Cosmic inflation, in conjunction with the vast energy landscape of string theory, offers compelling evidence that we are part of a multiverse. As an inhabitant of the multiverse, how should we reason probabilistically about the expected properties of our universe? Defining probabilities in cosmic inflation is a major open problem in the field. Our collaborative initiative proposes a fresh tack on the problem, by bringing in new ideas and expertise from an unlikely place: the study of biological energy landscapes and flow networks.
Our effort builds on recent progress in eternal inflation, which predicts that we exist early on in the unfolding of the multiverse and, therefore, likely inhabit states of the landscape that are easily accessed dynamically. A striking result makes a cross-disciplinary collaboration particularly timely: accessible states reside in regions of the landscape whose topography is that of a deep funnel, akin to the folding funnels of proteins.
Like many biological energy landscapes, the landscape of string theory can be represented mathematically as a network. A first objective of our proposed effort is to apply search optimization principles to optimize various observables of transition network dynamics, such as first-passage times. This will allow us to decode how dynamics of the network reflect the topography of the underlying energy landscape.
A central motivation is the puzzling evidence that our universe is on the verge of a phase transition. A key objective is to shed new light on this question by capitalizing on another unexpected connection with flow networks: optimal networks of the string landscape are poised near the percolation phase transition. The power of criticality lies in universality: near continuous phase transitions, various observables assume power-law probability distributions, independent of the microscopic details. Our goal is to derive such universal predictions, most importantly for the vacuum energy.