Applied and Computational Mathematics (ACM)

Artificial Boundary Conditions

When computing numerically the solution of a partial differential equation in an unbounded domain usually artificial boundaries are introduced to limit the computational domain. Special boundary conditions are derived at this artificial boundaries to approximate the exact whole-space solution. If the solution of the problem on the bounded domain is equal to the whole-space solution (restricted to the computational domain) these boundary conditions are called transparent boundary conditions (TBCs).

We are concerned with TBCs for general Schrödinger-type pseudo-differential equations arising from `parabolic' equation (PE) models which have been widely used for one-way wave propagation problems in various application areas, e.g. (underwater) acoustics, seismology, optics and plasma physics. As a special case the Schrödinger equation of quantum mechanics is included.

Existing discretizations of these TBCs induce numerical reflections at this artificial boundary and also may destroy the stability of the used finite difference method. These problems do not occur when using a so-called discrete TBC which is derived from the fully discretized whole-space problem. This discrete TBC is reflection-free and conserves the stability properties of the whole-space scheme. We point out that the superiority of discrete TBCs over other discretizations of TBCs is not restricted to the presented special types of partial differential equations or to our particular interior discretization scheme.

Another problem is the high numerical effort. Since the discrete TBC includes a convolution with respect to time with a weakly decaying kernel, its numerical evaluation becomes very costly for long-time simulations. As a remedy we construct new approximative TBCs involving exponential sums as an approximation to the convolution kernel. This special approximation enables us to use a fast evaluation of the convolution type boundary condition.

Finally, to illustrate the broad range of applicability of our approach we derived efficient discrete artificial boundary conditions for the Black-Scholes equation of American options.

Software

Our approach was implemented by C.A. Moyer in the QMTools software package for quantum mechanical applications.

Publications



2025

5500.

Hellmig, Lutz; Burk, Steffen; Hennecke, Martin; Herper, Henry; Hilbig, André; Michaeli, Tilman; Mittag, Alexander; Pasternak, Arno; Puhlmann, Hermann; Röhner, Gerhard; Rücker, Michael; Schmalfeldt, Thomas; Spalteholz, Wolf; Stechert, Peer
Bildungsstandards Informatik für die Sekundarstufe I – Empfehlungen der Gesellschaft für Informatik
Herausgeber: Gesellschaft für Informatik e.V.
2025

5499.

Kiesling, Elisabeth; Bohrmann-Linde, Claudia
Carbon Capture and Storage - Nachweis von adsorbiertem Kohlenstoffdioxid
Naturwissenschaften im Unterricht Chemie, 1/25 :Versuchskarteikarte
2025

5498.

Clément, François; Doerr, Carola; Klamroth, Kathrin; Paquete, Luís
Constructing Optimal Star Discrepancy Sets
accepted in Proceedings of the AMS
2025

5497.

Diaz, Ignacio; Gorrec, Yann Le; Wu, Yongxin
Control Oriented Modular Modelling of a Floating Wind Turbine: The Port-Hamiltonian Approach
IFAC-PapersOnLine, 59 (8) :125-130
2025

5496.

Schaller, Manuel; Schmitz, Merlin; Jacob, Birgit; Farkas, Bálint
Dissipativity-based time domain decomposition for optimal control of hyperbolic {PDE}s
2025

5495.

Lachetta, Michael; Schmitz, Denise; Morawski, Michael; Humbert, Ludger; Kuckuck, Miriam
Einschätzungen von Grundschullehrkräften zur Relevanz von informatischer Bildung in der Grundschule
Seite 93-109
Herausgeber: Verlag Julius Klinkhardt, Bad Heilbrunn
2025
93-109

5494.

Holzenkamp, Matthias; Lyu, Dongyu; Kleinekathöfer, Ulrich; Zaspel, Peter
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials.
Machine Learning: Science and Technology
2025

5493.

Lyu, Dongyu; Vinod, Vivin; Holzenkamp, Matthias; Holtkamp, Yannick M.; Maity, Sayan; Salazar, Carlos R.; Kleinekathöfer, Ulrich; Zaspel, Peter
Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine Learning.
Adv. Theory Simul., 8 (11) :e00271
2025

5492.

Song, Yongcun; Wang, Ziqi; Zuazua, Enrique
FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning
Neural Network, 181
Januar 2025

5491.

Kienitz, J; Moodliyar, L
Gaussian views explained
Wilmott, 2025 (135) :72–77
2025
Herausgeber: Wilmott Magazine

5490.

Xu, Zhuo; Tucsnak, Marius
Global Exponential Stabilization for a Simplified Fluid-Particle Interaction System
Januar 2025

5489.

Bartel, Andreas; Schaller, Manuel
Goal-oriented time adaptivity for port-Hamiltonian systems
Journal of Computational and Applied Mathematics, 461 :116450
2025
ISSN: 0377-0427

5488.

Schmitz, Denise
Grundschullehrkräfte zwischen informatischer Bildung und Medienbildung
In Jan Grey, Denise Schmitz, Inga Gryl, Alexander Best, Miriam Kuckuck, Ludger Humbert, Editor
Seite 41-50
Herausgeber: Verlag Julius Klinkhardt, Bad Heilbrunn
2025
41-50

5487.

Grey, Jan; Schmitz, Denise; Gryl, Inga; Best, Alexander; Kuckuck, Miriam; Humbert, Ludger
Herausforderungen und Möglichkeiten informatischer Bildung in der Grundschule
In Jan Grey, Denise Schmitz, Inga Gryl, Alexander Best, Miriam Kuckuck, Ludger Humbert, Editor
Seite 7-23
Herausgeber: Verlag Julius Klinkhardt, Bad Heilbrunn
2025
7-23

5486.

Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators
Computer Physics Communications, 309 :109478
2025
ISSN: 0010-4655

5485.

Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators
Computer Physics Communications, 309 :109478
2025
ISSN: 0010-4655

5484.

Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators and their application to lattice QCD simulations
PoS, LATTICE2024 :025
2025

5483.

Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators and their application to lattice QCD simulations
PoS, LATTICE2024 :025
2025

5482.

Krhac, Kaja; Schuller, Frederic P.; Stramigioli, Stefano
Hybrid Schrödinger-Liouville and projective dynamics
IFAC-PapersOnLine, 59 (8) :208-213
2025

5481.

Shaju, K.; Laepple, T.; Hirsch, N.; Zaspel, P.
Ice borehole thermometry: Sensor placement using greedy optimal sampling
Geoscientific Instrumentation, Methods and Data Systems, 14 (2) :459—474
2025

5480.

Brinda, Torsten; Diethelm, Ira; Dittert, Nadine; Humbert, Ludger; Kramer, Matthias; Losch, Daniel; Schmitz, Denise
Informatics Competencies for All Teachers - Development of Recommendations for Teacher Education
OCCE 2024
Bournemouth, UK
2025

5479.

Bergner, Nadine; Humbert, Ludger; Schmitz, Denise; Fricke, Martin
Informatik kommt in die Grundschule
In Jan Grey, Denise Schmitz, Inga Gryl, Alexander Best, Miriam Kuckuck, Ludger Humbert, Editor
Seite 231-249
Herausgeber: Verlag Julius Klinkhardt, Bad Heilbrunn
2025
231-249

5478.

Hilbig, André; Schmitz, Denise
Informatikdidaktische Sicht auf Barrierefreiheit als Unterrichts- und Forschungsgegenstand
INFOS 2025 – 21. GI-Fachtagung Informatik und Schule
Stoos, Schweiz
2025

5477.

Vinod, Vivin; Zaspel, Peter
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
J. Chem. Theory Comput., 21 (6) :3077-3091
2025

5476.

[german] Grandrath, Rebecca; Orhan, Nalan; Bohrmann-Linde, Claudia
Konzeption einer Projektwoche zu den Themen Food Waste und Food Loss für die gymnasiale Oberstufe
In Andreas Keil, Annika Hanau und Julian Dietze (Hg.): BNE in der Lehrkräftebildung. Erkenntnisse aus Forschung und Praxis., Editor
Seite 315-325
Herausgeber: Waxmann
2025
315-325