# New critical exponent inequalities for percolation and the random cluster model

## TL;DR

This paper introduces new inequalities relating critical exponents in percolation and the random cluster model, providing insights into cluster volume distributions and their behavior across different graph structures.

## Contribution

It establishes novel differential inequalities for cluster volume distributions, leading to new critical exponent inequalities valid on any transitive graph.

## Key findings

- Proves the inequalities γ ≤ δ-1 and Δ ≤ γ+1 for percolation models.
- Shows exponential tail decay of cluster volume in the subcritical phase.
- Extends results to infinite-range models, including Euclidean settings.

## Abstract

We apply a variation on the methods of Duminil-Copin, Raoufi, and Tassion to establish a new differential inequality applying to both Bernoulli percolation and the Fortuin-Kasteleyn random cluster model. This differential inequality has a similar form to that derived for Bernoulli percolation by Menshikov but with the important difference that it describes the distribution of the volume of a cluster rather than of its radius. We apply this differential inequality to prove the following: The critical exponent inequalities $\gamma \leq \delta-1$ and $\Delta \leq \gamma +1$ hold for percolation and the random cluster model on any transitive graph. These inequalities are new even in the context of Bernoulli percolation on $\mathbb{Z}^d$, and are saturated in mean-field for Bernoulli percolation and for the random cluster model with $q \in [1,2)$. The volume of a cluster has an exponential tail in the entire subcritical phase of the random cluster model on any transitive graph. This proof also applies to infinite-range models, where the result is new even in the Euclidean setting.