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• W3149021651 abstract "We introduce a nonlinear stochastic model reduction technique for high-dimensional stochastic dynamical systems that have a low-dimensional invariant effective manifold with slow dynamics, and high-dimensional, large fast modes. Given only access to a black box simulator from which short bursts of simulation can be obtained, we estimate the invariant manifold, a process of the effective (stochastic) dynamics on it, and construct an efficient simulator thereof. These estimation steps can be performed on-the-fly, leading to efficient exploration of the effective state space, without losing consistency with the underlying dynamics. This construction enables fast and efficient simulation of paths of the effective dynamics, together with estimation of crucial features and observables of such dynamics, including the stationary distribution, identification of metastable states, and residence times and transition rates between them." @default.
• W3149021651 created "2021-04-13" @default.
• W3149021651 creator A5050648341 @default.
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• W3149021651 date "2021-04-05" @default.
• W3149021651 modified "2023-09-27" @default.
• W3149021651 title "Nonlinear model reduction for slow-fast stochastic systems near manifolds" @default.
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• W3149021651 hasPublicationYear "2021" @default.
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