تقرير
Data-driven computation methods for quasi-stationary distribution and sensitivity analysis
| العنوان: | Data-driven computation methods for quasi-stationary distribution and sensitivity analysis |
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| المؤلفون: | Li, Yao, Yuan, Yaping |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Mathematics - Dynamical Systems, Mathematics - Numerical Analysis, 37M05, 65C05, 65P99 |
| الوصف: | This paper studies computational methods for quasi-stationary distributions (QSDs). We first proposed a data-driven solver that solves Fokker-Planck equations for QSDs. Similar as the case of Fokker-Planck equations for invariant probability measures, we set up an optimization problem that minimizes the distance from a low-accuracy reference solution, under the constraint of satisfying the linear relation given by the discretized Fokker-Planck operator. Then we use coupling method to study the sensitivity of a QSD against either the change of boundary condition or the diffusion coefficient. The 1-Wasserstein distance between a QSD and the corresponding invariant probability measure can be quantitatively estimated. Some numerical results about both computation of QSDs and their sensitivity analysis are provided. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2103.01419 |
| رقم الأكسشن: | edsarx.2103.01419 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |