most citedRobust computation of higher-dimensional invariant tori from individual trajectories

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP2025

Unscented and Higher-Order Linear Covariance Fidelity Checks and Measures of Non-Gaussianity

Jackson Kulik, Braden Hastings, Keith A. LeGrand

Linear covariance (LinCov) techniques have gained widespread traction in the modeling of uncertainty, including in the preliminary study of spacecraft navigation performance. While…

eess.SY2025

Optimal Rank-1 Directional State Transition Tensors

Grace E. Calkins, Jay W. McMahon, Jackson Kulik

An optimal rank-1 approximation of state transition tensors was developed as an efficient alternative to state transition tensors for nonlinear uncertainty quantification. While pr…

eess.SP2025

Higher-Order Tensor-Based Deferral of Gaussian Splitting for Orbit Uncertainty Propagation

G. Andrew Siciliano, Keith A. LeGrand, Jackson Kulik

Accurate propagation of orbital uncertainty is essential for a range of applications within space domain awareness. Adaptive Gaussian mixture-based approaches offer tractable nonli…

math.DS20251 cited

Robust computation of higher-dimensional invariant tori from individual trajectories

Maximilian Ruth, Jackson Kulik, Joshua Burby

We present a method for computing invariant tori of dimension greater than one. The method uses a single short trajectory of a dynamical system without any continuation or initial…

stat.ML2024

Nonlinearity and Uncertainty Informed Moment-Matching Gaussian Mixture Splitting

Jackson Kulik, Keith A. LeGrand

Many problems in navigation and tracking require increasingly accurate characterizations of the evolution of uncertainty in nonlinear systems. Nonlinear uncertainty propagation app…