SPECIAL SEMINAR: Search optimization, Natural Selection and Self-Organized Criticality on the Landscape

The most pressing fine-tuning puzzles of the Standard Model — the cosmological constant and weak hierarchy problems, as well as the Higgs metastability —  can all be understood as problems of near criticality. I will present a natural selection mechanism based on search optimization on the string landscape. The working assumption is that cosmological evolution on the multiverse has occurred for a finite time, much shorter than the exponentially-long global mixing time for the landscape. I will argue this imposes a strong selection pressure among hospitable vacua, favoring those that lie in optimal regions where the search algorithm is efficient. This satisfies the basic requirements for natural selection: a diverse gene pool, offered ab initio by the landscape; vacuum replication through cosmological expansion; and competition for a finite resource, namely the fraction of comoving volume. Optimality is defined by two competing requirements: search efficiency, which requires minimizing the mean-first passage time, and sweeping exploration, which requires recurrent random walks. Optimal landscape regions reach a compromise by lying at the critical boundary between recurrence and transience, thereby realizing the idea of self-organized criticality. The framework makes concrete phenomenological predictions: 1. The expected lifetime of our universe is ~10^{130} years, consistent with current Standard Model metastability estimates; 2. The SUSY breaking scale should be high. Importantly, these predictions do not rely on anthropic reasoning and instead follow readily from optimality.