Maximum rate of change
Problem 10.335 · medium
Find the maximum rate of change of \( \displaystyle f(x, y) = x^{2} y - y^{2} \) at \( \displaystyle (1, 1) \), and the direction in which it occurs.
- \[ \left[\begin{matrix}\frac{\partial}{\partial x} \left(x^{2} y - y^{2}\right)\\\frac{\partial}{\partial y} \left(x^{2} y - y^{2}\right)\end{matrix}\right] = \left[\begin{matrix}2 x y\\x^{2} - 2 y\end{matrix}\right] \]∇f.✓ Proved
- \[ \left[\begin{matrix}2\\-1\end{matrix}\right] \]∇f(1, 1).✓ Proved
- \[ \sqrt{5} \]The maximum rate of change is ‖∇f‖, in the direction of ∇f.✓ Proved
Answer \( \|\nabla f\| = \sqrt{5}\ \text{in the direction of}\ \left\langle 2, -1 \right\rangle \)
✓ 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 |
| answer, a second way | ✓ Checked independently | sympy 1.14.0 + mpmath 1.3.0 | the largest directional difference quotient over 3600 directions |
Reviewers
gpt-oss:20b: passqwen3.6:27b-mlx: pass — The solution correctly identifies the gradient, evaluates it at the given point, and applies the standard theorem that the maximum rate of change is the magnitude of the gradient in the direction of the gradient.
Every verdict on record (4)
qwen3.6:27b-mlx: pass 2026-10-04 — The solution correctly identifies the gradient, evaluates it at the given point, and applies the standard theorem that the maximum rate of change is the magnitude of the gradient in the direction of the gradient.gpt-oss:20b: pass 2026-10-04qwen3.6:27b-mlx: pass 2026-10-04 — The solution correctly computes the gradient, evaluates it at the given point, and applies the standard theorem that the maximum rate of change is the magnitude of the gradient in the direction of the gradient.gpt-oss:20b: pass 2026-10-04
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 2026-10-04 with SymPy 1.14.0.