HYBRID DETERMINISTIC STOCHASTIC SYSTEMS WITH MICROSCOPIC LOOK-AHEAD DYNAMICS
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作者:
Katsoulakis, M. A.
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机构:
Univ Massachusetts, Dept Math & Stat, Amherst, MA 01003 USAUniv Massachusetts, Dept Math & Stat, Amherst, MA 01003 USA
Katsoulakis, M. A.
[1
]
Majda, A. J.
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机构:
NYU, Courant Inst Math Sci, New York, NY 10012 USA
NYU, Ctr Atmospher & Ocean Sci, New York, NY 10012 USAUniv Massachusetts, Dept Math & Stat, Amherst, MA 01003 USA
Majda, A. J.
[2
,3
]
Sopasakis, A.
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机构:
Univ N Carolina, Dept Math & Stat, Charlotte, NC 28223 USAUniv Massachusetts, Dept Math & Stat, Amherst, MA 01003 USA
Sopasakis, A.
[4
]
机构:
[1] Univ Massachusetts, Dept Math & Stat, Amherst, MA 01003 USA
[2] NYU, Courant Inst Math Sci, New York, NY 10012 USA
[3] NYU, Ctr Atmospher & Ocean Sci, New York, NY 10012 USA
[4] Univ N Carolina, Dept Math & Stat, Charlotte, NC 28223 USA
Coupled hybrid systems;
stochastic closures;
multiscale interactions;
look-ahead dynamics;
critical phenomena;
Monte Carlo Methods;
TRAFFIC FLOW;
MODELS;
D O I:
暂无
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
We study the impact of stochastic mechanisms on a coupled hybrid system consisting of a general advection-diffusion-reaction partial differential equation and a spatially distributed stochastic lattice noise model. The stochastic dynamics include both spin-flip and spin-exchange type interparticle interactions. Furthermore, we consider a new, asymmetric, single exclusion process, studied elsewhere in the context of traffic flow modeling, with an one-sided interaction potential which imposes advective trends on the stochastic dynamics. This look-ahead stochastic mechanism is responsible for rich nonlinear behavior in solutions. Our approach relies heavily on first deriving approximate differential mesoscopic equations. These approximations become exact either in the long range, Kac interaction partial differential equation case, or, given sufficient time separation conditions, between the partial differential equation and the stochastic model giving rise to a stochastic averaging partial differential equation. Although these approximations can in some cases be crude, they can still give a first indication, via linearized stability analysis, of the interesting regimes for the stochastic model. Motivated by this linearized stability analysis we choose particular regimes where interacting nonlinear stochastic waves are responsible for phenomena such as random switching, convective instability, and metastability, all driven by stochasticity. Numerical kinetic Monte Carlo simulations of the coarse grained hybrid system are implemented to assist in producing solutions and understanding their behavior.
机构:
School of Computer Science and Information Engineering, Chongqing Technology and Business University
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and TechnologySchool of Computer Science and Information Engineering, Chongqing Technology and Business University
JIANG Yun
SONG Tao
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机构:
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and TechnologySchool of Computer Science and Information Engineering, Chongqing Technology and Business University
SONG Tao
ZHANG Zheng
论文数: 0引用数: 0
h-index: 0
机构:
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and TechnologySchool of Computer Science and Information Engineering, Chongqing Technology and Business University