∫Calc Practice

Derivative of \( \displaystyle \frac{\ln{\left(\tan^{2}{\left(x - 1 \right)} + 1 \right)}}{2} \)

Problem 2.662 · hard Beautiful

Differentiate \( \displaystyle f(x) = \frac{\ln{\left(\tan^{2}{\left(x - 1 \right)} + 1 \right)}}{2} \).
  1. \[ \frac{d}{d x} \frac{\ln{\left(\tan^{2}{\left(x - 1 \right)} + 1 \right)}}{2} \]
    derivativeStart with the derivative of the function.✓ Proved
  2. \[ = \frac{\frac{d}{d x} \ln{\left(\tan^{2}{\left(x - 1 \right)} + 1 \right)}}{2} \]
    constant-multiplePull out the constant factor 1/2.✓ Proved
  3. \[ = \frac{\frac{d}{d x} \left(\tan^{2}{\left(x - 1 \right)} + 1\right)}{2 \left(\tan^{2}{\left(x - 1 \right)} + 1\right)} \]
    chainApply the chain rule for the logarithm.✓ Proved
  4. \[ = \frac{\frac{d}{d x} \tan^{2}{\left(x - 1 \right)}}{2 \left(\tan^{2}{\left(x - 1 \right)} + 1\right)} \]
    sumDifferentiate the sum term by term.✓ Proved
  5. \[ = \frac{\tan{\left(x - 1 \right)} \frac{d}{d x} \tan{\left(x - 1 \right)}}{\tan^{2}{\left(x - 1 \right)} + 1} \]
    powerApply the power rule to the squared tangent term.✓ Proved
  6. \[ = \frac{\tan{\left(x - 1 \right)} \sec^{2}{\left(x - 1 \right)} \frac{d}{d x} \left(x - 1\right)}{\tan^{2}{\left(x - 1 \right)} + 1} \]
    chainApply the chain rule to the tangent function.≈ Checked numerically
  7. \[ = \frac{\tan{\left(x - 1 \right)} \sec^{2}{\left(x - 1 \right)}}{\tan^{2}{\left(x - 1 \right)} + 1} \]
    derivative simplifyDifferentiate the inner linear function. Cancel the 1/2 and the 2.✓ Proved
  8. \[ = \tan{\left(x - 1 \right)} \]
    algebra simplifyUse the identity tan(x - 1)**2 + 1 = sec(x - 1)**2. Simplify the fraction by canceling sec(x - 1)**2.≈ Checked numerically
Answer \( \tan{\left(x - 1 \right)} \)
Mind the domain. The answer is also defined at points where f(x) is not. Substituting there gives a number that is not a slope of f.

✓ Nihil obstat Lines: 9 proved, 2 checked numerically. 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 1.14.0line 1 is the problem as stated
2✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
tan has poles at odd multiples of pi/2
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
tan has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
6≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left (tan(x - 1)**2 - sec(x - 1)**2 + 1)*tan(x - 1)/(tan(x - 1)**2 + 1); numeric agreement only, at 24 of 24 sampled points
tan has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
sec has poles at odd multiples of pi/2
7✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
sec has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
8✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
sec has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
9≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left (-tan(x - 1)**2 + sec(x - 1)**2 - 1)*tan(x - 1)/(tan(x - 1)**2 + 1); numeric agreement only, at 24 of 24 sampled points
tan has poles at odd multiples of pi/2
sec has poles at odd multiples of pi/2
undefined where tan(x - 1)**2 + 1 = 0
10✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated f directly and got the stated answer

Reviewers

  • gpt-oss:20b: pass
  • qwen3.6:27b-mlx: pass — The solution correctly applies differentiation rules step-by-step, adhering to the one-change-per-step constraint. The labels used are appropriate for the operations performed, and the final simplification is correct.
Every verdict on record (4)
  • qwen3.6:27b-mlx: pass 2026-09-21 — The solution correctly applies differentiation rules step-by-step, adhering to the one-change-per-step constraint. The labels used are appropriate for the operations performed, and the final simplification is correct.
  • gpt-oss:20b: pass 2026-09-21
  • qwen3.6:27b-mlx: pass 2026-09-21 — The solution correctly applies differentiation rules step-by-step, adhering to the one-change-per-step constraint. The labels used are appropriate for the operations performed, and the final simplification is valid.
  • gpt-oss:20b: pass 2026-09-21

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 gemma4:26b, checked 2026-09-26 with SymPy 1.14.0.