∫Calc Practice

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

Problem 2.968 · hard

Differentiate \( \displaystyle f(x) = - \frac{\ln{\left(\tan^{2}{\left(2 x - 1 \right)} + 1 \right)}}{2} + \ln{\left(\tan{\left(2 x - 1 \right)} \right)} \).
  1. \[ \frac{d}{d x} \left(- \frac{\ln{\left(\tan^{2}{\left(2 x - 1 \right)} + 1 \right)}}{2} + \ln{\left(\tan{\left(2 x - 1 \right)} \right)}\right) \]
    sumDifferentiate the sum of two terms.✓ Proved
  2. \[ = \frac{d}{d x} \left(- \frac{\ln{\left(\tan^{2}{\left(2 x - 1 \right)} + 1 \right)}}{2}\right) + \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} \]
    constantPull out the constant factor.✓ Proved
  3. \[ = - \frac{\frac{d}{d x} \ln{\left(\tan^{2}{\left(2 x - 1 \right)} + 1 \right)}}{2} + \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} \]
    chainApply the chain rule to the first term.✓ Proved
  4. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{\frac{d}{d x} \left(\tan^{2}{\left(2 x - 1 \right)} + 1\right)}{2 \left(\tan^{2}{\left(2 x - 1 \right)} + 1\right)} \]
    sumDifferentiate the argument of the logarithm.✓ Proved
  5. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{\frac{d}{d x} 1 + \frac{d}{d x} \tan^{2}{\left(2 x - 1 \right)}}{2 \left(\tan^{2}{\left(2 x - 1 \right)} + 1\right)} \]
    constantDifferentiate the sum inside the parentheses.✓ Proved
  6. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{\frac{d}{d x} \tan^{2}{\left(2 x - 1 \right)}}{2 \left(\tan^{2}{\left(2 x - 1 \right)} + 1\right)} \]
    constantThe derivative of a constant is zero.✓ Proved
  7. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{\tan{\left(2 x - 1 \right)} \frac{d}{d x} \tan{\left(2 x - 1 \right)}}{\tan^{2}{\left(2 x - 1 \right)} + 1} \]
    powerApply the power rule to tan(2*x - 1)**2.✓ Proved
  8. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{\tan{\left(2 x - 1 \right)} \sec^{2}{\left(2 x - 1 \right)} \frac{d}{d x} \left(2 x - 1\right)}{\tan^{2}{\left(2 x - 1 \right)} + 1} \]
    chainApply the chain rule to tan(2*x - 1).≈ Checked numerically
  9. \[ = \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} - \frac{2 \tan{\left(2 x - 1 \right)} \sec^{2}{\left(2 x - 1 \right)}}{\tan^{2}{\left(2 x - 1 \right)} + 1} \]
    chain algebra algebraDifferentiate the inner linear function 2*x - 1. Simplify the product of constants. Combine the fraction and the constant.✓ Proved
  10. \[ = - 2 \tan{\left(2 x - 1 \right)} + \frac{d}{d x} \ln{\left(\tan{\left(2 x - 1 \right)} \right)} \]
    trig algebraUse the identity tan(u)**2 + 1 = sec(u)**2. Cancel the sec(2*x - 1)**2 term.≈ Checked numerically
  11. \[ = - 2 \tan{\left(2 x - 1 \right)} + \frac{\frac{d}{d x} \tan{\left(2 x - 1 \right)}}{\tan{\left(2 x - 1 \right)}} \]
    chainApply the chain rule to the second term's logarithm.✓ Proved
  12. \[ = - 2 \tan{\left(2 x - 1 \right)} + \frac{2 \sec^{2}{\left(2 x - 1 \right)}}{\tan{\left(2 x - 1 \right)}} \]
    chain algebraDifferentiate tan(2*x - 1). Simplify the product.≈ Checked numerically
  13. \[ = \frac{2 \tan^{2}{\left(2 x - 1 \right)} + 2}{\tan{\left(2 x - 1 \right)}} - 2 \tan{\left(2 x - 1 \right)} \]
    trigSubstitute sec(2*x - 1)**2 with 1 + tan(2*x - 1)**2.≈ Checked numerically
  14. \[ = \frac{2}{\tan{\left(2 x - 1 \right)}} \]
    algebra algebraDistribute the division by tan(2*x - 1). Combine like terms.✓ Proved
Answer \( \frac{2}{\tan{\left(2 x - 1 \right)}} \)
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: 16 proved, 4 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
4✓ 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(2*x - 1)**2 + 1 = 0
5✓ 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(2*x - 1)**2 + 1 = 0
6✓ 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(2*x - 1)**2 + 1 = 0
7✓ 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(2*x - 1)**2 + 1 = 0
8≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left 2*(-tan(2*x - 1)**2 + sec(2*x - 1)**2 - 1)*tan(2*x - 1)/(tan(2*x - 1)**2 + 1); numeric agreement only, at 24 of 24 sampled points
log is undefined for non-positive arguments
tan has poles at odd multiples of pi/2
undefined where tan(2*x - 1)**2 + 1 = 0
sec has poles at odd multiples of pi/2
9✓ 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
sec has poles at odd multiples of pi/2
undefined where tan(2*x - 1)**2 + 1 = 0
10✓ 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
sec has poles at odd multiples of pi/2
undefined where tan(2*x - 1)**2 + 1 = 0
11✓ 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
sec has poles at odd multiples of pi/2
undefined where tan(2*x - 1)**2 + 1 = 0
12≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left 2*(tan(2*x - 1)**2 - sec(2*x - 1)**2 + 1)*tan(2*x - 1)/(tan(2*x - 1)**2 + 1); numeric agreement only, at 24 of 24 sampled points
log is undefined for non-positive arguments
tan has poles at odd multiples of pi/2
sec has poles at odd multiples of pi/2
undefined where tan(2*x - 1)**2 + 1 = 0
13✓ 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
14✓ 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(2*x - 1) = 0
15≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left 2*(tan(2*x - 1)**2 - sec(2*x - 1)**2 + 1)/tan(2*x - 1); numeric agreement only, at 24 of 24 sampled points
tan has poles at odd multiples of pi/2
undefined where tan(2*x - 1) = 0
sec has poles at odd multiples of pi/2
16✓ 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(2*x - 1) = 0
17≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left 2*(-tan(2*x - 1)**2 + sec(2*x - 1)**2 - 1)/tan(2*x - 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(2*x - 1) = 0
18✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
undefined where tan(2*x - 1) = 0
19✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
tan has poles at odd multiples of pi/2
undefined where tan(2*x - 1) = 0
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
undefined where tan(2*x - 1) = 0
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated f directly and got the stated answer

Reviewers

  • gpt-oss:20b: fail (style) — Several steps apply more than one rule or use an incorrect label. For example, step 5 is a sum‑rule application but is labeled "constant"; step 2 pulls out a constant factor and should be labeled "constant‑multiple"; step 4 applies the chain rule to the logarithm but is labeled "sum". These mislabelings violate the contract’s granularity rules.
  • qwen3.6:27b-mlx: fail (style) — Step 2 is labeled 'constant' but performs the linearity of the derivative (splitting the sum), which should be labeled 'sum'. Step 3 is labeled 'chain' but performs pulling out a constant factor, which should be labeled 'constant-multiple'. The labels do not match the operations performed.
Every verdict on record (4)
  • qwen3.6:27b-mlx: fail (style) 2026-09-27 — Step 2 is labeled 'constant' but performs the linearity of the derivative (splitting the sum), which should be labeled 'sum'. Step 3 is labeled 'chain' but performs pulling out a constant factor, which should be labeled 'constant-multiple'. The labels do not match the operations performed.
  • gpt-oss:20b: fail (style) 2026-09-27 — Several steps apply more than one rule or use an incorrect label. For example, step 5 is a sum‑rule application but is labeled "constant"; step 2 pulls out a constant factor and should be labeled "constant‑multiple"; step 4 applies the chain rule to the logarithm but is labeled "sum". These mislabelings violate the contract’s granularity rules.
  • qwen3.6:27b-mlx: fail (style) 2026-09-27 — Step 2 is labeled 'constant' but performs the linearity of the derivative (splitting the sum), which should be labeled 'sum'. Step 3 is labeled 'chain' but performs pulling out a constant factor, which should be labeled 'constant-multiple'. The labels do not match the operations performed.
  • gpt-oss:20b: fail (style) 2026-09-27 — Step 5 incorrectly labels the operation as "constant"; it is actually a "sum" rule applied to the derivative of the argument of the logarithm.

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 2026-09-27 with SymPy 1.14.0.