Computational Mathematics STIR: Density Functional Theory as a New Mathematical Framework for Predicting Population Flows
Abstract
The objective of this STIR project, Density Functional Theory (DFT) as a New Mathematical Framework for Predicting Population Flows, is to investigate one of the more successful methods from physics, DFT, as a means of synthesizing behavior of a large number of entities in a social system. The proposed approach involves investigating the applicability of a proven method from quantum statistical mechanics, DFT, in the context of behaviors of large social populations Three main investigations will be made of group dynamics in agent-based models and in fruit fly populations: 1 - Stochastic equilibrium predictions of agent distributions in arbitrary enclosures 2- Adiabatic evolution testing of conflict between subpopulations 3- Time evolution testing of population flight into new space
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 27, 2017
- Source ID
- W911NF1610433
Entities
People
- Tomás Arias
Organizations
- Army Contracting Command
- Cornell University
- United States Army