Benjamin Beck | Searcharxiv

arXiv2022

Port-Hamiltonian inspired gradient diffusion model for magnetohydrodynamic turbulence

As a reduced representation of the nonlinear spectral fluxes of ideal invariants in incompressible magnetohydrodynamics, we construct a gradient-diffusion network model that combines phenomenological considerations and geometrical analysis of the exact nonlinear energy transfer function. The reduced-order representation of the conservative spectral transport of energy and cross-helicity is of port-Hamiltonian form, which highlights the flexibility and modularity of this approach. Numerical experiments with Reynolds numbers up to $~10^6$ yield clear power-law signatures of inertial-range energy spectra. Depending on the dominant timescale of energy transfer, Kolmogorov (-5/3), weak-turbulence (-2), or Iroshnikov-Kraichnan-like (-3/2) scaling exponents are observed. Anisotropic turbulence in a mean magnetic field is successfully modelled as well. The characteristic exponents of turbulence decay and the observed influence of cross-helicity on the energy transfer are consistent with the literature and in agreement with theoretical results.

physics.flu-dyn↗

arXiv2018

Principled Design and Implementation of Steerable Detectors

We provide a complete pipeline for the detection of patterns of interest in an image. In our approach, the patterns are assumed to be adequately modeled by a known template, and are located at unknown positions and orientations that we aim at retrieving. We propose a continuous-domain additive image model, where the analyzed image is the sum of the patterns to localize and a background with self-similar isotropic power-spectrum. We are then able to compute the optimal filter fulfilling the SNR criterion based on one single template and background pair: it strongly responds to the template while being optimally decoupled from the background model. In addition, we constrain our filter to be steerable, which allows for a fast template detection together with orientation estimation. In practice, the implementation requires to discretize a continuous-domain formulation on polar grids, which is performed using quadratic radial B-splines. We demonstrate the practical usefulness of our method on a variety of template approximation and pattern detection experiments. We show that the detection performance drastically improves when we exploit the statistics of the background via its power-spectrum decay, which we refer to as spectral-shaping. The proposed scheme outperforms state-of-the-art steerable methods by up to 50% of absolute detection performance.

eess.IV↗