Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Lukas Exl"'
Autor:
Lukas Exl
Publikováno v:
Results in Applied Mathematics, Vol 1, Iss , Pp - (2019)
An optimization-based approach for Tucker tensor approximation of parameter-dependent data tensors and solutions of tensor differential equations with low Tucker rank is presented. The problem of updating the tensor decomposition is reformulated as a
Externí odkaz:
https://doaj.org/article/ad645df82c4a47f6b7e0ec8c8f1c87b8
Autor:
Axel U J Lode, Fritz S Diorico, RuGway Wu, Paolo Molignini, Luca Papariello, Rui Lin, Camille Lévêque, Lukas Exl, Marios C Tsatsos, R Chitra, Norbert J Mauser
Publikováno v:
New Journal of Physics, Vol 20, Iss 5, p 055006 (2018)
We consider laser-pumped one-dimensional two-component bosons in a parabolic trap embedded in a high-finesse optical cavity. Above a threshold pump power, the photons that populate the cavity modify the effective atom trap and mediate a coupling betw
Externí odkaz:
https://doaj.org/article/7a313e69367d4fb3a3030e5fe4b57640
Autor:
Sebastian Schaffer, Thomas Schrefl, Harald Oezelt, Alexander Kovacs, Leoni Breth, Norbert J. Mauser, Dieter Suess, Lukas Exl
We study the full 3d static micromagnetic equations via a physics-informed neural network (PINN) ansatz for the continuous magnetization configuration. PINNs are inherently mesh-free and unsupervised learning models. In our approach we can learn to m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39202a0f4bd1d7fca50ea0bd217e62d8
http://arxiv.org/abs/2301.13508
http://arxiv.org/abs/2301.13508
Autor:
Claus O. W. Trost, Stanislav Zak, Sebastian Schaffer, Christian Saringer, Lukas Exl, Megan J. Cordill
As the need for miniaturized structural and functional materials has increased,the need for precise materials characterizaton has also expanded. Nanoindentation is a popular method that can be used to measure material mechanical behavior which enable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dc3355d6d770b93eb4dea3fb2fb9b54
http://arxiv.org/abs/2207.00243
http://arxiv.org/abs/2207.00243
Autor:
Alexander Kovacs, Lukas Exl, Alexander Kornell, Johann Fischbacher, Markus Hovorka, Markus Gusenbauer, Leoni Breth, Harald Oezelt, Masao Yano, Noritsugu Sakuma, Akihito Kinoshita, Tetsuya Shoji, Akira Kato, Thomas Schrefl
We demonstrate the use of model order reduction and neural networks for estimating the hysteresis properties of nanocrystalline permanent magnets from microstructure. With a data-driven approach, we learn the demagnetization curve from data-sets crea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::284c88693612a1cbb1130b845a739b11
http://arxiv.org/abs/2203.16676
http://arxiv.org/abs/2203.16676
Autor:
Alexander Kovacs, Lukas Exl, Alexander Kornell, Johann Fischbacher, Markus Hovorka, Markus Gusenbauer, Leoni Breth, Harald Oezelt, Dirk Praetorius, Dieter Suess, Thomas Schrefl
Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated with neural networks. Minimizing the residuals of the static Maxwell equation at collocation points
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::759ad1052bb91af9b87ef81ada31defd
http://arxiv.org/abs/2106.03362
http://arxiv.org/abs/2106.03362
Autor:
Lukas Exl, Thomas Schrefl, Alexander Kovacs, Markus Gusenbauer, Harald Oezelt, Johann Fischbacher
Publikováno v:
Computer Physics Communications. 235:179-186
Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner for a nonlinear conjugate gradient energy minimizer can lead to a speed
Autor:
Lukas Exl
Publikováno v:
Journal of Mathematical Analysis and Applications. 467:230-237
A formula for the magnetostatic energy of a finite magnet is proven. In contrast to common approaches, the new energy identity does not rely on evaluation of a nonlocal boundary integral inside the magnet or the solution of an equivalent Dirichlet pr
Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-dependent problems in micromagnetism such as fast response curve estimat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f153bb0b6e17451d7445e9052da63735
Publikováno v:
Handbook of Magnetism and Magnetic Materials ISBN: 9783030631017
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5f7c35724570fe9eb735fd1f5c5cb00
https://doi.org/10.1007/978-3-030-63101-7_7-1
https://doi.org/10.1007/978-3-030-63101-7_7-1