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Short Course on Tensor Numerical Methods in Scientific Computing

November 18 / 12:00 - December 6 / 12:00

Prof. Dr. Boris Khoromskij   with the assistance of Dr. Venera Khoromskaia is offering a short course on Tensor Numerical Methods in Scientific Computing at Trier University on behalf of the Research Training Group on Algorithmic Optimization. 

The course will consist of several two hour lectures as follows:

Monday,                           18 Nov 2019                   12:00 – 14:00                                                E 52

Tuesday,                          19 Nov 2019                   10:00 – 12:00                                                E 45

Wednesday,                     20 Nov 2019                   14:00 – 16:00                                              HS 10

Thursday,                         21 Nov 2019                   14:00 – 16:00                                                E 10

Friday,                               22 Nov 2019                  10:00 – 12:00                                                E 44

Monday,                              2 Dec 2019                   12:00 – 14:00                                                E 52

Tuesday,                             3 Dec 2019                   10:00 – 12:00                                                E 45

Wednesday,                       4 Dec 2019                    14:00 – 16:00                                              HS 10

Thursday,                           5 Dec 2019                   12:00 – 14:00                                                E 10

Friday,                                 6 Dec 2019                   10:00 – 12:00                                                E 44

Course Abstract:
Solution of multi-dimensional problems by traditional numerical methods suffer from the so-called “curse of dimensionality”, that cannot be eliminated by using parallel architectures and high performance computing. The novel tensor numerical methods are based on a “smart” rank-structured tensor   representation of the multivariate functions and operators, thus reducing solution of multidimensional integral-differential equations to 1D   calculations. We show how the canonical, Tucker, tensor train (TT), quantized-TT (QTT) and range-separated tensor approximations  provide the way to solve the multi-dimensional equations on  low-parametric rank-structured manifolds. We consider tensor methods for the elliptic optimal control problems, for elliptic PDEs with oscillating coefficients and for some quantum chemical  models. Matlab exercises for the tensor decomposition algorithms will be provided.

For a printout of this information, please click here.

 

Details

Start:
November 18 / 12:00
End:
December 6 / 12:00
Event Category:

Organizer

RTG ALOP at Trier University
Phone:
0651-2013461
Email:
ALOP@uni-trier.de


ALOP