver transplants by uncovering the delicate details concealed in the arterial blood pressure signal recorded during surgery that remain indistinguishable to the naked eye.

Math-Fi seminar on 30 Nov.

2023.11.24 Fri up
  • Date: 30 Nov. (Thu.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker: Andrea Macrina (University College London)
  • Title: Filtered Arcade Martingales: An Alternative Approach to Martingale Optimal Transport?
  • Abstract:
Arcade processes are a class of continuous stochastic processes that interpolate in a strong sense between zeros at fixed pre-specified times. Their additive randomization allows one to match any finite sequence of target random variables, indexed by the given fixed dates, on the whole probability space. The filtrations generated by such processes are utilized to construct a class of martingales which interpolate between the given target random variables. These so-called filtered arcade martingales (FAMs) are almost-sure solutions to the martingale interpolation problem and reveal an underlying stochastic filtering structure. In the special case of conditionally Markov randomized arcade processes, the dynamics of FAMs are informed through Bayesian updating. FAMs can be connected to martingale optimal transport (MOT) by considering optimally coupled target random variables. Moreover, FAMs allow to formulate an information-based martingale optimal transport problem, which enables the introduction of noise in MOT, in a similar fashion to how Schrödinger’s problem introduces noise in optimal transport. This information-based transport problem is concerned with selecting an optimal martingale coupling for the target random variables under the influence of the noise that is generated by an arcade process. 

Workshop [November 4-5, 2023]

2023.10.16 Mon up
”Ritsumeikan Workshop on Stochastic Analysis”
 
Date: November 4(Sat)–5(Sun), 2023
Place: Ritsumeikan University, Biwako-Kusatsu Campus, West Wing 6F,  Colloquium Room 
 

Math-Fi seminar on 12 Oct.

2023.10.06 Fri up
  • Date: 12 Oct. (Thu.)
  • Place: W.W. 6th-floor, Colloquium Room and on the Web (Zoom)
  • Time: 16:30 – 18:00
  • Speaker: Syoiti Ninomiya (Tokyo Institute of Technology)
  • Title: 確率微分方程式の高次弱近似アルゴリズムの構造を模った深層学習機械
  • Abstract:
確率微分方程式の高次弱近似アルゴリズムの構造を模したネットワーク構造を持つ深層学習機械を提案する. この機械は学習によってある拡散過程を得ること—具体的には金融派生商品のヘッジ戦略をこの機械によって「陽に得る」こと—を目的とするものである. 実際にこれらを作成して数値実験を行なったところ, 高次弱近似に基づく機械はアメリカンオプションの価格計算とそのヘッジ過程を学習することに成功した.