Recently we have been looking a lot into Poisson process and other related more physical topics. But the things we have been talking about also applies to our earlier more social science related works. This video by Mathemaniac discusses how the statistical methodology behind the Poisson process can be used to understand queues. As usual, we invite you to watch this fascinating video!

In the last post we have seen that 1/f noise can be obtained from superposition of Lorentzian power spectral densities. Though we have imposed an odd requirement of scaling pulse height for different characteristic rates \( \lambda \). In this post let us explore how to achieve the same thing with fixed height pulses.

Earlier we have taken a look at a power spectral density of a signal generated by a single charge carrier. We have seen that it generates a signal composed of pulses and gaps. If the pulse and gap duration is distributed according to the exponential distribution (i.e., Poisson process model applies), then the power spectral density of the signal has a characteristic Lorentzian shape. Which is nothing alike 1/f noise, which we are looking for. But maybe we can still obtain it?

We invite you to watch and think about the role of prediction in science. While the media and funding bodies tend to prefer when the research projects have practical applications (which often require making some new predictions), this is not how the most well-known theories were formulated. Many of the famous theories in Physics (and other sciences) were iterations of the earlier "clunkier" theories. This is discussed in the following video by the Last Theory YouTube channel.

Note that this channel is linked to Stephen Wolfram, who by some is regarded as a highly controversial figure in science. Although, he is the mastermind behind the Mathematica computer algebra system, which we like a lot (at least to help me with analytical derivations).

Over the last few years we have been keeping a steady pace of 33 posts a year. Though in 2023 we have managed to produce one more post containing an interactive app.

Fig 1.The number of posts written in English and still available on this iteration of Physics of Risk (as of the end of 2023). The wide bars represent total number of posts for each year since 2010, while the narrower bars represent a number of posts containing an interactive app.

This year we have mostly focused on the various properties of Poisson processes and related topics (such as point processes and shot noise). Otherwise we have finished a series of posts from the 2022 on the statistical modeling of dating apps.

There were also some major changes "under the hood". First of all we have moved from local server, which was managed by ourselves, to GitHub Pages. When making transition we have noticed couple of issues. Most immediate issues are already resolved. For example, some of the links were broken, or not using common practices in Pelican. Some of the less important issues, which can be easily fixed, were fixed. For example, we have renamed numerous article files in the source repository so that their names would match article slugs. What remains, is to fix some figure file names (also to match respective article slugs and the content of the figure). Also, as the number of interactive apps is growing every year, it seems worthwhile to reorganize their code in the source repository by putting them in "thematic" directories (for example, based on research topic or model type).

What is coming in 2024? Well, most likely we will have few more posts dedicated to our recent works on the random telegraph noise. Then I will likely tell you about my woes with football themed board game Eleven. While it is highly thematic, it has some glaring issues which I wanted to fix with science! Well, numerical simulation at least.