Alphabeta Math
AlgorithmAlgorithm: Literature-sourcedProof: Not applicablePipeline-generatedjudge pass (gpt-6-luna)
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.

Frozen-slow explicit Euler with fast microsteps

Definition

Let r,s≥1, let D⊆Rr+s be open, and let f:D→Rr and g:D→Rs be the designated slow and fast vector fields. The labels “slow” and “fast” are input partition labels; this definition does not assert that either field actually varies at a specified rate. The routine receives proposed state vectors x,z, a real macro step H, and a microstep count m.

Procedure.

  1. Before any division or field evaluation, check that x∈Rr, z∈Rs, H>0, m is an integer with m≥1, and (x,z)∈D. If any check fails, return invalid-input.
  2. Set h:=H/m and evaluate f(x,z) to set x+:=x+Hf(x,z).
  3. Set z0:=z.
  4. For j=0,1,…,m−1, first check whether (x,zj)∈D. If not, return domain-exit without a macro-step output. Otherwise evaluate g(x,zj) and set zj+1:=zj+hg(x,zj).
  5. If (x+,zm)∉D, return domain-exit without a macro-step output. Otherwise return success and the output state (x+,zm).

For inputs on which the procedure succeeds, write its output map as ΨH,m(x,z):=(x+,zm).

On a successful step the procedure uses exactly one evaluation of f and m evaluations of g; an invalid-input return uses no field evaluations, and a domain-exit return uses no more than these counts. The slow state is held at its initial value during every fast microstep. In a separated implementation, the slow update needs the starting fast value z0, while the fast loop needs the starting slow value x; x can be sent to the fast worker once and cached for all m microsteps, with no fast-to-slow refresh during the block. The actual communication cost depends on the implementation. The evaluation counts alone give no wall-clock saving claim, especially when the fast block accounts for nearly all right-hand-side work.

Used by

Dependency tree · 0 levels

Nothing. This result depends on no other item in the library.

Sources