Using Symmetry to Enhance the Performance of Agent-Based Epidemic Models

Symmetries express the invariance of a system towards sets of mathematical transformations. In more practical terms, symmetries greatly reduce or simplify the computational efforts required to evaluate relevant properties of a system. In this paper, two methods are proposed to implement spin symmetries which simplify the analysis of the spreading of diseases in an agent-based epidemic model. We perform a set of simulations to measure the efficiency gains compared to traditional methods. Our findings show symmetry-based algorithms improve the performance of the Monte Carlo simulation and the exact Markov process.

Automated summary

Symmetries greatly reduce computational efforts in evaluating system properties. This paper proposes two methods to simplify the analysis of disease spreading in an agent-based epidemic model using spin symmetries, and the efficiency gains are measured through simulations.