TY  - CONF
AU  - Fernandez Corral, Alvaro
AU  - Mendoza, Sebastian
AU  - Yachmenev, Andrey
AU  - Iske, Armin
AU  - Küpper, Jochen
TI  - Learning phase-space flows using time-discrete implicit Runge-Kutta PINNs
M1  - PUBDB-2024-00205
SP  - 26
PY  - 2024
N1  - https://bib-pubdb1.desy.de/record/603801
AB  - We present a computational framework for obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations, using high-order implicit Runge-Kutta Physics-Informed Neural Networks (IRK-PINNs) schemes. Building upon foundational work originally solving differential equations for fields depending on coordinates [J. Comput. Phys. 378, 686 (2019)],we adapt the scheme to a context where the coordinates are treated as functions. This modification enables us to efficiently solve equations of motion for a particle in an external field. Our scheme is particularly useful for explicitly time-independent and periodic fields. We apply this approach to successfully solve the equations of motion for a mass particle placed in a central force field and acharged particle in a periodic electric field.
T2  - International Conference on Scientific Computing and Machine Learning 2024
CY  - 19 Mar 2024 - 23 Mar 2024, Kyoto (Japan)
Y2  - 19 Mar 2024 - 23 Mar 2024
M2  - Kyoto, Japan
LB  - PUB:(DE-HGF)8
UR  - https://bib-pubdb1.desy.de/record/601475
ER  -