Posts

In the previous post about limit theorems of stochastic processes, we considered when everything goes right, leading to Gaussian-like behavior. Here we’ll discuss when things go wrong, particularly when memory effects and infinite moments are introduced.

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A few months ago, Frank Stenger uploaded a preprint of a proposed proof of the Riemann hypothesis. Unlike the plethora of other attempts at famous problems, nobody seems to be talking about this. Why?

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One way to understand the structure of randomness is to experience a lot of it. We’ll use $\lim_{n\to\infty} X_1 + \cdots + X_n$ as a case study, and along the way bump into classical ideas like the Central Limit Theorem (CLT) and Brownian motion.

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The debut post on this blog, mostly consisting of rambling about its creation: both why and how.

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