We show that the naive mean-field approximation correctly predicts leading term of logarithmic lower tail probabilities for number copies a given subgraph in G(n,p) and arithmetic progressions length random subsets integers entire range densities where is viable. Our main technical result provides sufficient conditions on maximum degrees uniform hypergraph H guarantee edges, induced by binomial...

Given any half-sided modular inclusion of standard subspaces, we show that the entropy function associated with decreasing one-parameter family translated subspaces is convex for given (not necessarily smooth) vector in underlying Hilbert space. In second quantisation, this infers convexity vacuum relative respect to translation parameter tunnel von Neumann algebras. This result allows us study...

We show that the derivative of the relative entropy with respect to its parameters is lower and upper bounded. We characterize the conditions under which this derivative can reach zero. We use these results to explain when the minimum relative entropy and the maximum log likelihood approaches can be valid. We show that these approaches naturally activate in the presence of large data sets and t...

My greatest concern was what to call it. I thought of calling it “information”, but the word was overly used, so I decided to call it “uncertainty”. When I discussed it with John von Neumann, he had a better idea. Von Neumann told me, “You should call it entropy, for two reasons. In the first place your uncertainty function has been used in statistical mechanics under that name, so it already h...