 In higher dimensions, a critical point of a scalar valued function is a point at which the gradient is zero.The second derivative test can still be used to analyse critical points by considering the eigenvalues of the Hessian matrix of second partial derivatives of the function at the critical point.If all of the eigenvalues are positive, then the point is a local minimum; if all are negative, it is a local maximum.