From statistical physics to social phenomena
| Quand ? |
Le 31/03/2025, de 11:00 à 12:00 |
|---|---|
| Où ? | Amphi L'Huillier |
| S'adresser à | Pablo Jensen |
| Participants |
Laetitia Gauvin |
| Ajouter un événement au calendrier |
vCal
iCal
|
The application of statistical physics beyond its traditional domain has grown considerably over the past decade. Concepts and tools from statistical physics have been increasingly used to model social phenomena, not merely by drawing analogies between individuals and interacting particles, but through deeper, more structural insights. In this talk, I will present a series of studies that explore social phenomena with varying degrees of connection to physics - some closely tied to it, others more distantly related.
I will begin with a paradigmatic example where statistical physics was applied outside its usual scope: the Schelling segregation model, which illustrates the concepts of emergence and phase transitions. I will also consider the model's applications and limitations in understanding housing market dynamics.
Next, I will discuss the importance of representation when studying human behavior, focusing on networks as a framework for capturing interactions. Network science, which has deep roots in statistical physics, provides powerful tools for extracting knowledge from network structures and linking them to spreading processes such as disease transmission. We will explore examples of this.
Beyond interactions, human mobility also plays a key role in disease spread and is widely used to predict infectious disease dynamics. Since both human interactions and mobility patterns shape disease dynamics, in the final part of the talk I will focus on how mobility connects to disease dynamics. To formalize this connection, I will introduce an information-theoretic approach that helps quantifying to which extent mobility metrics are predictive of infectious disease dynamics.