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ubuntu2004

The 2nd Derivative test

The second derivative test looks at the eigenvalues of the Hessian matrix evaluated at critical points.

The idea for this came from Ben Woodruff, who implemented a similar thing in Mathematica.

var('x,y')
(x, y)
f(x,y)=-x^2+y^2 table, graph=illustrate_test(f) print table show(graph)
Critical PointEigenvalueEigenvector
(0.0, 0.0, 0.0)-2.0(1.0, 0.0)
(0.0, 0.0, 0.0)2.0(0.0, 1.0)
f(x,y)=x*y*exp((-x^2-y^2)/3) table, graph=illustrate_test(f) print table show(graph)
Critical PointEigenvalueEigenvector
(0.0, 0.0, 0.0)1.0(0.707106781187, 0.707106781187)
(0.0, 0.0, 0.0)-1.0(-0.707106781187, 0.707106781187)
(-1.22474487139, -1.22474487139, 0.551819161757)-0.735758882343(0.707106781187, 0.707106781187)
(-1.22474487139, -1.22474487139, 0.551819161757)-0.735758882343(-0.707106781187, 0.707106781187)
(1.22474487139, -1.22474487139, -0.551819161757)0.735758882343(0.707106781187, 0.707106781187)
(1.22474487139, -1.22474487139, -0.551819161757)0.735758882343(-0.707106781187, 0.707106781187)
(-1.22474487139, 1.22474487139, -0.551819161757)0.735758882343(0.707106781187, 0.707106781187)
(-1.22474487139, 1.22474487139, -0.551819161757)0.735758882343(-0.707106781187, 0.707106781187)
(1.22474487139, 1.22474487139, 0.551819161757)-0.735758882343(0.707106781187, 0.707106781187)
(1.22474487139, 1.22474487139, 0.551819161757)-0.735758882343(-0.707106781187, 0.707106781187)
illustrate_test?