Philipp Krah
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View article: Gyselalib++: A Portable C++ Library for Semi-Lagrangian Kinetic and Gyrokinetic Simulations
Gyselalib++: A Portable C++ Library for Semi-Lagrangian Kinetic and Gyrokinetic Simulations Open
Gyselalib++ provides the mathematical building blocks to construct kinetic or gyrokinetic plasma simulation codes in C++, simulating a distribution function discretised in phase space on a fixed grid. It relies on the Discrete Domain Compu…
View article: An adaptive quasi-neutrality solver for full-F flux-driven gyrokineticsimulations of tokamak plasmas in presence of poloidal asymmetries
An adaptive quasi-neutrality solver for full-F flux-driven gyrokineticsimulations of tokamak plasmas in presence of poloidal asymmetries Open
Gyrokinetic codes are used to simulate transport in tokamak plasmas. In theses codes, the distributionfunctions evolve simultaneously with an electromagnetic field. To compute the temporal evolution of theelectrostatic potential, a quasi-n…
View article: A Robust Shifted Proper Orthogonal Decomposition: Proximal Methods for Decomposing Flows with Multiple Transports
A Robust Shifted Proper Orthogonal Decomposition: Proximal Methods for Decomposing Flows with Multiple Transports Open
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View article: Parametric model order reduction for a wildland fire model via the shifted POD-based deep learning method
Parametric model order reduction for a wildland fire model via the shifted POD-based deep learning method Open
Parametric model order reduction techniques often struggle to accurately represent transport-dominated phenomena due to a slowly decaying Kolmogorov n -width. To address this challenge, we propose a non-intrusive, data-driven methodology t…
View article: A Characteristic Mapping Method with Source Terms: Applications to Ideal Magnetohydrodynamics
A Characteristic Mapping Method with Source Terms: Applications to Ideal Magnetohydrodynamics Open
This work introduces a generalized characteristic mapping method designed to handle non-linear advection with source terms. The semi-Lagrangian approach advances the flow map, incorporating the source term via the Duhamel integral. We deri…
View article: Automated transport separation using the neural shifted proper orthogonal decomposition
Automated transport separation using the neural shifted proper orthogonal decomposition Open
This paper presents a neural network-based methodology for the decomposition of transport-dominated fields using the shifted proper orthogonal decomposition (sPOD). Classical sPOD methods typically require an a priori knowledge of the tran…
View article: A Characteristic Mapping Method for Vlasov-Poisson with Extreme Resolution Properties
A Characteristic Mapping Method for Vlasov-Poisson with Extreme Resolution Properties Open
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View article: A robust shifted proper orthogonal decomposition: Proximal methods for decomposing flows with multiple transports
A robust shifted proper orthogonal decomposition: Proximal methods for decomposing flows with multiple transports Open
We present a new methodology for decomposing flows with multiple transports that further extends the shifted proper orthogonal decomposition (sPOD). The sPOD tries to approximate transport-dominated flows by a sum of co-moving data fields.…
View article: Synthesizing impurity clustering in the edge plasma of tokamaks using neural networks
Synthesizing impurity clustering in the edge plasma of tokamaks using neural networks Open
This work investigates the behavior of impurities in edge plasma of tokamaks using high-resolution numerical simulations based on Hasegawa–Wakatani equations. Specifically, it focuses on the behavior of inertial particles, which has not be…
View article: Zooming into Kinetic Equations using the Characteristic Mapping Method
Zooming into Kinetic Equations using the Characteristic Mapping Method Open
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View article: A Characteristic Mapping Method for Vlasov-Poisson with Extreme Resolution Properties
A Characteristic Mapping Method for Vlasov-Poisson with Extreme Resolution Properties Open
We propose an efficient semi-Lagrangian characteristic mapping method for solving the one+one-dimensional Vlasov-Poisson equations with high precision on a coarse grid. The flow map is evolved numerically and exponential resolution in line…
View article: Model Order Reduction for the 1D Boltzmann-BGK Equation: Identifying Intrinsic Variables Using Neural Networks
Model Order Reduction for the 1D Boltzmann-BGK Equation: Identifying Intrinsic Variables Using Neural Networks Open
Kinetic equations are crucial for modeling non-equilibrium phenomena, but their computational complexity is a challenge. This paper presents a data-driven approach using reduced order models (ROM) to efficiently model non-equilibrium flows…
View article: Front Transport Reduction for Complex Moving Fronts
Front Transport Reduction for Complex Moving Fronts Open
This work addresses model order reduction for complex moving fronts, which are transported by advection or through a reaction–diffusion process. Such systems are especially challenging for model order reduction since the transport cannot b…
View article: Parametric model order reduction for a wildland fire model via the shifted POD based deep learning method
Parametric model order reduction for a wildland fire model via the shifted POD based deep learning method Open
Parametric model order reduction techniques often struggle to accurately represent transport-dominated phenomena due to a slowly decaying Kolmogorov n-width. To address this challenge, we propose a non-intrusive, data-driven methodology th…
View article: Front Transport Reduction for Complex Moving Fronts
Front Transport Reduction for Complex Moving Fronts Open
# Front Transport Reduction for Complex Moving Fronts Authors: Philipp Krah, Steffen Büchholz, Matthias Häringer, Julius Reiss This Zenodo inlcudes the data for the Bunsen flame example. The data includes: + A1_F100.tar.gz .... openfoam da…
View article: Crystalline phases at finite winding densities in a quantum link ladder
Crystalline phases at finite winding densities in a quantum link ladder Open
Condensed matter physics of gauge theories coupled to fermions can exhibit a rich phase structure, butare nevertheless very difficult to study in Monte Carlo simulations when they are afflicted by a signproblem. As an alternate approach, w…
View article: Macro-micro decomposition for consistent and conservative model order reduction of hyperbolic shallow water moment equations: A study using POD-Galerkin and dynamical low rank approximation
Macro-micro decomposition for consistent and conservative model order reduction of hyperbolic shallow water moment equations: A study using POD-Galerkin and dynamical low rank approximation Open
Geophysical flow simulations using hyperbolic shallow water moment equations require an efficient discretization of a potentially large system of PDEs, the so-called moment system. This calls for tailored model order reduction techniques t…
View article: Crystalline phases at finite winding densities in a quantum link ladder
Crystalline phases at finite winding densities in a quantum link ladder Open
Condensed matter physics of gauge theories coupled to fermions can exhibit a rich phase structure, but are nevertheless very difficult to study in Monte Carlo simulations when they are afflicted by a sign problem. As an alternate approach,…
View article: Phases at finite winding number of an Abelian lattice gauge theory
Phases at finite winding number of an Abelian lattice gauge theory Open
Pure gauge theories are rather different from theories with pure scalar and fermionic matter, especially in terms of the nature of excitations. For example, in scalar and fermionic theories, one can create ultra-local excitations. For a ga…
View article: Data-driven reduced order modeling for flows with moving geometries using shifted POD
Data-driven reduced order modeling for flows with moving geometries using shifted POD Open
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View article: Front Transport Reduction for Complex Moving Fronts
Front Transport Reduction for Complex Moving Fronts Open
This work addresses model order reduction for complex moving fronts, which are transported by advection or through a reaction-diffusion process. Such systems are especially challenging for model order reduction since the transport cannot b…
View article: Phases at finite winding number of an Abelian lattice gauge theory
Phases at finite winding number of an Abelian lattice gauge theory Open
Pure gauge theories are rather different from theories with pure scalar and fermionic matter, especially in terms of the nature of excitations. For example, in scalar and fermionic theories, one can create ultra-local excitations. For a ga…
View article: Shifted Proper Orthogonal Decomposition and Artificial Neural Networks for Time-Continuous Reduced Order Models of Transport-Dominated Systems
Shifted Proper Orthogonal Decomposition and Artificial Neural Networks for Time-Continuous Reduced Order Models of Transport-Dominated Systems Open
Transport-dominated systems are pervasive in both industrial and scientific applications. However, they provide a challenge for common mode-based model order reduction (MOR) approaches, as they often require a large number of linear modes …
View article: Supervised Learning for Multi Zone Sound Field Reproduction under Harsh Environmental Conditions
Supervised Learning for Multi Zone Sound Field Reproduction under Harsh Environmental Conditions Open
This manuscript presents an approach for multi zone sound field reproduction using supervised learning. Traditional multi zone sound field reproduction methods assume constant speed of sound, neglecting nonlinear effects like wind and temp…
View article: Wavelet Adaptive Proper Orthogonal Decomposition for Large Scale Flow Data
Wavelet Adaptive Proper Orthogonal Decomposition for Large Scale Flow Data Open
The proper orthogonal decomposition (POD) is a powerful classical tool in fluid mechanics used, for instance, for model reduction and extraction of coherent flow features. However, its applicability to high-resolution data, as produced by …