P-sync: Disillusioned with a chance of compassion, isolated with a chance of immunity: Forecasting Order in Chaotic Worlds
- Complex systems are useful for modeling much of the dynamic world, balancing chaos and synchrony.
- Such systems can be difficult to model using a simulated recreation, as a defining characteristic of such systems is the sensitivity to initial conditions.
- Reservoir computing has recently shown promise for rapidly forecasting the states of a chaotic complex system, without recreating the system itself.
- Our goal is to explore the potential of the technique for modeling diverse data, both from controlled, experimental simulations and from messy, complex systems in the world that connect people, ideas, and power.
- By developing a specialized tool for predicting the states of dynamic complex systems, we hope to take away lessons about the dynamic, chaotic nature of our worlds, and to contribute to a modern technological arsenal of instruments for taking the pulse of human activity, from predicting surges in the spread of viral misinformation and infectious diseases, to societal healing and moral unity.
Jacob Zimmerman (Pomona College ’23)
Hannah Lu (Harvey Mudd College ’24)
Ryan Ong (UC Berkeley ’22)
Hannah Mandell (Pomona ’23)
Shaun KewalRamani (Pomona ’24)