This thesis describes the development of practical and efficient computational approaches to the quantum dynamics of complex systems. Most of the work presented here relies on the generalized quantum master equation (GQME) formalism, which provides a simple equation of motion of reduced dimensionality for a set of dynamical quantities, e.g., nonequilibrium averages and equilibrium time correlation functions. The reduced dimensionality of the GQME comes at a cost: the introduction of the memory kernel, which accounts for the influence of all ``excluded'' degrees of freedom. Focusing first on the second-order perturbative treatment of the memory kernel known as Redfield theory, I present a collaborative effort to extend its applicability into highly non-Markovian regions via a mode freezing approach. In this method, a portion of bath modes characterized by low frequencies are treated as sources of static disorder and used to calculate modified Redfield dynamics. Application of the method to the spin-boson and FMO complex models indicates that the Redfield+frozen modes scheme consistently produces dynamics that are as good or better than bare Redfield dynamics. Next, we explore GQME approach coupled to the self-consistent solution of the memory kernel, which requires the calculation of auxiliary kernels. Previous implementations of the method had shown impressive boosts in efficiency and, when approximate methods were used to calculate the auxiliary kernels, accuracy over direct calculation of nonequilibrium averages. We show that this method, when formulated from the Mori perspective, is equally applicable to nonequilibrium averages and equilibrium correlation functions. In addition, we examine the dependence of the improvements afforded by the GQME framework on the choice projection operator and kernel closure. In particular, we demonstrate that improvements in efficiency, which rely on short memory lifetimes, are sensitively dependent on the choice of projection operator, and that the choice of kernel closure directly dictates the improvements in accuracy. In addition, we present evidence that indicates that the success of the GQME formalism when the auxiliary kernels are calculated via semi- and quasi-classical methods is largely due to the exact sampling of bath operators at t = 0 required by the calculation of specific kernel closures. Next, we provide analytical arguments that delineate when the GQME framework coupled to the self-consistent solution of the memory kernel is likely to provide improvements in efficiency and accuracy. Finally, we present a path integral framework that can efficiently render the partially Wigner-transformed canonical density operator for systems coupled linearly to harmonic baths. This approach permits the direct calculation of any thermodynamic quantity and can be integrated into dynamical schemes like the Ehrenfest, surface hopping, or linearized semi-classical initial value representation methods to calculate equilibrium correlation functions.
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