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.
Quantum occupation fluctuations and the classical approximation boundary
A one-mode exact comparison of Bose, Fermi, and first-order classical occupations at q=1/2, with no empirical interpretation.
Example
Take one dimensionless mode with fugacity . The first-order dilute term for the mean occupation is . As an explicit comparison, define the Poisson law by for ; its mean and variance are both . The exact Bose law is geometric and the exact Fermi law is Bernoulli. This declared calculation illustrates the distinct occupation statistics and why a small-error conclusion needs a small-fugacity condition; the Poisson comparison is not asserted to follow from the linked theorem's mean and log-partition bounds.
Verification
Given: (The Axiom of Countable Choice ()), , and the exact occupation and variance formulas of Controlled dilute Bose/Fermi occupation limit and Explicit diagonal Fock domains and occupation trace.
[F1] Controlled dilute Bose/Fermi occupation limit, Statement: Bose and Fermi mode means are and , with explicit errors relative to .
[F2] Explicit diagonal Fock domains and occupation trace, Statement: the one-mode Bose and Fermi variances are and .
Substitution of gives , , while the first-order value is . Thus the Bose error is and the Fermi error magnitude is .
For the comparison law, and , so . The exact variances from [F2] are for bosons and for fermions. These are finite exact model values; since is not near zero, no small-error claim follows from this example.