Interactive Models

A selection of models studied by our group was implemented in Javascript to make them accessible for everyone to study. You can explore those directly on this website.

MARKET MODEL

A model of financial markets based on the Ising Model.

The agents are given two possibilities: To buy or to sell a given stock. Each agent is influenced by the price as well as its nearest neighbors. The conflicting character of a minority game combined with a ferromagnetic Ising model causes frustration across scales and emerges expectation bubbles and volatility clustering known from real markets.

S. Bornholdt, Expectation bubbles in a spin model of markets: Intermittency from frustration across scales, doi:10.1142/S0129183101001845

SCIENTIFIC PARADIGMS MODEL

A model of scientific paradigms

Scientists suggest ideas to each other and accept those new ideas with a probability proportional to their popularity. Once a scientists has scrapped an idea he cannot reconsider it. An innovation rate controls how often scientists come up with new ideas.

S. Bornholdt, M. H. Jensen and K. Sneppen, Emergence and Decline of Scientific Paradigms, doi:10.1103/PhysRevLett.106.058701

MULTIPLE EPIDEMICS MODEL

A model of multiple epidemics

This is a minimal model of how epidemic spreading interacts with immunity of individual hosts: Every agent only gets infected once by each disease. Older diseases thus face a harder time while new diseases sweep over the system.

K. Sneppen, A. Trusina, M.H. Jensen, and S. Bornholdt, A Minimal Model for Multiple Epidemics and Immunity Spreading, PLoS ONE 5 (2010) e13326

SELF-ORGANIZED CRITICAL NEURAL NETWORK

A model for how the brain may keep itself between silence and chaos

This is a simple neural network model which exhibits self-organized criticality (SOC). Based on local rules only, the network evolves towards criticality, showing typical scale-free avalanches matching those recently observed in the brain.

S. Bornholdt and T. Rohlf, Topological evolution of dynamical networks: Global criticality from local dynamics, Phys. Rev. Lett. 84 (2000) 6114-6117.
S. Landmann and S. Bornholdt, Self-organized criticality in a binary neural network model with local rules, Verhandl. DPG (VI) 52 (2017).

DISCRIMINATION

Social evolution of structural discrimination

We ask: “Could a social hierarchy emerge and persist between two groups distinguished by easily observable characteristics, even if they are identical in terms of intrinsic properties?”

G. Gruner, S. Bornholdt, Social evolution of structural discrimination, arXiv/1703.06311

In contrast to the implementations listed above the following programs make use of the full features of the SpiMoSim library. These implementation are meant for advanced users and those who are familiar with Javascript and might want to use SpiMoSim for their projects.

MARKET MODEL (advanced version)

A model of financial markets based on the Ising Model.

This implementation features more plots, higher dimensional lattices, CSV export, downloads of animated GIFs, upload of initial states, export of the current state (JSON format) and more.

S. Bornholdt, Expectation bubbles in a spin model of markets: Intermittency from frustration across scales, doi:10.1142/S0129183101001845

Models powered by SpiMoSim – A modular javascript library for interactive physical models by Pascal Grafe. Find out more!