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In academic year 2007-2008, Universities of Orléans, Tours and Paris 13, the École Polytechnique in Palaiseau and the Vietnam National University-HCMUS started the French-Vietnamese Master 2 program in Applied Mathematics. In 2017, the program was extended until 2022 with two new partners: Universities of Lorraine and Rennes 1.
In this program, more than 170 students were awarded the Master diploma. Around sixty percent of them pursued a PhD degree, in France, Europe, the United States, Australia, ....
Many former graduate students have become lecturers and have initiated many new research topics at Vietnamese Universities, in domains such as Applied Numerical Analysis, Complex Variables, Informatics, Biomathematics, Computational Mechanics, ....
The Vietnamese-French conference in Applied Mathematics has the following objectives:
We will review recent results on the propagation
of waves on domains, with emphasis on two extreme
cases: the exterior or the interior of a stricly convex
domain. Understanding the wave localization, its
amplitude and how it decays is fundamental for
several (unrelated) problems and we will describe an
interesting interplay between geometrical aspects and
degenerate oscillatory integrals that model waves
Parareal method is a numerical method to solve time - evolutional problems in parallel, which uses two propagators: the coarse - fast and inaccurate - and the fine - slow but more accurate. Instead of running the fine propagator on the whole time interval, we divide the time space into small time intervals, where we can run the fine propagator in parallel to obtain the desired solution, with the help of the coarse propagator and through parareal steps. Furthermore, each local subproblem can be solved by an iterative method, and instead of doing this local iterative method until convergence, one may perform only a few iterations of it, during parareal iterations. Propagators then become much cheaper but sharply lose their accuracy, and we hope that the convergence will be achieved across parareal iterations.
In this talk, we propose to couple Parareal with a well-known iterative method - Optimized Schwarz Waveform Relaxation (OSWR) - with only few OSWR iterations in the fine propagator and with a simple coarse propagator deduced from Backward Euler method. We present the analysis of this coupled method for 1-dimensional advection reaction diffusion equation, for this case the convergence is almost linear. We also give some numerical illustrations for 1D and 2D equations, which shows that the convergence is much faster in practice.
We study the Multi-level Monte Carlo method introduced by Giles [3] and its applications to finance which is significantly more efficient than the classical Monte Carlo method. This method for the stochastic differential equations driven by only Brownian Motion had been studied by Ben Alaya and Kebaier [2]. Here, we consider the stochastic differential equation driven by a pure jump Lévy process. When the Lévy process have a Brownian component, the speed of convergence of the multilevel was recently studied by Dereich and Li [4].
Now, we prove the stable law convergence theorem in the spirit of Jacod [1]. More precisely, we consider the SDE of form
with
[1] Jean Jacod. The Euler scheme for Lévy driven stochastic differential equations: Limit theorems. The Annals of Probability, 2004, Vol.32, No.3A, 1830-1872.
[2] Mohamed Ben Alaya and Ahmed Kebaier. Central limit theorem for the multilevel Monte Carlo Euler method. Ann.Appl. Probab. 25(1): 211-234, 2015.
[3] Michael B.Giles. Multilevel Monte Carlo path simulation, Oper. Res., 56(3): 607-617, 2008.
[4] Steffen Dereich and Sangmeng Li. Multilevel Monte Carlo for Lévy-driven SDEs: Central limit theorems for adaptive Euler schemes. Ann. Appl. Probab., 26(1): 136-185, 2016.