Instabilities in self-consistent diagrammatic approaches and how to cure them
Self-consistent diagrammatic approaches often fail to find correct solutions in strongly correlated regimes due to 'misleading convergence.' The study proves this isn't a flaw in the theory but an issue with iterative math. By inverting unstable directions of the Jacobian matrix, a new method stabilizes these schemes, allowing them to reliably converge across all parameter ranges.