Multivariable calculus

Second Partial Derivatives of xy e^(x+y)

Write E = e^(x+y). For f(x,y) = xy E the second partials are f_xx = y(2 + x)E, f_yy = x(2 + y)E, and the mixed partial f_xy = (1 + x)(1 + y)E. The critical points are the origin, a saddle, and the point (-1,-1), a local maximum of value 1/e^2. Both mixed orders give the same formula.

f(x,y)=xyex+yf(x,y) = xy\,e^{x+y}
fx=y(1+x)ex+y\frac{\partial f}{\partial x} = y(1 + x)\,e^{x+y}
fy=x(1+y)ex+y\frac{\partial f}{\partial y} = x(1 + y)\,e^{x+y}

Second and mixed partials

2fx2=y(2+x)ex+y\frac{\partial^{2} f}{\partial x^{2}} = y(2 + x)\,e^{x+y}
2fyx=(1+x)(1+y)ex+y\frac{\partial^{2} f}{\partial y\,\partial x} = (1 + x)(1 + y)\,e^{x+y}
2fy2=x(2+y)ex+y\frac{\partial^{2} f}{\partial y^{2}} = x(2 + y)\,e^{x+y}

Product rule twice, then factor

Write E=ex+yE = e^{x+y}, so that Ex=Ey=E\frac{\partial E}{\partial x} = \frac{\partial E}{\partial y} = E. For the xx partial, treat yy as constant and apply the product rule to xEx \cdot E.

fx=y(E+xE)=y(1+x)E\frac{\partial f}{\partial x} = y\left(E + xE\right) = y(1 + x)E

Differentiate that again in xx. The bracket y(1+x)y(1+x) contributes yEyE and the exponential contributes y(1+x)Ey(1+x)E.

2fx2=yE+y(1+x)E=y(2+x)E\frac{\partial^{2} f}{\partial x^{2}} = yE + y(1 + x)E = y(2 + x)E

For the mixed partial, differentiate y(1+x)Ey(1 + x)E in yy. Here (1+x)(1 + x) is constant and the product yEy \cdot E needs the rule again, which factors into a tidy symmetric form.

2fyx=(1+x)(E+yE)=(1+x)(1+y)E\frac{\partial^{2} f}{\partial y\,\partial x} = (1 + x)\left(E + yE\right) = (1 + x)(1 + y)E

Since swapping xx and yy leaves ff unchanged, fyy=x(2+y)Ef_{yy} = x(2 + y)E follows without further work, and the mixed partial is already symmetric under the swap, which is the Clairaut consistency you should expect.

Classifying both critical points

Because EE is never zero, the critical point equations reduce to y(1+x)=0y(1 + x) = 0 and x(1+y)=0x(1 + y) = 0. The solutions are (0,0)(0,0) and (1,1)(-1,-1).

At the origin, fxx=0f_{xx} = 0, fyy=0f_{yy} = 0, and fxy=1f_{xy} = 1, so D=1<0D = -1 < 0 and the origin is a saddle point. That matches the surface: ff is positive in the first and third quadrants and negative in the second and fourth.

At (1,1)(-1,-1) the mixed partial vanishes because of the factor (1+x)(1 + x), and both pure partials are negative.

fxx(1,1)=e2,fyy(1,1)=e2,fxy(1,1)=0f_{xx}(-1,-1) = -e^{-2}, \qquad f_{yy}(-1,-1) = -e^{-2}, \qquad f_{xy}(-1,-1) = 0

So D=e4>0D = e^{-4} > 0 with fxx<0f_{xx} < 0, giving a local maximum of value f(1,1)=e20.135f(-1,-1) = e^{-2} \approx 0.135.

The mistake students make

The frequent error is differentiating the two factors separately and multiplying the results, which turns fxf_x into yEyE instead of y(1+x)Ey(1 + x)E. The product rule adds two terms, it does not multiply two derivatives, and the term that gets dropped is the one that grows: the correct fxxf_{xx} is y(2+x)Ey(2 + x)E, while the mistaken route just repeats yEyE at every stage.

A useful pattern for this family: differentiating p(x)Ep(x)E in xx gives (p+p)E\left(p + p'\right)E, so xExE goes to (1+x)E(1 + x)E and (1+x)E(1 + x)E goes to (2+x)E(2 + x)E. The constant climbs by 1 with each derivative while the xx term stays put.

The second slip is classifying the origin as a maximum or minimum because both pure second partials are zero there. Zero pure curvature with a nonzero mixed partial means D<0D < 0, which is a saddle. The twist term alone decides it.

Frequently asked questions

Why does the mixed partial factor so neatly?

Because ff separates as (xex)(yey)\left(xe^{x}\right)\left(ye^{y}\right). One derivative in each variable is ddx(xex)ddy(yey)=(1+x)ex(1+y)ey\frac{d}{dx}\left(xe^{x}\right) \cdot \frac{d}{dy}\left(ye^{y}\right) = (1 + x)e^{x}(1 + y)e^{y}, which is the product form of (1+x)(1+y)E(1 + x)(1 + y)E.

Is the local maximum at (-1,-1) a global maximum?

No. Along the ray y=xy = x with xx large and positive, f=x2e2xf = x^{2}e^{2x} grows without bound, so the value e2e^{-2} is only a local maximum.