Natural selection is commonly assumed to become more effective as it becomes stronger. However, selection acts on phenotypes rather than directly on genotypes, and phenotypic success is inherently noisy. Here we study how this mismatch shapes long-term evolutionary dynamics. Using a minimal stochastic model in which individuals inherit genetic fitness while selection acts on noisy phenotypic expressions, we show that increasing selection strength accelerates adaptation only up to a critical threshold. Beyond this point, stronger selection paradoxically slows evolution and erodes genetic diversity by favouring the luckiest individuals rather than the genetically fittest.

We identify two distinct evolutionary regimes—selection of the fittest and selection of the luckiest—separated by a sharp transition. This transition corresponds to a previously un-recognized change in the structure of traveling fitness waves, from semi-pulled to fully pulled fronts, with consequences for adaptation speed and genealogical structure. Our results reveal a biological instance of Goodhart’s law: when phenotypic measures become overly optimized targets, they cease to reliably promote genetic improvement.

Por anunciar

Por anunciar

Por anunciar

An asymmetric random variable $X$ is said to be symmetrization resistant if every independent random variable $Y$ that produces a symmetric sum $X+Y$ has a greater variance than that of $X$. Asymmetric Bernoulli random variables were shown to be symmetrization resistant by Kagan, Mallows, Shepp, Vanderbei, and Vardi (1999); Pal (2008) gave a proof using stochastic calculus. Proving symmetrization resistance appears to be difficult: little is known about other asymmetric distributions. We introduce the notion of entropic symmetrization resistance, which is the same as symmetrization resistance except that the entropy (rather than variance) of $Y$ must exceed that of $X$. We show that Bernoulli random variables exhibit entropic symmetrization resistance exactly when they exhibit symmetrization resistance. We also extend the underlying entropy and variance inequalities to the hypercube. Finally, we explore the possibility of extensions to non-Bernoulli random variables. This talk is based on joint work with Mokshay Madiman (University of Delaware).

Activated random walk (ARW) is an ‘abelian’ particle system that conjecturally exhibits the complex behaviors associated with self-organized criticality (SOC), a phenomenon that was first described heuristically by physicists in the 1990s. I will discuss recent results for ARW on Z which rigorously establish some of the predictions of SOC, including universality of the phase transition, and properties of the critical state.