A vector field splitting approach is discussed for the systematic derivation of numerical propagators for deterministic dynamics. Based on the formalism, a class of numerical integrators for Langevin dynamics are presented for single and multiple time step algorithms.

Generalized Langevin Equation (GLE) thermostats have been used very effectively as a tool to manipulate and optimize the sampling of thermodynamic ensembles and the associated static properties. Here we show that a similar, exquisite level of control can be achieved for the dynamical properties computed from thermostatted trajectories. We develop quantitative measures of the disturbance induced...

We study the connection between Hamiltonian dynamics and irreversible, stochastic equations, such as the Langevin equation. We consider a simple model of a classical harmonic oscillator (Brownian particle) coupled to a field (heat bath). In traditional approaches Langevin-type equations have been derived from Hamiltonian dynamics, but these equations contain memory terms and are both time-rever...

We study the statistically invariant structures of nonlinear generalized Langevin equation (GLE) with a power-law memory kernel. For broad class kernels, including those in subdiffusive regime, we construct solutions GLE using Gibbsian framework, which does not rely on existing Markovian approximations. Moreover, provide conditions decay to ensure uniqueness steady states, generalizing previous...

Solving the optimal symbol detection problem in multiple-input multiple-output (MIMO) systems is known to be NP-hard. Hence, objective of any detector practical relevance get reasonably close solution while keeping computational complexity check. In this work, we propose a MIMO based on an annealed version Langevin (stochastic) dynamics. More precisely, define stochastic dynamical process whose...