This thesis addresses deep questions that cut to the physical and informational essence of central chemical quantities such as transition paths and reaction mechanisms and proposes fundamental new connections between transition-path theory, linear-response theory, nonequilibrium thermodynamics, and information theory. The author investigates slow, energetically efficient driving protocols that drive a system between conformations corresponding to endpoints of a reaction, aiming to find connections between principles of efficient driving and the spontaneous transition mechanism in the absence of driving. First, an alternative perspective of transition-path theory is developed that unifies it with stochastic thermodynamics to describe flows of entropy, energy, and information during the reaction. This also provides an optimization criterion for selecting collective variables. Next, protocols are designed which invert the magnetization of a 3×3 Ising model with minimal energetic cost,and it is determined that using multiple control parameters allows the system to be driven along a fast-relaxing pathway between reaction endpoints. Finally, the author compares these protocols with the spontaneous transition mechanism for magnetization inversion in the same Ising model, finding that designed protocols capture general features of the spontaneous mechanism and energetics given the constraints on the control parameters. This work represents a major step forward in our understanding of rare events and provides a basis for investigating the connection between efficient protocols and spontaneous transition mechanisms which can be further probed in a wider variety of systems.

Auteur

Dr. Miranda Louwerse obtained a Bachelor of Science in Chemistry and Mathematics from the University of the Fraser Valley in 2017 before beginning a PhD in Chemistry at Simon Fraser University. She joined Dr. David Sivak's research group in the physics department and carried out interdisciplinary research at the intersection of chemistry, physics, biology, and statistics. Upon completing her PhD in 2022, Miranda found employment as a data scientist in the biotech industry. Miranda has been married to her husband Mitch since 2018 and spends her time fishing with him and her two-year old border collie Roscoe.