leads to quick alterations of sign $\dot\alpha(t)\gtrless0$ with a nearly constant value of $\alpha(t)$, like in [Fig. \[fig:trj\]]{}(a) around $0.35<t<0.45$ r.u. or in [Fig. \[fig:trj\]]{}(b) $0.50 < t < 0.55$. In contrast, the trajectory of our MD simulation appears more resistant to changes of its direction, $\dot\alpha(t)$, and thus slightly smoother.

The alterations of $\dot\alpha(t)$, mentioned above, might be an artifact of the white noise approximation. In principle, a colored noise, which introduces additional correlations into the stochastic forces on the right-hand side of [Eq. (\[eq:lgv2\])]{}, e.g. [@Queiros2016], could make the dynamics of $\dot\alpha(t)$ more inertial. Possibly this would make the trajectory of $\alpha(t)$ smoother, by reducing the chance of quick sign alterations in its time derivative.

\[sec:final\]Conclusion
=======================

In this paper we have demonstrated, how efficiently the Langevin dynamics can represent certain nonequilibrium systems in a steady state. Section \[sec:mic\] describes a way to find the parameters of such representation from the statistics of the original system. The numerical simulations of [Eq. (\[eq:lgv2\])]{}, thus obtained, and the integration algorithm, proposed in Appendix \[sec:alg\], yield results, which are both, statistically and qualitatively, very accurate and precise; cf. [Sec. \[sec:mes\]]{}.

Two models of athermal noise for [Eq. (\[eq:lgv2\])]{}, i.e. simple white 