Equivalent dynamical complexity in a many-body quantum and collective human system

TL;DR

This paper demonstrates that a single complexity model based on cluster coalescence and fragmentation can unify understanding of phenomena across quantum physics and social systems, revealing underlying dynamical similarities.

Contribution

It introduces a unified complexity model that explains diverse phenomena from quantum effects to social insurgencies, bridging a gap in complexity science.

Findings

Explains quantum many-body effects in cuprate superconductors.

Accounts for universal casualty distributions in insurgencies.

Aligns with empirical facts in markets, neurons, and gangs.

Abstract

Proponents of Complexity Science believe that the huge variety of emergent phenomena observed throughout nature, are generated by relatively few microscopic mechanisms. Skeptics however point to the lack of concrete examples in which a single mechanistic model manages to capture relevant macroscopic and microscopic properties for two or more distinct systems operating across radically different length and time scales. Here we show how a single complexity model built around cluster coalescence and fragmentation, can cross the fundamental divide between many-body quantum physics and social science. It simultaneously (i) explains a mysterious recent finding of Fratini et al. concerning quantum many-body effects in cuprate superconductors (i.e. scale of 10^{-9} - 10^{-4} meters and 10^{-12} - 10^{-6} seconds), (ii) explains the apparent universality of the casualty distributions in distinct human insurgencies and terrorism (i.e. scale of 10^3 - 10^6 meters and 10^4 - 10^8 seconds), (iii) shows consistency with various established empirical facts for financial markets, neurons and human gangs and (iv) makes microscopic sense for each application. Our findings also suggest that a potentially productive shift can be made in Complexity research toward the identification of equivalent many-body dynamics in both classical and quantum regimes.