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...

In this paper, we develop a multiscale approach to model intrinsic dissipation under high frequency of vibrations in solids. For vibrations with a timescale comparable to the phonon relaxation time, the local phonon distribution deviates from the equilibrium distribution. We extend the quasiharmonic (QHM) method to describe the dynamics under such a condition. The local deviation from the equil...

We develop an efficient sampling method by simulating Langevin dynamics with an artificial force rather than a natural force by using the gradient of the potential energy. The standard technique for sampling following the predetermined distribution such as the GibbsBoltzmann one is performed under the detailed balance condition. In the present study, we propose a modified Langevin dynamics viol...