∫Calc Practice

Maximum rate of change

Problem 10.556 · medium

Find the directional derivative of \( \displaystyle f(x, y) = x e^{- y} \) at \( \displaystyle P(1, 1) \) in the direction toward \( \displaystyle Q(1, 4) \).
  1. \[ \left[\begin{matrix}\frac{\partial}{\partial x} x e^{- y}\\\frac{\partial}{\partial y} x e^{- y}\end{matrix}\right] = \left[\begin{matrix}e^{- y}\\- x e^{- y}\end{matrix}\right] \]
    ∇f.✓ Proved
  2. \[ \left[\begin{matrix}e^{-1}\\- \frac{1}{e}\end{matrix}\right] \]
    ∇f(1, 1).✓ Proved
  3. \[ \left[\begin{matrix}0\\1\end{matrix}\right] \]
    The unit vector from P toward Q.✓ Proved
  4. \[ - \frac{1}{e} \]
    D_u f = ∇f · u.✓ Proved
Answer \( D_{\mathbf u} f = - \frac{1}{e} \)

✓ 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
LineStatusChecked byDetail
1✓ Provedsympy 1.14.0simplify(lhs - rhs) reduced to 0
2✓ Provedsympy 1.14.0simplify(lhs - rhs) reduced to 0
3✓ Provedsympy 1.14.0simplify(lhs - rhs) reduced to 0
4✓ Provedsympy 1.14.0simplify(lhs - rhs) reduced to 0
answer, a second way✓ Checked independentlysympy 1.14.0 + mpmath 1.3.0difference quotient along the direction

Reviewers

  • gpt-oss:20b: pass
  • qwen3.6:27b-mlx: pass — The solution correctly computes the gradient, identifies the unit direction vector, and calculates the dot product to find the directional derivative.
Every verdict on record (4)
  • gpt-oss:20b: pass 2026-10-13
  • qwen3.6:27b-mlx: pass 2026-10-13 — The solution correctly computes the gradient, identifies the unit direction vector, and calculates the dot product to find the directional derivative.
  • qwen3.6:27b-mlx: pass 2026-10-13 — The solution correctly computes the gradient, identifies the direction vector, normalizes it to a unit vector, and performs the dot product. The steps are logically sound and algebraically correct.
  • gpt-oss:20b: pass 2026-10-13

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 2026-10-13 with SymPy 1.14.0.