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.
An identity dynamics leaves a noncanonical finite preparation unchanged
A two-state finite model with explicitly frozen identity dynamics; it shows that a canonical preparation rule alone supplies no relaxation dynamics and is not an empirical statement.
Example
Let with energies , joules, and fix kelvins. The separately adopted canonical law has probabilities proportional to . For the dynamical comparison, use a dimensionless model-time parameter , stipulate the identity transition map , for all , and start with the point mass .
Facts & Assumptions
Given: A two-state energy model, positive temperature, the canonical preparation rule, and the explicitly stipulated identity dynamics.
Finite statistical microstate model: the two microstates and their fixed finite energies define an admissible finite statistical model.
Canonical sampling assumption for finite and normalized statistical models: the canonical probabilities are the normalized weights ; this is an adopted preparation rule and includes no time-evolution equation.
The comparison dynamics is the deterministic identity map for every dimensionless model time , and the initial law for that comparison is .
Verification
Given: , , and the stipulated dynamics.
Put , so . The canonical law is and ; in particular it is not .
The identity map preserves the initial point mass at every model time: . Hence the time-evolved law does not converge to the canonical law, whose probability of is strictly positive. This is a counterexample to deriving equilibration from the sampling rule alone.