Math behind everyday life: "black days", their manifestation as traffic jams, and beyond
Daniil Fedotov, Sergei Nechaev

TL;DR
This paper investigates the occurrence of 'black days' in daily life, analyzing their manifestation as traffic jams and other events through clustering and phase transition phenomena in high-dimensional event data.
Contribution
It introduces a novel analysis of event clustering using UMAP and explores phase transitions in high-dimensional point distributions, linking these to real-world phenomena like traffic congestion.
Findings
Clustering of event sequences indicates 'black days' similar to traffic jams.
Identifies a critical dimensionality where a phase transition occurs in point clustering.
Spectral analysis reveals Lifshitz tail behavior near the clustering transition.
Abstract
In our daily lives, we encounter numerous independent events, each occurring with varying probabilities over time. This letter delves into the scientific background behind the inhomogeneous distribution of these events over time, often resulting in what we refer to as ``black days'', where multiple events seem to converge at once. In the first part of the work we performed an analysis involving independent periodic and random sequences of events. Using the Uniform Manifold Approximation and Projection (UMAP) technique, we observed a clustering of event sequences on a two-dimensional manifold at a certain large . We interpret this clustering as a signature of ``black days'', which bears a clear resemblance to traffic jams in vehicle flow. In the second part of the work we examined in detail clustering patterns of independently distributed points within the corners…
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Taxonomy
TopicsMathematics Education and Teaching Techniques · History and Theory of Mathematics · Mathematical and Theoretical Analysis
