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Integral of \( \displaystyle \frac{e^{2 x - 1}}{e^{2 x - 1} + 1} \)

Problem 4.658 · medium

Find \( \displaystyle \int \frac{e^{2 x - 1}}{e^{2 x - 1} + 1} \, dx \). (Omit the constant of integration.)
  1. \[ \int \frac{e^{2 x - 1}}{e^{2 x - 1} + 1}\, dx \]
    integralStart with the integral of the given function.✓ Proved
  2. \[ = \int \frac{e^{2 x}}{e \left(\frac{e^{2 x}}{e} + 1\right)}\, dx \]
    algebraRewrite the exponent using exponent laws.≈ Checked numerically
  3. \[ = \int \frac{e^{2 x}}{e^{2 x} + e}\, dx \]
    algebra algebraSimplify the fraction by multiplying numerator and denominator by exp(1). Rewrite the integrand to reveal the derivative of the denominator.✓ Proved
  4. \[ = \frac{\ln{\left(e^{2 x} + e \right)}}{2} \]
    antiderivativeIntegrate using the substitution method or logarithmic rule.✓ Proved
  5. \[ = \frac{\ln{\left(e e^{2 x - 1} + e \right)}}{2} \]
    algebraRewrite the first term inside the log to match the original form.✓ Proved
  6. \[ = \frac{\ln{\left(e \left(e^{2 x - 1} + 1\right) \right)}}{2} \]
    algebraFactor out exp(1) from the expression inside the logarithm.✓ Proved
  7. \[ = \frac{\ln{\left(e^{2 x - 1} + 1 \right)}}{2} \]
    simplifyUse log properties to simplify the expression.≈ Checked numerically
Answer \( \frac{\ln{\left(e^{2 x - 1} + 1 \right)}}{2} + C \)

✓ Nihil obstat Lines: 7 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≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left -log(exp(2*x) + E)/2 + log(exp(2*x - 1) + 1)/2; numeric agreement only, at 24 of 24 sampled points
undefined where exp(2*x - 1) + 1 = 0
undefined where exp(-1)*exp(2*x) + 1 = 0
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where exp(-1)*exp(2*x) + 1 = 0
undefined where exp(2*x) + E = 0
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where exp(2*x) + E = 0
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where exp(2*x) + E = 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≈ Checked numericallysympy 1.14.0sympy 1.14.0: simplify left log(exp(2*x) + E)/2 - log(exp(2*x - 1) + 1)/2; numeric agreement only, at 24 of 24 sampled points
log is undefined for non-positive arguments
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
log is undefined for non-positive arguments
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated the stated antiderivative back to the integrand

Reviewers

  • gpt-oss:20b: pass
  • qwen3.6:27b-mlx: pass — The solution correctly applies algebraic manipulations and the antiderivative rule for logarithmic forms. Each step changes only one aspect of the expression, and the labels accurately reflect the operations performed.
Every verdict on record (4)
  • gpt-oss:20b: pass 2026-10-08
  • qwen3.6:27b-mlx: pass 2026-10-08 — The solution correctly applies algebraic manipulations and the antiderivative rule for logarithmic forms. Each step changes only one aspect of the expression, and the labels accurately reflect the operations performed.
  • gpt-oss:20b: pass 2026-10-08
  • qwen3.6:27b-mlx: pass 2026-10-08 — The solution correctly applies algebraic manipulations to prepare for integration, identifies the antiderivative, and simplifies the result back to the original form. All steps adhere to the single-rule constraint and use valid labels from the fixed vocabulary.

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 2026-10-08 with SymPy 1.14.0.