Optimality of nonconservative driving for finite-time processes with discrete states
Benedikt Remlein, Udo Seifert
Abstract
An optimal finite-time process drives a given initial distribution to a given final one in a given time at the lowest cost as quantified by total entropy production. We prove that for a system with discrete states this optimal process involves nonconservative driving, i.e., a genuine driving affinity, in contrast to the case of a system with continuous states. In a multicyclic network, the optimal driving affinity is bounded by the number of states within each cycle. If the driving affects forward and backwards rates nonsymmetrically, the bound additionally depends on a structural parameter characterizing this asymmetry.
Topics & Concepts
Bounded functionDiscrete time and continuous timeEntropy (arrow of time)Process (computing)AsymmetryMathematicsPrinciple of maximum entropyFinite setEntropy productionControl theory (sociology)Statistical physicsApplied mathematicsMathematical optimizationComputer sciencePhysicsMathematical analysisStatisticsThermodynamicsArtificial intelligenceOperating systemControl (management)Quantum mechanicsAdvanced Thermodynamics and Statistical MechanicsNeural dynamics and brain functionstochastic dynamics and bifurcation