Find the minimum point of polynomials using the Hessian matrix

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The Textbook Question

For $F_1(x,y) = \frac{1}{4}x^4 + x^2y + y^2$ and $F_2(x,y) = x^3 + xy - x$ find the second derivative matrices $H_1$ and $H_2$:

\begin{bmatrix}\frac{\partial^2 F}{\partial x^2}&\frac{\partial^2 F}{\partial x \partial y}\\\frac{\partial^2 F}{\partial x \partial y}&\frac{\partial^2 F}{\partial y^2}\end{bmatrix}

$H_1$ is positive definite so $F_1$ is concave up (= convex). Find the minimum point of $F_1$ and the saddle point of $F_2$ (look only where first derivatives are zero).

The Textbook Answer For $F_1$

$F_1 = \begin{bmatrix}6x^2&2x\\2x&2\end{bmatrix} $ is positive definite if $x \ne 0$;

$F_1 = (\frac{1}{2}x^2+y)^2=0$ on the curve $x^2+y=0$

My Answer For $F_1$

$\frac{\partial F_1}{\partial x}= x^3+2xy = x(x^2+2y)$

$\frac{\partial F_1}{\partial x}= 0 $

when

$x =0$

or when

$y = -\frac{1}{2}x^2$

so

$\frac{\partial^2 F_1}{\partial x^2}= 3x^2+2y=3x^2-x^2=2x^2$

$\frac{\partial^2 F_1}{\partial x \partial y}=2x$

$\frac{\partial^2 F_1}{\partial y^2}= 2$

$H_1 = \begin{bmatrix}2x^2&2x\\2x&2\end{bmatrix} $

A singular matrix

The minimum is the parabola $y = -\frac{1}{2}x^2$

Could someone please verify whether the textbook answer is wrong, the author is cleverer than I am so my calculations should be treated with more suspicion.