Derivative of \( \displaystyle - x e^{4 x} + \frac{e^{4 x}}{4} \)
Problem 2.1749 · hard
Differentiate \( \displaystyle f(x) = - x e^{4 x} + \frac{e^{4 x}}{4} \).
- \[ \frac{d}{d x} \left(- x e^{4 x} + \frac{e^{4 x}}{4}\right) \]sumStart with the derivative of the entire function.✓ Proved
- \[ = \frac{d}{d x} \left(- x e^{4 x}\right) + \frac{d}{d x} \frac{e^{4 x}}{4} \]sum constant-multiple constant-multiple productApply the sum rule. Factor out the constant 1/4. Factor out the negative sign. Apply the product rule to the first term.✓ Proved
- \[ = - x \frac{d}{d x} e^{4 x} - e^{4 x} \frac{d}{d x} x + \frac{d}{d x} \frac{e^{4 x}}{4} \]productExpand the product rule.✓ Proved
- \[ = - x \frac{d}{d x} e^{4 x} - e^{4 x} + \frac{d}{d x} \frac{e^{4 x}}{4} \]derivativeDifferentiate x.✓ Proved
- \[ = - x e^{4 x} \frac{d}{d x} 4 x - e^{4 x} + \frac{d}{d x} \frac{e^{4 x}}{4} \]chainApply the chain rule to exp(4*x).✓ Proved
- \[ = - 4 x e^{4 x} - e^{4 x} + \frac{d}{d x} \frac{e^{4 x}}{4} \]derivative algebraDifferentiate 4*x. Simplify the expression inside the parentheses.✓ Proved
- \[ = - 4 x e^{4 x} - e^{4 x} + \frac{\frac{d}{d x} e^{4 x}}{4} \]constant-multipleFactor out the constant 1/4 from the second term.✓ Proved
- \[ = - 4 x e^{4 x} + e^{4 x} \frac{d}{d x} x - e^{4 x} \]chainApply the chain rule to the second term.✓ Proved
- \[ = - 4 x e^{4 x} \]derivative algebra simplifySimplify the derivative of the second term. Distribute the negative sign. Combine like terms.✓ Proved
Answer \( - 4 x e^{4 x} \)
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. The reviewers disagree about how one step is explained; every verdict is in the receipt.
The full receipt
| Line | Status | Checked by | Detail |
|---|---|---|---|
| 1 | ✓ Proved | sympy 1.14.0 | line 1 is the problem as stated |
| 2 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 3 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 4 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 5 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 6 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 7 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 8 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 9 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 10 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 11 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 12 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 13 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 14 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| 15 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 |
| answer | ✓ Proved | sympy 1.14.0 | final line against the stated answer: simplify(a - b) reduced to 0 |
| answer, a second way | ✓ Proved | sympy 1.14.0 | SymPy differentiated f directly and got the stated answer |
Reviewers
gpt-oss:20b: passqwen3.6:27b-mlx: fail (error) — Step 5 is labeled 'product' but performs no differentiation; it merely rewrites the term by associativity. The actual application of the product rule occurs in Step 6, making Step 5 a no-op mislabeled as a differentiation rule.
Every verdict on record (4)
gpt-oss:20b: pass 2026-10-07qwen3.6:27b-mlx: fail (error) 2026-10-07 — Step 5 is labeled 'product' but performs no differentiation; it merely rewrites the term by associativity. The actual application of the product rule occurs in Step 6, making Step 5 a no-op mislabeled as a differentiation rule.gpt-oss:20b: fail (error) 2026-10-07 — Step 12 applies both the chain rule and the derivative rule in a single step, violating the rule that each step must change only one thing.qwen3.6:27b-mlx: fail (style) 2026-10-07 — Step 5 is labeled 'product' but performs no differentiation; it merely rewrites the term to prepare for the product rule, so it should be labeled 'rewrite' or 'algebra'. Step 12 applies the chain rule and constant multiple rule simultaneously, violating the one-rule-per-step constraint.
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 2026-10-07 with SymPy 1.14.0.