Zobrazeno 1 - 10
of 316
pro vyhledávání: '"Raeth, P."'
Semi-Lagrangian solvers for the Vlasov system offer noiseless solutions compared to Lagrangian particle methods and can handle larger time steps compared to Eulerian methods. In order to reduce the computational complexity of the interpolation steps,
Externí odkaz:
http://arxiv.org/abs/2406.09941
With the increase in computational capabilities over the last years it becomes possible to simulate more and more complex and accurate physical models. Gyrokinetic theory has been introduced in the 1960s and 1970s in the need of describing a plasma w
Externí odkaz:
http://arxiv.org/abs/2402.06605
Publikováno v:
Communications Physics volume 7, Article number: 254 (2024)
Minkowski tensors are comprehensive shape descriptors that robustly capture n-point information in complex random geometries and that have already been extensively applied in the Euclidean plane. Here, we devise a novel framework for Minkowski tensor
Externí odkaz:
http://arxiv.org/abs/2402.06286
Identifying and quantifying co-dependence between financial instruments is a key challenge for researchers and practitioners in the financial industry. Linear measures such as the Pearson correlation are still widely used today, although their limite
Externí odkaz:
http://arxiv.org/abs/2312.16185
Autor:
Köglmayr, Daniel, Räth, Christoph
Model-free and data-driven prediction of tipping point transitions in nonlinear dynamical systems is a challenging and outstanding task in complex systems science. We propose a novel, fully data-driven machine learning algorithm based on next-generat
Externí odkaz:
http://arxiv.org/abs/2312.06283
Early warning systems are an essential tool for effective humanitarian action. Advance warnings on impending disasters facilitate timely and targeted response which help save lives, livelihoods, and scarce financial resources. In this work we present
Externí odkaz:
http://arxiv.org/abs/2312.00626
Publikováno v:
Physical Review Research 6 (3), 033103 (2024)
We investigate the stationary (late-time) training regime of single- and two-layer underparameterized linear neural networks within the continuum limit of stochastic gradient descent (SGD) for synthetic Gaussian data. In the case of a single-layer ne
Externí odkaz:
http://arxiv.org/abs/2311.14120
Autor:
Raeth, Mario, Hallatschek, Klaus
First of a kind 6D-Vlasov computer simulations of high frequency ion Bernstein wave turbulence for parameters relevant to the tokamak edge show transport comparable to sub-Larmor-frequency gyrokinetic turbulence. The customary restriction of magnetiz
Externí odkaz:
http://arxiv.org/abs/2310.15981
Controlling nonlinear dynamical systems using machine learning allows to not only drive systems into simple behavior like periodicity but also to more complex arbitrary dynamics. For this, it is crucial that a machine learning system can be trained t
Externí odkaz:
http://arxiv.org/abs/2307.07195
In this paper, we describe our approach to develop a simulation software application for the fully kinetic Vlasov equation which will be used to explore physics beyond the gyrokinetic model. Simulating the fully kinetic Vlasov equation requires effic
Externí odkaz:
http://arxiv.org/abs/2303.05994