Conformal invariance constraints in the $O(N)$ models: a first study within the nonperturbative renormalization group

TL;DR

This study investigates how conformal invariance constrains $O(N)$ models within the nonperturbative renormalization group framework, focusing on derivative expansion at order $ abla^2$, and compares critical exponent predictions with established methods.

Contribution

It applies conformal symmetry constraints to $O(N)$ models using the derivative expansion at order $ abla^2$, addressing symmetry breaking issues in the approximation.

Findings

Conformal symmetry constraints help fix non-physical parameters.

Predicted critical exponents are consistent with the principle of minimal sensitivity.

Minimizing conformal symmetry breaking improves approximation accuracy.

Abstract

The behavior of many critical phenomena at large distances is expected to be invariant under the full conformal group, rather than only isometries and scale transformations. When studying critical phenomena, approximations are often required, and the framework of the nonperturbative, or functional renormalization group is no exception. The derivative expansion is one of the most popular approximation schemes within this framework, due to its great performance on multiple systems, as evidenced in the last decades. Nevertheless, it has the downside of breaking conformal symmetry at a finite order. This breaking is not observed at the leading order of the expansion, denoted LPA approximation, and only appears once one considers, at least, the next-to-leading order of the derivative expansion ($\mathcal{O}(\partial^2)$) when including composite operators. In this work, we study the constraints arising from conformal symmetry for the $O(N)$ models using the derivative expansion at order $\mathcal{O}(\partial^2)$. We explore various values of $N$ and minimize the breaking of conformal symmetry to fix the non-physical parameters of the approximation procedure. We compare our prediction for the critical exponents with those coming from a more usual procedure, known as the principle of minimal sensitivity.