activity
20072023
most citedA robust numerical scheme for highly compressible magnetohydrodynamics: Nonlinear stability, implementation and tests

178 citations · 1.1k across the 54 of their papers we have counts for

collaborators

56 papers

math.NA2023★ 1 cited

Energy stable and conservative dynamical low-rank approximation for the Su-Olson problem

Lena Baumann, Lukas Einkemmer, Christian Klingenberg +1

Computational methods for thermal radiative transfer problems exhibit high computational costs and a prohibitive memory footprint when the spatial and directional domains are finel…

math.NA2023

A well-balanced semi-implicit IMEX finite volume scheme for ideal Magnetohydrodynamics at all Mach numbers

Claudius Birke, Walter Boscheri, Christian Klingenberg

We propose a second-order accurate semi-implicit and well-balanced finite volume scheme for the equations of ideal magnetohydrodynamics (MHD) including gravitational source terms.…

astro-ph.SR2022★ 17 cited

A finite-volume scheme for modeling compressible magnetohydrodynamic flows at low Mach numbers in stellar interiors

G. Leidi, C. Birke, R. Andrassy +5

Fully compressible magnetohydrodynamic (MHD) simulations are a fundamental tool for investigating the role of dynamo amplification in the generation of magnetic fields in deep conv…

math.AP2022★ 3 cited

Kinetic chemotaxis tumbling kernel determined from macroscopic quantities

Kathrin Hellmuth, Christian Klingenberg, Qin Li +1

Chemotaxis is the physical phenomenon that bacteria adjust their motions according to chemical stimulus. A classical model for this phenomenon is a kinetic equation that describes…

math.AP2022

Well-balanced Central Scheme for the System of MHD Equations with Gravitational source term

Farah Kanbar, Rony Touma, Christian Klingenberg

A well-balanced second order finite volume central scheme for the magnetohydrodynamic (MHD) equations with gravitational source term is developed in this paper. The scheme is an un…

q-fin.MF2022★ 3 cited

Computing Black Scholes with Uncertain Volatility-A Machine Learning Approach

Kathrin Hellmuth, Christian Klingenberg

In financial mathematics, it is a typical approach to approximate financial markets operating in discrete time by continuous-time models such as the Black Scholes model. Fitting th…