20 citations · 20 across the 7 of their papers we have counts for
7 papers
A catalog of exact steady states in Kolmogorov flow
Matthew Golden
Two-dimensional Kolmogorov flow is a common proving ground for the dynamical systems picture of turbulence. Hundreds of unstable periodic orbits have been found for this system acr…
An Explicit Sixth Order Runge-Kutta Method for Simple Lawson Integration
Matthew Golden
Explicit Runge-Kutta schemes become impractical when a stiff linear operator is present in the dynamics. This failure mode is quite common in numerical simulations of fluids and pl…
Data-driven discovery of the equations of turbulent convection
Christopher J. Wareing, Alasdair T. Roy, Matthew Golden +2
We compare the efficiency and ease-of-use of the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm and Sparse Physics-Informed Discovery of Empirical Relations (SPIDER)…
Scalable Discovery of Fundamental Physical Laws: Learning Magnetohydrodynamics from 3D Turbulence Data
Matthew Golden, Kaushik Satapathy, Dimitrios Psaltis
The discovery of dynamical models from data represents a crucial step in advancing our understanding of physical systems. Library-based sparse regression has emerged as a powerful…
Scalable Sparse Regression for Model Discovery: The Fast Lane to Insight
Matthew Golden
There exist endless examples of dynamical systems with vast available data and unsatisfying mathematical descriptions. Sparse regression applied to symbolic libraries has quickly e…
Covariant Guiding Center Equations for Charged Particle Motions in General Relativistic Spacetimes
Tyler Trent, Karin Roley, Matthew Golden +2
Low density plasmas in curved spacetimes, such as those found in accretion flows around black holes, are challenging to model from first principles, owing to the large scale separa…
Learning fluid physics from highly turbulent data using sparse physics-informed discovery of empirical relations (SPIDER)
Daniel R. Gurevich, Matthew R. Golden, Patrick A. K. Reinbold +1
We show how a complete mathematical description of a complicated physical phenomenon can be learned from observational data via a hybrid approach combining three simple and general…