Alphabeta Math
PostulateStatement: AI-adaptedProof: Not applicablePipeline-generated‡ sources checked 2026-10-15
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.

Microcanonical sampling assumption

Physical scope

Adopted uniform weighting for a nonempty finite energy window or the normalized coarea law on an admitted regular compact Hamiltonian energy shell; neither rule is a consequence of dynamics or a claim about measured samples.

Postulate

For the regular-shell branch below, assume AC as required by Regular Hamiltonian shell preparation data and its coarea-measure supplier. No choice assumption is needed for the separate finite-window branch.

For a finite microstate model and a declared energy value E0 in joules and resolution δ≥0 in joules, define the admitted window ΩE0,δ:={x∈Ω:∣E(x)−E0∣≤δ}. When this set is nonempty, adopt the uniform preparation P(x)=∣ΩE0,δ∣−1 on it and zero outside. Its dimensionless Boltzmann entropy is log⁡∣ΩE0,δ∣, and its physical entropy convention is kBlog⁡∣ΩE0,δ∣ in J K−1. A zero-width window is allowed only when it contains at least one microstate.

For a continuous classical model, when the regular-band, nonempty-shell, and normalization hypotheses in Regular Hamiltonian shell preparation data hold, the microcanonical preparation is the normalized shell measure νE^ defined there. The shell preparation does not require a globally defined flow. These finite-window and regular-shell rules are adopted model preparations. They do not assert Hamiltonian ergodicity, equality with long-time averages, canonical sampling, or equilibration.

Depends on

Dependency tree · 2 levels

Sources