A gradient-based trust radius update suitable for saddle point and transition state optimization

Abstract

A new trust radius method, appropriate for saddle point optimization is proposed. The idea is to ensure that the gradients from the quadratic model, and the exact computed gradients, are similar in direction and magnitude. For transition state optimization, the new trust radius method is found to work somewhat better than more traditional methods, based on the value of the objective function.