Eigenvalue

If a (scalar) value, $LaTeX: \lambda$, satisfies $LaTeX: Ax = \lambda x$ for some vector, $LaTeX: x \neq 0$, it is an eigenvalue of the matrix $LaTeX: A$, and $LaTeX: x$ is an eigenvector. In mathematical programming this arises in the context of convergence analysis, where $LaTeX: A$ is the hessian of some merit function, such as the objective or Lagrangian.