ritvikmath has already explained to us what the Beta distribution is. There is another video by ritvikmath, which explains multidimensional generalization of it. This generalization is known as Dirichlet distribution. Watch it for the data science perspective.

I myself understand Dirichlet distribution from the perspective of noisy voter model (or Kirman's model. Although I haven't explicitly mentioned it earlier, Dirichlet distribution arises from the multistate generalization of the voter model.

Another summer has gone by. This year my main summer activity was supervising summer internship project. The intern was rather capable, so the project itself was not very eventful and comparably effortless on my part. Also the final conclusion on the research hypothesis was negative (i.e., state interaction network doesn't seem to have any effect on stationary distribution), so there wasn't much to analyze.

From a technical side, once again, my institution's IT admins have irritated my a bit. In mid-June I have received a notification about outdated software on a server I supervise (which is not related to Physics of Risk in any way). I promptly connected to the server to immediately apply the update (as I was warned about severe security risks of not updating), just to find that no update is available for the Linux server. After quick search I have found that a newer version of the software in question is in fact directly available from its developers, but hasn't yet landed in the official repositories. It is not a good idea to update from outside the official repositories, so I felt somewhat annoyed due to being prodded and lectured for no real reason.

Summer experiences aside, what is coming for Physics of Risk? At the time of writing I do not know. I do have material for a rant about my summer experiences with open access publishing, but really not much else. I expect that the first-party content might become much rarer in the foreseeable future.

Summer is already here! Go grab a ball and play! Just make sure that your ball is correct.

Have you ever wondered how Fermi-Dirac statistics arises? I already have in the previous couple of posts, but the more important question is why I suddenly started to care about Fermi-Dirac statistics. It is still all related to [1]. Reviewers raised doubts about our assumption about uniform detrapping rates, asking us to provide experimental evidence for our claim. As far as I am able to read the experimental works, it doesn't seem possible to provide any direct evidence. Still as a theoretician I can provide theoretical justification which is indirectly supported by experimental works.

This is why in this post we'll talk about detrapping rates arising from a simple model explored in an earlier post.

Summer is almost here! Are you looking for a cool computer science project to do in a free time? Why not implement Conway's Game of Life? Using it you can even build your own simulation of a computer inside your physical computer! See the video below by Alan Zucconi.