629 citations · 1.7k across the 20 of their papers we have counts for
24 papers
Separation of periodic orbits in the delay embedded space of chaotic attractors
Prerna Patil, Eurika Kaiser, J Nathan Kutz +1
This work explores the intersection of time-delay embeddings, periodic orbit theory, and symbolic dynamics. Time-delay embeddings have been effectively applied to chaotic time seri…
Control of Vortex Dynamics using Invariants
Kartik Krishna, Aditya G. Nair, Anand Krishnan +2
Vortex-dominated flows are ubiquitous in engineering, and the ability to efficiently manipulate the dynamics of these vortices has broad applications, from wake shaping to mixing e…
PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator
Shaowu Pan, Eurika Kaiser, Brian M. de Silva +2
PyKoopman is a Python package for the data-driven approximation of the Koopman operator associated with a dynamical system. The Koopman operator is a principled linear embedding of…
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton, Marko Budišić, Eurika Kaiser +1
The field of dynamical systems is being transformed by the mathematical tools and algorithms emerging from modern computing and data science. First-principles derivations and asymp…
Bilinear dynamic mode decomposition for quantum control
Andy Goldschmidt, Eurika Kaiser, Jonathan L. Dubois +2
Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives…
Deep reinforcement learning for optical systems: A case study of mode-locked lasers
Chang Sun, Eurika Kaiser, Steven L. Brunton +1
We demonstrate that deep reinforcement learning (deep RL) provides a highly effective strategy for the control and self-tuning of optical systems. Deep RL integrates the two leadin…