∫Calc Practice

Gradient and directional derivatives

Problem 10.149 · medium

Find the directional derivative of \( \displaystyle f(x, y) = x^{2} + 3 x y + y^{2} \) at \( \displaystyle (1, 2) \) in the direction of \( \displaystyle \langle -1, 2 \rangle \).
  1. \[ \left[\begin{matrix}\frac{\partial}{\partial x} \left(x^{2} + 3 x y + y^{2}\right)\\\frac{\partial}{\partial y} \left(x^{2} + 3 x y + y^{2}\right)\end{matrix}\right] = \left[\begin{matrix}2 x + 3 y\\3 x + 2 y\end{matrix}\right] \]
    ∇f.✓ Proved
  2. \[ \left[\begin{matrix}8\\7\end{matrix}\right] \]
    ∇f at the point.✓ Proved
  3. \[ \left[\begin{matrix}\frac{\left(-1\right) \sqrt{5}}{5}\\\frac{2 \sqrt{5}}{5}\end{matrix}\right] = \left[\begin{matrix}- \frac{\sqrt{5}}{5}\\\frac{2 \sqrt{5}}{5}\end{matrix}\right] \]
    The unit direction u.✓ Proved
  4. \[ \frac{6 \sqrt{5}}{5} \]
    D_u f = ∇f · u.✓ Proved
Answer \( \frac{6 \sqrt{5}}{5} \)

✓ 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 1.3.0f differenced along the unit direction agrees

Reviewers

  • gpt-oss:20b: pass
  • qwen3.6:27b-mlx: pass
Every verdict on record (4)
  • qwen3.6:27b-mlx: pass 2026-09-26
  • gpt-oss:20b: pass 2026-09-26
  • qwen3.6:27b-mlx: pass 2026-09-26
  • gpt-oss:20b: pass 2026-09-26

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/gradient_directional, checked 2026-09-26 with SymPy 1.14.0.