Concentration of Measure Phenomenon

The concentration of measure phenomenon is a concept in mathematics and probability that describes how, in high-dimensional spaces, most of the data points tend to be very close to a central value or surface. As the dimensionality increases, the distribution "concentrates" around a specific region, making deviations from this typical region increasingly unlikely. In practical terms, it means that for complex, high-dimensional systems—like large networks or datasets—most properties are predictable and tightly clustered, despite the seemingly vast possible variations.