Second derivatives of parametric curves
Problem 8.168 · medium
For \( \displaystyle x = t + \frac{1}{t} \), \( \displaystyle y = t - \frac{1}{t} \), find \( \displaystyle \frac{dy}{dx} \) and \( \displaystyle \frac{d^2y}{dx^2} \) at \( \displaystyle t = 3 \).
- \[ \frac{\frac{d}{d t} \left(t - \frac{1}{t}\right)}{\frac{d}{d t} \left(t + \frac{1}{t}\right)} = \frac{t^{2} + 1}{t^{2} - 1} \]dy/dx = (dy/dt)/(dx/dt).✓ Proved
- \[ \frac{\frac{d}{d t} \frac{t^{2} + 1}{t^{2} - 1}}{\frac{d}{d t} \left(t + \frac{1}{t}\right)} = - \frac{4 t^{3}}{\left(t^{2} - 1\right)^{3}} \]d²y/dx² = [d/dt (dy/dx)] / (dx/dt).✓ Proved
- \[ \left[\begin{matrix}\frac{5}{4}\\- \frac{27}{128}\end{matrix}\right] \]At t = 3.✓ Proved
Answer \( \frac{dy}{dx} = \frac{5}{4},\ \frac{d^2y}{dx^2} = - \frac{27}{128} \)
✓ 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 | y found as a function of x by inverting x(t) numerically, then differenced |
Reviewers
gpt-oss:20b: passqwen3.6:27b-mlx: pass — The solution correctly applies the parametric differentiation formulas for the first and second derivatives. The algebraic simplifications and final evaluation at t=3 are correct.
Every verdict on record (4)
qwen3.6:27b-mlx: pass 2026-10-08 — The solution correctly applies the parametric differentiation formulas for the first and second derivatives. The algebraic simplifications and final evaluation at t=3 are correct.gpt-oss:20b: pass 2026-10-08gpt-oss:20b: pass 2026-10-08qwen3.6:27b-mlx: pass 2026-10-08 — The solution correctly applies the parametric differentiation formulas for the first and second derivatives. The algebraic simplifications and final evaluations at t=3 are correct.
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/parametric_second_derivative, checked 2026-10-08 with SymPy 1.14.0.