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A common goal in the sciences is optimization of an objective function byselecting control variables such that a desired outcome is achieved. Thisscenario can be expressed in terms of a control landscape of an objectiveconsidered as a function of the control variables. At the most basic level, itis known that the vast majority of quantum control landscapes possess no traps,whose presence would hinder reaching the objective. This paper reviews andextends the quantum control landscape assessment, presenting evidence that thesame highly favorable landscape features exist in many other domains ofscience. The implications of this broader evidence are discussed. Specifically,control landscape examples from quantum mechanics, chemistry, and evolutionarybiology are presented. Despite the obvious differences, commonalities betweenthese areas are highlighted within a unified mathematical framework. Thismathematical framework is driven by the wide ranging experimental evidence onthe ease of finding optimal controls (in terms of the required algorithmicsearch effort beyond laboratory set up overhead). The full scope andimplications of this observed common control behavior pose an open question forassessment in further work.

philosophical transactions - royal society. mathematical, physical and engineering sciences/philosophical transactions - royal society. mathematical, physical and engineering sciences

Common Foundations of Optimal Control Across the Sciences: evidence of a free lunch