Presentation #117.32 in the session Time-Domain Astrophysics.
Accreting compact object systems exhibit variability in their luminosity on many timescales ranging from milliseconds to hundreds of days. Current studies seek to connect the ubiquitously complex variability of accreting systems to their accretion properties and environment, probing commonalities across decades of mass. Recent studies using the recurrence analysis method from nonlinear dynamics have uncovered relationships between the classes of AGN and the spectral states of XRBs and their temporal variability, categorized as stochastic, deterministic, or chaotic. Recurrence analysis shows promise in critically probing distinct classes of variability among systems with different accretion flows. However, these studies have all been applied to the light curves of XRBs and AGN that are evenly sampled in the X-ray bandpasses. In this work, we extend the application of recurrence analysis to light curves with irregular cadence typical of ground-based optical observatories, such as the Zwicky Transient Facility. We generate recurrence plots of synthetic light curves of dynamical systems as well as real systems and use machine learning methodologies to determine the impact of seasonal gaps and irregular cadence on classifications of variability. We find the recurrence plot is an effective tool for classifying the temporal variability features of accreting and dynamical systems alike for both all-sky monitors and ground-based time domain observatories.