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.
for every real , hence
Statement
For every real , Consequently, if and , then
Facts & Assumptions
Given: A real , a real , and a natural .
The derivative of the exponential is the exponential (The exponential function is smooth and ).
The exponential is strictly increasing (The exponential function is strictly increasing).
The exponential is positive at every real argument (The exponential is positive and satisfies ).
If a function is continuous on and differentiable on , then its endpoint difference equals its derivative at an intermediate point times (The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with ).
Natural powers are defined recursively, and preserve order on nonnegative bases (Integer powers , Monotonicity of and of ).
For all real , (The exponential addition formula ).
Proof
If , then .
If , [L5] and [L2] give for some ; [L3] gives , hence .
If , apply [L5] on : for some . Now by [L3] and [L4], so and .
The three cases prove for every real .
Apply step 2.1 to to get , then raise both sides to the natural power and use [L7] repeatedly to obtain . The case is equality, including .
Depends on
- The real exponential function and the number $e$ by a power series
- The exponential is positive and satisfies $\exp(-x)=1/\exp(x)$
- The exponential function is smooth and $(\exp)'=\exp$
- The exponential function is strictly increasing
- The exponential addition formula $\exp(x+y)=\exp(x)\exp(y)$
- 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 $f(b) - f(a) = f'(c)(b-a)$
- Integer powers $a^m$
- Monotonicity of $x \mapsto x^n$ and of $n \mapsto a^n$
Used by
- A sample-size consequence for compression schemes Corollary
- The symmetric Lovász Local Lemma under ep(d+1)≤1 Corollary
- A bounded continuous normalized function that is not of positive type Counterexample
- A Hopf--Lax solution with a forming corner from smooth data Example
- A parameter ledger for the high-girth, high-chromatic alteration proof Example
- A stable coupled model has an unstable explicit fast microstep Example
- Fixed-time error slopes for Euler, midpoint, and classical RK4 Example
- Heat and Poisson semigroups as Fourier multipliers Example
- Hilbert transform of the line Poisson kernel Example
- Too few sweeps lower the order from Gauss collocation Example
- A binomial-sum bound for compression sample sizes Lemma
- Finite geometric error bound from a one-step recurrence Lemma
- Gaussian decay gives an entire Fourier-Laplace transform and its growth bound Lemma
- Logarithmic L-r covering bound for VC classes of sets Lemma
- One-step stability of frozen-slow Euler with fast microsteps Lemma
- ℙ(α(G(n,p))≥ s)leC(n, s)(1-p)^C(s, 2)≤ nˢ exp(-pC(s, 2)) for s≤ n Lemma
- The improper integral of e^-x² over ℝ is finite and positive Lemma
- The sine integral under Countable Choice: uniform bounds and the value pi/2 Lemma
- Trace-norm continuity, growth and multiplicativity of the local determinant Lemma
- A conditional binomial error bound for Parareal Theorem
- A k-uniform hypergraph is 2-colourable when every edge meets at most d other edges and e(d+1)≤2ᵏ⁻¹ Theorem
- A square-root global error bound for projected Euler with certified projection tolerances Theorem
- Adaptive conditional failure budgets compose by a union bound Theorem
- An n-vertex graph of minimum degree δ>1 has a dominating set of size at most n(log(δ+1)+1)/(δ+1) Theorem
- Bernstein inequality for bounded independent sums Theorem
- Correctness and cost of the linear-combination sampler Theorem
- Euler–Maruyama uniform moments and interpolation increments Theorem
- Every finite family with the Erdős–Hajnal property is viral Theorem
- Exp3 expected regret under bandit feedback Theorem
- Expected generalization of nonconvex stochastic gradient training Theorem
- Finite-class realizable PAC bound Theorem
- Finite-state killed projection has an exact lost-mass certificate Theorem
- Fixed-matrix global orders and certified-action error propagation Theorem
- For all positive k,ℓ, some finite graph has girth greater than ℓ and chromatic number greater than k Theorem
- Forward Euler has first-order global error and preserves a margin tube for the regularized SPH ODE Theorem
- Hedge's second-order and static-regret bounds Theorem
- If k≥1 and n≥3k² 2ᵏ, an n-vertex tournament with property Sₖ exists Theorem
- Realizable sample complexity for finite-VC classes Theorem
- Rosenbrock–Euler has a first-order global error bound on a common tube Theorem
- Sauer–Shelah growth bound for indexed samples Theorem
…and 2 more results.
Dependency tree · two levels
46 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
- J. Matousek and J. Vondrak, The Probabilistic Method, Chapter 4 (standard reference, not scraped)