arXiv subjects

Jeremiah Lübke

Publications and source records attributed to Jeremiah Lübke.

7 recordsLinked to original sources

arXiv2025

Modelling cosmic-ray transport: magnetised versus unmagnetised motion in astrophysical magnetic turbulence

Cosmic-ray transport in turbulent astrophysical environments remains a multifaceted problem and, despite decades of study, the impact of complex magnetic field geometry -- evident in simulations and observations -- has only recently received more focussed attention. To understand how ensemble-averaged transport behaviour emerges from the intricate interactions between cosmic rays and structured magnetic turbulence, we run test-particle experiments in snapshots of a strongly turbulent magnetohydrodynamics simulation. We characterise particle-turbulence interactions via the gyro radii of particles and their experienced field-line curvatures, which reveals two distinct transport modes: magnetised motion, where particles are tightly bound to strong coherent flux tubes and undergo large-scale mirroring; and unmagnetised motion, characterised by chaotic scattering through weak and highly tangled regions of the magnetic field. We formulate an effective stochastic process for each mode: compound subdiffusion with long mean free paths for magnetised motion, and a Langevin process with short mean free paths for unmagnetised motion. A combined stochastic walker that alternates between these two modes accurately reproduces the mean squared displacements observed in the test-particle data. Our results emphasise the critical role of coherent magnetic structures in comprehensively understanding cosmic-ray transport and lay a foundation for developing a theory of geometry-mediated transport.

physics.plasm-ph↗

arXiv2025

Anisotropic Cosmic Ray Transport in strong MHD Turbulence due to Magnetic Mirroring and Resonant Curvature Scattering

The transport of cosmic rays through turbulent astrophysical plasmas still constitutes an open problem. Building on recent progress, we study the combined effect of magnetic mirroring and resonant curvature scattering on parallel and perpendicular transport. We conduct test-particle simulations in snapshots of an anisotropic magnetohydrodynamics simulation with $δB/B_0\sim 1$ and record magnetic moment variation and field line curvature around pitch-angle reversals. We find for strongly magnetized particles that (i) pitch-angle reversals may occur either in coherent regions of the field with small variation of the magnetic moment via magnetic mirroring or in chaotic regions of the field with strong variation of the magnetic moment via resonant curvature scattering; (ii) parallel transport can be modeled as a Lévy walk with a truncated power-law distribution based on pitch-angle reversal times; and (iii) perpendicular transport is enhanced by resonant curvature scattering in synergy with chaotic field line separation and diminished by magnetic mirroring due to confinement in locally ordered field line bundles. While magnetic mirroring constitutes the bulk of reversal events, resonant curvature scattering additionally acts on trajectories that fall in the loss cones of typical mirroring structures and thus provides the cut-off for the reversal time distribution. Our results, which highlight the role of the magnetic field line geometry in cosmic-ray transport processes, are consistent with energy-independent diffusion coefficients. We conclude by considering how energy-dependent observations could arise from an intermittently inhomogeneous interstellar medium.

astro-ph.HE↗

arXiv2025

Synthetic Turbulence via an Instanton Gas Approximation

Sampling synthetic turbulent fields as a computationally tractable surrogate for direct numerical simulations (DNS) is an important practical problem in various applications, and allows to test our physical understanding of the main features of real turbulent flows. Reproducing higher-order Eulerian correlation functions, as well as Lagrangian particle statistics, requires an accurate representation of coherent structures of the flow in the synthetic turbulent fields. To this end, we propose in this paper a systematic coherent-structure based method for sampling synthetic random fields, based on a superposition of instanton configurations - an instanton gas - from the field-theoretic formulation of turbulence. We discuss sampling strategies for ensembles of instantons, both with and without interactions and including Gaussian fluctuations around them. The resulting Eulerian and Lagrangian statistics are evaluated numerically and compared against DNS results, as well as Gaussian and log-normal cascade models that lack coherent structures. The instanton gas approach is illustrated via the example of one-dimensional Burgers turbulence throughout this paper, and we show that already a canonical ensemble of non-interacting instantons without fluctuations reproduces DNS statistics very well. Finally, we outline extensions of the method to higher dimensions, in particular to magnetohydrodynamic turbulence for future applications to cosmic ray propagation.

physics.flu-dyn↗

arXiv2025

Optimal Landau-type closure parameters for two-fluid simulations of plasma turbulence at kinetic scales

Two fluid simulations using local Landau-fluid closures derived from linear theory provide an efficient computational framework for plasma modelling, since they bridge the gap between computationally intensive kinetic simulations and fluid descriptions. Their accuracy in representing kinetic effects depends critically on the validity of the linear approximation used in the derivation: the plasma should not be too far from local thermodynamic equilibrium, LTE. However, many of the problems where these models are of particular interest (such as plasma turbulence and instabilities) are in fact quite far from LTE. The question then arises, if kinetic scale processes are still sufficiently well captured outside of the theoretical regime of applicability of the closure. In this paper, we show that two fluid simulations with Landau fluid closures can effectively reproduce the energy spectra obtained with fully kinetic Vlasov simulations, used as references, as long as the local closure parameter is appropriately chosen. Our findings validate the usage of two fluid simulations with Landau-fluid closure as a possible alternative to fully kinetic simulations of turbulence, in cases where being able to simulate extremely large domains is of particular interest.

physics.plasm-ph↗

arXiv2025

Generation of cosmic ray trajectories by a Diffusion Model trained on test particles in 3D magnetohydrodynamic turbulence

Models for the transport of high energy charged particles through strong magnetic turbulence play a key role in space and astrophysical studies, such as describing the propagation of solar energetic particles and high energy cosmic rays. Inspired by the recent advances in high-performance machine learning techniques, we investigate the application of generative diffusion models to synthesizing test particle trajectories obtained from a turbulent magnetohydrodynamics simulation. We consider velocity increment, spatial transport and curvature statistics, and find excellent agreement with the baseline trajectories for fixed particle energies. Additionally, we consider two synthetic turbulence models for comparison. Finally, challenges towards an application-ready transport model based on our approach are discussed.

physics.flu-dyn↗

arXiv2024

Towards Synthetic Magnetic Turbulence with Coherent Structures

Synthetic turbulence is a relevant tool to study complex astrophysical and space plasma environments inaccessible by direct simulation. However, conventional models lack intermittent coherent structures, which are essential in realistic turbulence. We present a novel method, featuring coherent structures, conditional structure function scaling and fieldline curvature statistics comparable to magnetohydrodynamic turbulence. Enhanced transport of charged particles is investigated as well. This method presents significant progress towards physically faithful synthetic turbulence.

physics.space-ph↗

arXiv2022

Stochastic interpolation of sparsely sampled time series by a superstatistical random process and its synthesis in Fourier and wavelet space

We present a novel method for stochastic interpolation of sparsely sampled time signals based on a superstatistical random process generated from a multivariate Gaussian scale mixture. In comparison to other stochastic interpolation methods such as Gaussian process regression, our method possesses strong multifractal properties and is thus applicable to a broad range of real-world time series, e.g. from solar wind or atmospheric turbulence. Furthermore, we provide a sampling algorithm in terms of a mixing procedure that consists of generating a 1 + 1-dimensional field u(t, ξ), where each Gaussian component uξ(t) is synthesized with identical underlying noise but different covariance function Cξ(t,s) parameterized by a log-normally distributed parameter ξ. Due to the Gaussianity of each component uξ(t), we can exploit standard sampling alogrithms such as Fourier or wavelet methods and, most importantly, methods to constrain the process on the sparse measurement points. The scale mixture u(t) is then initialized by assigning each point in time t a ξ(t) and therefore a specific value from u(t, ξ), where the time-dependent parameter ξ(t) follows a log-normal process with a large correlation time scale compared to the correlation time of u(t, ξ). We juxtapose Fourier and wavelet methods and show that a multiwavelet-based hierarchical approximation of the interpolating paths, which produce a sparse covariance structure, provide an adequate method to locally interpolate large and sparse datasets.

physics.data-an↗