Constraints in Molecular Dynamics: Theory and SHAKE Algorithm

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Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.

Explores extremum of a function under constraints and finding candidate points in practice.

Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.

Covers advanced optimization techniques using Lagrange multipliers to find extrema of functions subject to constraints.

Covers the analysis of stationary points in functions, focusing on optimization methods.

Covers the limitations of Lagrange formalism and the transition to Hamiltonian formalism for dynamic variables.

Covers the principle of least action, Euler-Lagrange equations, Lagrange multipliers, and variational calculus.

Explores optimization with constraints using KKT conditions and interior point algorithm on two examples of quadratic programming.

Covers optimization methods without constraints, including gradient and line search in the quadratic case.