Speaker
Description
We investigate the probability distribution of the order parameter in the O(N) model, with a focus on its behavior near criticality. Characterizing the full distribution provides direct insight into fluctuations and universal features of the system.
On the analytical side, we employ the Functional Renormalization Group (FRG), which enables a non-perturbative treatment of critical fluctuations and allows access to the scale dependence of the effective action. This approach yields predictions for the shape and scaling behavior of the order parameter distribution across different regimes.
Complementing the analytical study, we perform numerical simulations using the Wolff cluster algorithm, which efficiently reduces critical slowing down in O(N) models. From these simulations, we extract the order parameter distribution and compare it with FRG predictions.
We interpret the resulting distributions as a generalization of the Central Limit Theorem to systems with strongly correlated degrees of freedom. In this setting, critical correlations give rise to non-Gaussian universal distributions, extending the classical CLT paradigm beyond independent or weakly correlated variables.
| Affiliation | Institute for Physics |
|---|---|
| Link to paper | https://arxiv.org/abs/2501.04465 |
| Career status | PhD student |