Benjamin Kuznets-Speck

TL;DR: In this paper, the authors use counter-diabatic driving to control the behaviour of quantum states for applications like quantum computing and manipulating ultracold atoms, and show how a set of external control parameters (that is, varying drug concentrations and types, temperature and nutrients) can guide the probability distribution of genotypes in a population along a specified path and time interval.

TL;DR: The authors propose to use quantum methods to control the speed and distribution of potential evolutionary outcomes, using counterdiabatic driving toControl the behaviour of quantum states for applications like quantum computing and manipulating ultracold atoms.

TL;DR: Stochastic thermodynamics is employed to build a framework which can be used to gain mechanistic insight into transitions far from equilibrium, and shows that under general conditions, there is a basic speed limit relating the typical excess heat dissipated throughout a transition and the rate amplification achievable.

TL;DR: This work shows how a set of external control parameters can guide the probability distribution of genotypes in a population along a specified path and time interval, allowing empirical optimization of evolutionary speed and trajectories.

TL;DR: In this article, the authors acknowledge support from the U.S. National Science Foundation (NSF) under Grant No. MCB-1651650 and the Labex CelTisPhyBioBioNitrome(ANR-11-LABX-0038, ANR-10-IDEX-0001-02).