At the turn of the year, we finalised a new manuscript with the title “Measurement-Induced Phase Transition in State Estimation of Chaotic Systems and the Directed Polymer”. I think this is a nice work worth checking/reading for a couple of reasons. First, it has a rather fundamental interpretation of a phase transition in the ability of controlling chaos: think about a system with a Lyapunov exponent that some observer tries to study. It is clear that the best the observer can do is associated some statistical description within a certain expanding region in the accessible phase space. However, suppose now that the observer has some indirect access to the system itself, so they perform measuremenst to improve their knowledge about the current state of the system. It is clear that there is a competition between the chaos induced growth of uncertainty and the mitigation from the measurements. Also, due to the exponential growth induced by a Lyapunov exponent, it is natural to model this setup with an tree-like expander graph. Thus, the description we employed is one of a particle performing directed random walk on a tree. After some technical manipulation, it turns out that the problem of estimating the effective uncertainty for the observer estimates is mappable onto the well-known directed polymer on the Cayley tree. However, in contrast with the standard studies in this framework, which deals with the evaluation of the free energy ~ log Z, here we have to deal with the uncommon quantity Z log Z. This forces us to look at rare events in the directed polymer which dominate the statistics. Nonetheless, we identify a phase transition, which sits exactly at the same point as the usual freezing one! This was not expected a-priori, and indeed the critical points are very different features.