# Mean field theory of short range order in strongly correlated low dimensional electronic systems

## TL;DR

This paper extends the covariant gaussian approximation to fermionic systems with composite order parameters, improving mean field predictions for low-dimensional strongly correlated electronic systems like the Hubbard model.

## Contribution

It introduces a novel scheme for symmetry restoration in fermionic systems, validated through comparisons with exact and Monte Carlo results in 1D and 2D Hubbard models.

## Key findings

- Improved correlator accuracy over traditional mean field methods.
- Successful symmetry restoration in low-dimensional Hubbard models.
- Better agreement with exact and Monte Carlo simulations.

## Abstract

Mean field approach, although a generally reliable tool that captures major short range correlations, often fails in symmetric low dimensional strongly correlated electronic systems like those described by the Hubbard model. In these situations a symmetry is \almost broken". The problem is linked to the restoration of the symmetry due to strong uctuations (both quantum and thermal) on all scales. The restoration of symmetry in statistical models of scalar \order parameter" fields was treated recently successfully on the gaussian approximation level by symmetrization of the correlators. Here the idea is extended to fermionic systems in which the order parameter is composite. Furthermore the precision of the correlators can be improved perturbatively. Such a scheme (based on covariant gaussian approximation) is demonstrated on the 1D and 2D one band Hubbard models by comparison of the correlator with exact diagonalization and MC simulations respectively.