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.
Equal mean trajectories do not determine a master-equation state
Example
On states , compare with
both with initial vector . For the law stays . For it is
Both mean trajectories equal , so both obey the same deterministic mean equation , . For every the probability vectors differ. Thus an equation for the mean alone does not solve or determine the full master-equation state.
Facts & Assumptions
Given: The finite state set , initial vector , and generators displayed in the Example.
Finite column generator: a finite column generator has nonnegative off-diagonal entries and every source column sums to zero.
Finite master equation and uniformization formula: the full probability vector is the unique solution of from its initial vector.
Verification
is a finite column generator, and the constant vector solves with the stated initial value. By [F2] it is the unique law, and its mean is .
The off-diagonal entries of are nonnegative and its columns sum to zero, so [F1] applies. Writing , its master equation is , , with initial values . Solving gives and ; direct differentiation verifies these formulas and their initial data, and [F2] makes this the unique law.
The mean under is , the same as the mean under , while has positive mass at for and has none. Thus the same mean trajectory corresponds to two different full distributions.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
10 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
- Brian Munsky and Mustafa Khammash, The Finite State Projection Algorithm for the Solution of the Chemical Master Equation (standard reference, not scraped)