arXiv subjects

Julia Sanders

Publications and source records attributed to Julia Sanders.

5 recordsLinked to original sources

arXiv2026

What is a minimum work transition in stochastic thermodynamics?

We reassess the concept of transition at minimum work in classical stochastic finite-time thermodynamics, when the system dynamics is modelled by a diffusion process. We show that a well-posed formulation of the optimal control problem corresponding to the minimization of the mean work done on the system during a finite-time transition necessarily requires taking into account speed limits on control protocols. This fact has major qualitative consequences. First, it permits to discriminate between optimal swift engineered equilibration and transitions at minimum work. Second, it shows that in the limit when speed limits are removed, only transitions specified by generalized Schr\"odinger bridges admit a consistent physical interpretation. To illustrate these points, we focus on the simplest model problem: a levitating particle in a Gaussian moving trap.

cond-mat.stat-mech↗

arXiv2025

Optimal Control of Engineered Swift Equilibration of Nanomechanical Oscillators

We propose a reformulation of the problem of optimally controlled transitions in stochastic thermodynamics. We impose that any terminal cost specified by a thermodynamic functional should depend only on state variables and not on control protocols, according to the canonical Bolza form. In this way, we can unambiguously discriminate between transitions at minimum dissipation between genuine equilibrium states, and transitions at minimum work driving a system from a genuine equilibrium to a non-equilibrium state. For underdamped dynamics subject to a mechanical force, genuine equilibrium means a Maxwell-Boltzmann probability distribution defining a vanishing current velocity. Transitions at minimum dissipation between equilibria are a model of optimal swift engineered equilibration. Remarkably, we show that transitions at minimum work do not directly imply explicit boundary conditions on terminal values of parameters of the mechanical force and on control protocols. Thus, the problem often discussed in the literature, that optimal protocols need terminal jumps to satisfy boundary conditions, completely disappears. The quantitative properties of optimal controls are entirely determined by the form of the penalty modelling an experimental setup. More generally, we use centre manifold theory to analytically account for the tendency of optimal controls to exhibit a turnpike property: optimal protocols in the bulk of the control horizon tend to converge to a universal centre manifold determined only by the running cost. Exponential deviations from the centre manifold occur at the ends of the control horizon in order to satisfy the boundary conditions. Our findings are supported numerically.

cond-mat.stat-mech↗

arXiv2024

On the numerical integration of the Fokker-Planck equation driven by a mechanical force and the Bismut-Elworthy-Li formula

Optimal control theory aims to find an optimal protocol to steer a system between assigned boundary conditions while minimizing a given cost functional in finite time. Equations arising from these types of problems are often non-linear and difficult to solve numerically. In this note, we describe numerical methods of integration for two partial differential equations that commonly arise in optimal control theory: the Fokker-Planck equation driven by a mechanical potential for which we use Girsanov theorem; and the Hamilton-Jacobi-Bellman, or dynamic programming, equation for which we find the gradient of its solution using the Bismut-Elworthy-Li formula. The computation of the gradient is necessary to specify the optimal protocol. Finally, we give an example application of the numerical techniques to solving an optimal control problem without spacial discretization using machine learning.

math.OC↗

arXiv2024

Minimal work protocols for inertial particles in non-harmonic traps

Progress in miniaturized technology allows us to control physical systems at nanoscale with remarkable precision. Experimental advancements have sparked interest in control problems in stochastic thermodynamics, typically concerning a time-dependent potential applied to a nanoparticle to reach a target stationary state in a given time with minimal energy cost. We study this problem for a particle subject to thermal fluctuations in a regime that takes into account the effects of inertia, and, building on the results of a previous work, provide a numerical method to find optimal controls even for non-Gaussian initial and final conditions, corresponding to non-harmonic confinements. The control protocol and the time-dependent position distribution are qualitatively different from the corresponding overdamped limit: in particular, a symmetry of the boundary conditions, which is preserved in the absence of inertia, turns out to be broken in the underdamped regime. We also show that the momentum mean tends to a constant value along the trajectory, except close to the boundary, while the evolution of the position mean and of the second moments is highly non-trivial. Our results also support that the lower bound on the optimal entropy production computed from the overdamped case is tight in the adiabatic limit.

cond-mat.stat-mech↗

arXiv2024

Optimal Control of Underdamped Systems: An Analytic Approach

Optimal control theory deals with finding protocols to steer a system between assigned initial and final states, such that a trajectory-dependent cost function is minimized. The application of optimal control to stochastic systems is an open and challenging research frontier, with a spectrum of applications ranging from stochastic thermodynamics to biophysics and data science. Among these, the design of nanoscale electronic components motivates the study of underdamped dynamics. In this work, we develop analytic techniques to determine protocols steering finite time transitions at a minimum thermodynamic cost for stochastic underdamped dynamics. As cost functions, we consider two paradigmatic thermodynamic indicators. The first is the Kullback-Leibler divergence between the probability measure of the controlled process and that of a reference process. The corresponding optimization problem is the underdamped version of the Schr\"odinger diffusion problem that has been widely studied in the overdamped regime. The second is the mean entropy production during the transition, corresponding to the second law of modern stochastic thermodynamics. For transitions between Gaussian states, we show that optimal protocols satisfy a Lyapunov equation, a central tool in stability analysis of dynamical systems. For transitions between states described by general Maxwell-Boltzmann distributions, we introduce an infinite-dimensional version of the Poincar\'e-Linstedt multiscale perturbation theory around the overdamped limit. This technique fundamentally improves the standard multiscale expansion. Indeed, it enables the explicit computation of momentum cumulants, whose variation in time is a distinctive trait of underdamped dynamics and is directly accessible to experimental observation.

cond-mat.stat-mech↗