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.
Second and mixed partials
Product rule twice, then factor
Write , so that . For the partial, treat as constant and apply the product rule to .
Differentiate that again in . The bracket contributes and the exponential contributes .
For the mixed partial, differentiate in . Here is constant and the product needs the rule again, which factors into a tidy symmetric form.
Since swapping and leaves unchanged, 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 is never zero, the critical point equations reduce to and . The solutions are and .
At the origin, , , and , so and the origin is a saddle point. That matches the surface: is positive in the first and third quadrants and negative in the second and fourth.
At the mixed partial vanishes because of the factor , and both pure partials are negative.
So with , giving a local maximum of value .
The mistake students make
The frequent error is differentiating the two factors separately and multiplying the results, which turns into instead of . 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 is , while the mistaken route just repeats at every stage.
A useful pattern for this family: differentiating in gives , so goes to and goes to . The constant climbs by 1 with each derivative while the 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 , which is a saddle. The twist term alone decides it.
Frequently asked questions
Why does the mixed partial factor so neatly?
Because separates as . One derivative in each variable is , which is the product form of .
Is the local maximum at (-1,-1) a global maximum?
No. Along the ray with large and positive, grows without bound, so the value is only a local maximum.