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Density-functional fluctuation theory of crowds

Cornell Affiliated Author(s)

Author

J.F. Méndez-Valderrama
Y.A. Kinkhabwala
J. Silver
Itai Cohen
Tomas Arias

Abstract

A primary goal of collective population behavior studies is to determine the rules governing crowd distributions in order to predict future behaviors in new environments. Current top-down modeling approaches describe, instead of predict, specific emergent behaviors, whereas bottom-up approaches must postulate, instead of directly determine, rules for individual behaviors. Here, we employ classical density functional theory (DFT) to quantify, directly from observations of local crowd density, the rules that predict mass behaviors under new circumstances. To demonstrate our theory-based, data-driven approach, we use a model crowd consisting of walking fruit flies and extract two functions that separately describe spatial and social preferences. The resulting theory accurately predicts experimental fly distributions in new environments and provides quantification of the crowd “mood”. Should this approach generalize beyond milling crowds, it may find powerful applications in fields ranging from spatial ecology and active matter to demography and economics. © 2018, The Author(s).

Date Published

Journal

Nature Communications

Volume

9

Issue

1

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052671619&doi=10.1038%2fs41467-018-05750-z&partnerID=40&md5=502cdbc26fb6c43fba6b2c780c7792c1

DOI

10.1038/s41467-018-05750-z

Group (Lab)

Itai Cohen Group
Tomas Arias Group

Funding Source

W911NF-16-1-0433
DGE-1650441
D71TW010433
Army-ARO W911NF-16-1-0433

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