Maximum rate of change
Problem 10.485 · medium
Find the directional derivative of \( \displaystyle f(x, y) = x e^{- y} \) at \( \displaystyle P(3, 4) \) in the direction toward \( \displaystyle Q(3, 6) \).
- \[ \left[\begin{matrix}\frac{\partial}{\partial x} x e^{- y}\\\frac{\partial}{\partial y} x e^{- y}\end{matrix}\right] = \left[\begin{matrix}e^{- y}\\- x e^{- y}\end{matrix}\right] \]∇f.✓ Proved
- \[ \left[\begin{matrix}e^{-4}\\- \frac{3}{e^{4}}\end{matrix}\right] \]∇f(3, 4).✓ Proved
- \[ \left[\begin{matrix}0\\1\end{matrix}\right] \]The unit vector from P toward Q.✓ Proved
- \[ - \frac{3}{e^{4}} \]D_u f = ∇f · u.✓ Proved
Answer \( D_{\mathbf u} f = - \frac{3}{e^{4}} \)
✓ Nihil obstat Every line of this solution was proved by the computer algebra system SymPy. The answer was also checked a second way, without looking at the solution. Reviewers found nothing wrong with the explanation.
The full receipt
| Line | Status | Checked by | Detail |
|---|---|---|---|
| 1 | ✓ Proved | sympy 1.14.0 | simplify(lhs - rhs) reduced to 0 |
| 2 | ✓ Proved | sympy 1.14.0 | simplify(lhs - rhs) reduced to 0 |
| 3 | ✓ Proved | sympy 1.14.0 | simplify(lhs - rhs) reduced to 0 |
| 4 | ✓ Proved | sympy 1.14.0 | simplify(lhs - rhs) reduced to 0 |
| answer, a second way | ✓ Checked independently | sympy 1.14.0 + mpmath 1.3.0 | difference quotient along the direction |
Reviewers
gpt-oss:20b: passqwen3.6:27b-mlx: pass — The solution correctly identifies the gradient, evaluates it at the given point, determines the correct unit direction vector, and computes the dot product accurately.
Every verdict on record (4)
qwen3.6:27b-mlx: pass 2026-10-10 — The solution correctly identifies the gradient, evaluates it at the given point, determines the correct unit direction vector, and computes the dot product accurately.gpt-oss:20b: pass 2026-10-10gpt-oss:20b: pass 2026-10-10qwen3.6:27b-mlx: pass 2026-10-10 — The solution correctly identifies the gradient, evaluates it at the given point, determines the correct unit direction vector, and computes the dot product accurately.
Proved: SymPy reduced the difference between the two sides to zero. Checked independently: a separate
method, named above, confirmed it. Checked numerically: the two sides agree at every sampled point, which is evidence,
not proof. Reviewed: a model or a person read it; that is all a sentence can have. Solution by
generator:structured/max_rate_of_change, checked 2026-10-10 with SymPy 1.14.0.