Fully self-consistent models have driven major advances in plasma simulation, supported by a rapid growth in computational performance. However, their high computational and energy costs highlight the need for accurate, reduced models. One promising approach is parameter-drift modeling, in which selected parameters evolve according to prescribed time laws rather than being coupled self-consistently to all other model variables. In this tutorial, we introduce key concepts in parameter-drift dynamical models and explore their applications in plasma physics. Using a familiar test-particle guiding-center model, we present the main analysis tools of the parameter-drift literature, namely, the ensemble approach, and discuss their advantages and limitations in Hamiltonian systems. Furthermore, we describe the dynamics of the model with traditional tools from dynamical systems theory, e.g., the Lyapunov exponent. In summary, we highlight the potential of parameter-drift models as reduced but insightful representations of time-dependent plasma dynamics. Although they cannot replace large-scale simulations with full bidirectional coupling between particles and fields, parameter-drift dynamical models offer an efficient framework for developing and testing fundamental aspects of time-dependent scenarios using reduced models.
Grime et al. (Thu,) studied this question.