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An iterative optimization approach that simultaneously minimizes the energy and optimizes the Lagrange multipliers enforcing desired constraints is presented. The method is tested on previously established benchmark systems and it is proved to be efficient and accurate. The approach can also be efficiently used when the constraint is not a scalar quantity but a spatially varying function like the charge density distribution.

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