Stochastic Lohe Matrix Model on the Lie Group and Mean-Field Limit

被引:0
|
作者
Dohyun Kim
Jeongho Kim
机构
[1] National Institute for Mathematical Sciences,Institute of New Media and Communications
[2] Seoul National University,undefined
来源
关键词
Lohe matrix model; Mean-field limit; Stability; Stochastic process; 82C10; 82C22; 35Q84; 60H10;
D O I
暂无
中图分类号
学科分类号
摘要
We propose a Lohe matrix model in a random environment where each oscillator can be regarded as an element of a general matrix Lie group G. In order to make the stochastic system stays on G for all time, we introduce suitable noise terms so that the underlying manifold G is positively invariant under the stochastic system. Then, we formally derive the Fokker-Planck type equation defined on G×g\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G\times \mathfrak {g}$$\end{document} in which g\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathfrak {g}$$\end{document} denotes the Lie algebra corresponding to G. After identifying the target Fokker-Planck equation, we especially consider the unitary group G=U(d)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G=\mathbf {U}(d)$$\end{document} and show that the equation on U(d)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf {U}(d)$$\end{document} admits a global unique solution and that it can be rigorously derived using a stochastic mean-field limit procedure with a convergence rate of order O(1/N)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O(1/\sqrt{N})$$\end{document}. Finally, we restrict our concern to G=SU(2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G=\mathbf {SU}(2)$$\end{document} to provide explicit calculation and present the nonlinear stability of an incoherent state for the Fokker-Planck equation depending on the relation between parameters.
引用
收藏
页码:1467 / 1514
页数:47
相关论文
共 50 条
  • [41] MEAN-FIELD RENORMALIZATION-GROUP FOR THE POTTS-MODEL IN A TRANSVERSE FIELD
    MARQUES, MC
    SANTOS, MA
    [J]. JOURNAL OF PHYSICS C-SOLID STATE PHYSICS, 1986, 19 (22): : 4213 - 4221
  • [42] On the Mean-Field Spherical Model
    Michael Kastner
    Oliver Schnetz
    [J]. Journal of Statistical Physics, 2006, 122 : 1195 - 1214
  • [43] Stochastic Control of Memory Mean-Field Processes
    Nacira Agram
    Bernt Øksendal
    [J]. Applied Mathematics & Optimization, 2019, 79 : 181 - 204
  • [44] Transfer matrix test of the two-cell mean-field renormalization group
    Kamieniarz, G
    [J]. PHYSICA A, 1998, 256 (1-2): : 211 - 216
  • [45] Transfer matrix test of the two-cell mean-field renormalization group
    Kamieniarz, G.
    [J]. Physica A: Statistical Mechanics and its Applications, 1998, 256 (1-2): : 211 - 216
  • [46] MODEL-FREE MEAN-FIELD REINFORCEMENT LEARNING: MEAN-FIELD MDP AND MEAN-FIELD Q-LEARNING
    Carmona, Rene
    Lauriere, Mathieu
    Tan, Zongjun
    [J]. ANNALS OF APPLIED PROBABILITY, 2023, 33 (6B): : 5334 - 5381
  • [47] On the mean-field spherical model
    Kastner, M
    Schnetz, O
    [J]. JOURNAL OF STATISTICAL PHYSICS, 2006, 122 (06) : 1195 - 1213
  • [48] Stochastic Control of Memory Mean-Field Processes
    Agram, Nacira
    Oksendal, Bernt
    [J]. APPLIED MATHEMATICS AND OPTIMIZATION, 2019, 79 (01): : 181 - 204
  • [49] STOCHASTIC LIENARD EQUATION WITH MEAN-FIELD INTERACTION
    NARITA, K
    [J]. SIAM JOURNAL ON APPLIED MATHEMATICS, 1989, 49 (03) : 888 - 905
  • [50] Stochastic Mean-Field Approach to Fluid Dynamics
    Hochgerner, Simon
    [J]. JOURNAL OF NONLINEAR SCIENCE, 2018, 28 (02) : 725 - 737