Local extrema of $x^2 + y^2 + axy$

multivariable-calculus

let a be a constant, find and classify local extrema.

so i found the partials and set them to 0:

$2x + ay = 0$ and $2y + ax = 0$ and found as solutions $(0,0)$ and the lines $ x = y$ and $x = -y$ when $a$ is -2 and 2 respectively.

taking the second derivatives, i found that the determinant of the matrix of second derivatives is $4 – a^2$.

Since 2 is always positive, I only looked for minimas and saddle points. The saddle points occur when $a>2$ or $a<-2$ and the only critical point at which this occurs is the origin. Thus if $a>2$ or $a<-2$ there will be a saddle point at $(0,0)$

for the determinant to be positive, we need $-2 < a <2$, which again is only a critical point at the origin. Thus if $-2 < a <2$, there is a min at the origin.

If determinant is 0, we get $f(x,y) = (x+y)^2$ or $(x-y)^2$ and thus there is a minimum at the origin.

Lastly, in the case where $a = -2$ or $a = 2$, there are an indeterminate critical points along the lines $x = y$ and $x = -y$.

Is this correct? And is there a way to find out the nature of the indeterminate critical points by inspection?

Thanks

Best Answer

You were doing well until the very end. Note that the determinant of the Hessian, which is also a multiple of the discriminant of the original quadric, vanishes precisely when $a=\pm2$, so this case is really the same as the next one that you describe, and the critical point at the origin is in fact also indeterminate.

To determine the nature of the critical points in this case, it’s helpful to step back from the calculus and algebra and take a geometric look at the situation. When $|a|\lt 2$, the graph of this function is an elliptic paraboloid opening upward with vertex at the origin. For $|a|\gt2$, we have a classic saddle surface. Finally, when $|a|=2$, we have a parabolic cylinder, with the bottom of the “valley” along the line $x+y=0$ or $x-y=0$. So, in the indeterminate case, the function is constant along this line and increasing in every other direction away from the line.

You can examine the spectrum of the Hessian matrix to determine all of this: at a critical point, the first-order derivatives vanish, so per its Taylor expansion, the behavior of the function near this point is dominated by the quadratic form determined by the second derivatives. In other words, near a critical point, the function “looks like” the quadric defined by its Hessian. The signs of the Hessian’s eigenvalues thus tell you whether the function is generally increasing or decreasing in the principal axis directions near a critical point.

For a $2\times2$ Hessian, a positive determinant means that the eigenvalues are either both positive—a local minimum—or both negative—a local maximum. You can examine the sign of its trace, or more simply, its upper-left entry, to determine which of these two cases you have. A negative determinant means that the eigenvalues have opposite signs—increasing in one principal direction but decreasing in the other, i.e., a saddle point. A zero determinant means that there’s at least one zero eigenvalue, so we have to probe more deeply.

For this particular family of functions, the trace of the Hessian is always positive, so when the determinant vanishes we have one positive and one zero eigenvalue: the function is increasing along one principal axis. For its behavior in the other principal direction, we have to look at higher-order derivatives or examine the behavior of the function near the critical point directly. In this case, we’ve run out of derivatives—all third- and higher-order derivatives vanish—but it’s easy to see that the function is zero all along the “trough” of the cylinder, as you’ve determined.