Alphabeta Math
AlgorithmAlgorithm: AI-adaptedProof: Not applicablePipeline-generated
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.

Finite scaled Taylor action for the matrix exponential

Definition

Inputs: A∈Mn(C) with n≥1, a vector v∈Cn, an exactly represented finite time t∈R, positive rational tolerance ε, integer budgets smax⁡≥1 and pmax⁡≥0, rational upper bounds ρA≥∥A∥2, ρt≥∣t∣, and ρv≥∥v∥2, and a provider satisfying Normwise certified matrix-vector and vector-step arithmetic.

For s≥1 define the rational Rs:=ρtρA/s, which upper-bounds ∣t∣∥A∥2/s. For rational 0≤R≤1 and integer p≥0, define

Qp(R):=Rp+1(p+1)!(1−R/(p+2)).

Outputs: a vector candidate when returned, an extended nonnegative rational error bound in Q≥0∪{+∞} (+∞ means no finite certificate was established), the number of calls to A, and one status: success, inconclusive-tail-budget, inconclusive-roundoff, or invalid-input.

Procedure:

  1. Reject invalid dimensions, nonpositive tolerance, negative bounds, or invalid budgets by returning no candidate, bound +∞, zero calls to A, and invalid-input. If v=0, t=0, or ρA=0, return v, bound 0, zero calls to A, and status success. In the last case ∥A∥2=0 forces A=0.
  2. Among pairs 1≤s≤smax⁡ and 0≤p≤pmax⁡ with Rs≤1, select one minimizing sp subject to s 3s−1Qp(Rs)ρv≤ε/2. Break ties by smaller s, then smaller p. If no pair exists, return the zero vector candidate, bound +∞, and inconclusive-tail-budget.
  3. Set δ:=t/s and w0:=v. For each substep ℓ=1,…,s, initialize z0:=wℓ−1 and a0:=wℓ−1. For j=1,…,p, call the certified provider with coefficient c=δ/j and vector zj−1 to obtain zj and a bound αℓj for ∥zj−(δ/j)Azj−1∥2. Add zj to the partial sum through the provider, obtaining aj and a bound ζℓj for ∥aj−(aj−1+zj)∥2. Set dℓ0:=0 and compute dℓj:=(Rs/j)dℓ,j−1+αℓj. Set wℓ:=ap and ϵℓ:=∑j=1p(dℓj+ζℓj); for p=0, set wℓ:=wℓ−1 and ϵℓ:=0.
  4. If any provider result lacks a sound bound, return the current candidate, bound +∞, and inconclusive-roundoff. Otherwise compute B:=s 3s−1Qp(Rs)ρv+∑ℓ=1s3s−ℓϵℓ. Return ws, bound B, and success if B≤ε; otherwise return the same candidate and bound with inconclusive-roundoff.

The pair search is finite. The recurrence makes exactly sp calls to A when it reaches step 4; the error-bound provider performs no additional A calls. An implementation may return an inconclusive status whenever an outward scalar comparison or a local error certificate cannot be established.

Well-definedness and guarantee boundary

There are at most smax⁡(pmax⁡+1) pairs in the search, and for every admissible R∈[0,1] and p≥0 the denominator 1−R/(p+2) is at least 1/2, so each Qp(R) is defined. Every matrix-vector and partial-sum loop has a finite bound. The zero branches are exact: v=0 gives the zero action, t=0 gives e0Av=v, and ρA=0 forces A=0. A failed local certificate stops with inconclusive-roundoff; failure to find a pair within the declared budgets returns inconclusive-tail-budget. Neither status asserts an error guarantee.

The separate error/work theorem on this page proves the reported bound under the stated rational input bounds and successful local provider certificates. Finite budgets need not return success; no convergence claim beyond this conditional finite certificate is made. The count sp is the exact matrix-vector call count for a completed recurrence, not a claim about wall-clock cost.

Depends on

Used by

Dependency tree · two levels

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Sources