Quasi-Newton methods are optimization algorithms used to find the minimum of a function by approximating the Hessian matrix, which describes the curvature of the function. These methods improve efficiency in electronic structure calculations by avoiding the direct computation of second derivatives, thus allowing for faster convergence and reduced computational costs. They are particularly useful in contexts where evaluating the full Hessian is impractical due to resource constraints.
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