288 citations · 1.1k across the 43 of their papers we have counts for
43 papers
Physics-informed data-driven inference of an interpretable equivariant LES model of incompressible fluid turbulence
Matteo Ugliotti, Brandon Choi, Mateo Reynoso +2
Restrictive phenomenological assumptions represent a major roadblock for the development of accurate subgrid-scale models of fluid turbulence. Specifically, these assumptions limit…
Data-driven modeling of multiscale phenomena with applications to fluid turbulence
Brandon Choi, Matteo Ugliotti, Mateo Reynoso +2
This paper introduces a novel data driven framework for constructing accurate and general equivariant models of multiscale phenomena which does not rely on specific assumptions abo…
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)…
Ultra-low-energy defibrillation through adjoint optimization
Alejandro Garzon, Roman O. Grigoriev
This study investigates ultra-low-energy defibrillation protocols using a simple two-dimensional model of cardiac tissue. We find that, rather counter-intuitively, a single, proper…
Self-similarity and the direct (enstrophy) cascade in two-dimensional fluid turbulence
Mateo Reynoso, Dmitriy Zhigunov, Roman O. Grigoriev
A widely used statistical theory of 2D turbulence developed by Kraichnan, Leith, and Batchelor (KLB) predicts a power-law scaling for the energy, with an integral…
Computing Chaotic Time-Averages from Few Periodic or Non-Periodic Orbits
Joshua L. Pughe-Sanford, Sam Quinn, Teodor Balabanski +1
For appropriately chosen weights, temporal averages in chaotic systems can be approximated as a weighted sum of averages over reference states, such as unstable periodic orbits. Un…