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Derivative of \( \displaystyle \ln{\left(\frac{e^{2 x}}{4 x^{2}} \right)} \)

Problem 2.1143 · hard Beautiful

Differentiate \( \displaystyle f(x) = \ln{\left(\frac{e^{2 x}}{4 x^{2}} \right)} \).
  1. \[ \frac{d}{d x} \ln{\left(\frac{e^{2 x}}{4 x^{2}} \right)} \]
    derivativeStart with the derivative of the function.✓ Proved
  2. \[ = \frac{d}{d x} \left(2 x - \ln{\left(4 x^{2} \right)}\right) \]
    algebra simplifyUse the property log(a/b) = log(a) - log(b). Simplify log(exp(2*x)) to 2*x.✓ Proved
  3. \[ = \frac{d}{d x} 2 x - \frac{d}{d x} \ln{\left(4 x^{2} \right)} \]
    sumSplit the derivative using the difference rule.✓ Proved
  4. \[ = 2 - \frac{d}{d x} \ln{\left(4 x^{2} \right)} \]
    constantThe derivative of 2*x is 2.✓ Proved
  5. \[ = 2 - \frac{d}{d x} \left(\ln{\left(x^{2} \right)} + \ln{\left(4 \right)}\right) \]
    algebraUse the property log(ab) = log(a) + log(b).✓ Proved
  6. \[ = - \frac{d}{d x} \ln{\left(4 \right)} - \frac{d}{d x} \ln{\left(x^{2} \right)} + 2 \]
    sumDistribute the derivative.✓ Proved
  7. \[ = 2 - \frac{d}{d x} \ln{\left(x^{2} \right)} \]
    constantThe derivative of the constant log(4) is 0.✓ Proved
  8. \[ = 2 - \frac{d}{d x} 2 \ln{\left(x \right)} \]
    rewriteUse the power rule for logarithms: log(x**2) = 2*log(x).✓ Proved
  9. \[ = 2 - 2 \frac{d}{d x} \ln{\left(x \right)} \]
    constant-multiplePull the constant factor 2 out of the derivative.✓ Proved
  10. \[ = 2 - \frac{2}{x} \]
    derivative simplifyThe derivative of log(x) is 1/x. Simplify the expression.✓ Proved
Answer \( 2 - \frac{2}{x} \)

✓ 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 1.14.0line 1 is the problem as stated
2✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
undefined where x = 0
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
6✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
7✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
8✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
9✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
10✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
11✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
undefined where x = 0
12✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where x = 0
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
undefined where x = 0
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 logarithmic properties to simplify the expression before differentiating, and each step adheres to the single-rule constraint with appropriate labels.
Every verdict on record (4)
  • qwen3.6:27b-mlx: pass 2026-09-28 — The solution correctly applies logarithmic properties to simplify the expression before differentiating, and each step adheres to the single-rule constraint with appropriate labels.
  • gpt-oss:20b: pass 2026-09-28
  • qwen3.6:27b-mlx: pass 2026-09-28
  • gpt-oss:20b: pass 2026-09-28

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 2026-09-28 with SymPy 1.14.0.