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.
Normalized shifted character observables
Definition
Fix . For a partition of Shifted character observables and profile moments write , where is the multiplicity of the part . For with define the normalized observable For declare , consistently with there. Since , the definition can be written in the equivalent localized form which is the concrete evaluation of the source's localization on each ; the equality uses , a positive number for , so the square roots are ordinary positive real roots. In particular, for a single part , , one has , the observable of Joint convergence in distribution and the normalized cycle-character observables.
Each is a real function on the finite set , hence a random variable on (The Plancherel measure on the partitions of ), and for every the expectation of Plancherel expectations of the shifted character observables gives so the expectation vanishes whenever and , and equals for ; in every case it is uniformly in . Moreover for every , : by For a complex character, , is a class function, and with equality exactly at scalars every irreducible character satisfies , so , and dividing by gives the displayed bound. This normalization is the one used in Hermite leading terms for normalized shifted characters and Kerov's central limit theorem for normalized cycle characters. No choice principle is used.
Depends on
- Joint convergence in distribution and the normalized cycle-character observables
- Shifted character observables $p_\rho^\#$ and profile moments $\tilde p_k$
- The shifted character observables form a basis of $A$, with the Kerov weight filtration
- Plancherel expectations of the shifted character observables
- For a complex character, $\chi(1)=\dim V$, $\chi$ is a class function, and $|\chi(g)|\le\chi(1)$ with equality exactly at scalars
- The Plancherel measure on the partitions of $n$
Used by
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