How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Basic properties of characteristic functions
Statement
Every characteristic function on satisfies , , , and is uniformly continuous on .
Facts & Assumptions
Given: The hypotheses and conventions in the statement.
Characteristic functions integrate the unit-modulus exponential. Characteristic function of a real random variable.
The integral triangle inequality applies to integrable complex functions. The modulus of an integral is bounded by the integral of the modulus.
Complex integrals are linear. The Lebesgue integral is linear on .
Euler form gives conjugation and unit modulus. , , and .
Exponential addition factors frequency increments. , and the complex exponential extends the real exponential.
Dominated pointwise convergence permits passage through the integral. Dominated convergence.
The mean value theorem bounds increments by a bound for the derivative times the interval length. The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with .
The derivatives of sine and cosine are cosine and minus sine. The derivatives of sine and cosine are cosine and minus sine.
Proof
Write with . At zero the integrand is one, so . The triangle inequality gives .
Writing the integral componentwise, . Linearity and exponential addition further give
For real , apply the mean value theorem separately to sine and cosine between and . Their derivatives have absolute value at most one by Euler's formula, so and . Thus . For each positive integer , define . This measurable sequence tends pointwise to zero and is dominated by the integrable constant , so DCT gives . Whenever , step 1.2 bounds by , for every . Given , take the least positive integer with this integral less than . Then proves uniform continuity. This uses a prescribed sequence and no choice of a sequence of counterexamples.
Depends on
- Characteristic function of a real random variable
- Dominated convergence
- The modulus of an integral is bounded by the integral of the modulus
- The Lebesgue integral is linear on $L^1(\mu)$
- $\exp(x+iy)=e^x(\cos y+i\sin y)$, $|\exp(x+iy)|=e^x$, and $e^{i\pi}+1=0$
- $\exp(z+w)=\exp z\,\exp w$, and the complex exponential extends the real exponential
- The mean value theorem, as the case $g(x) = x$ of Cauchy's: for $f$ continuous on $[a,b]$ with $a < b$ and differentiable on $(a,b)$ there is $c \in (a,b)$ with $f(b) - f(a) = f'(c)(b-a)$
- The derivatives of sine and cosine are cosine and minus sine
Used by
- Characteristic function criterion for weak convergence Corollary
- Density inversion from an integrable characteristic function Corollary
- Pointwise limit discontinuous at zero signals mass escape Counterexample
- Characteristic function of the uniform law Example
- Density inversion for a triangular characteristic function Example
- Levy continuity theorem converse Theorem
- Uniqueness of a law from its characteristic function Theorem
Dependency tree · two levels
38 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Durrett, Probability: Theory and Examples, fifth edition (standard reference, not scraped)
- Norris, Probability and Measure (standard reference, not scraped)