A fixed template list computes the denoted steps on the level layout
ProvedNLogN.KFD.stepsU_fspecA fixed template list computes the denoted steps on the level layout.
The following holds (Lean statement, in the scope of module Solutions.KFDStep):
theorem NLogN.KFD.stepsU_fspec {N : ℕ} [NeZero N] (A B Cs : Shape) (P L : ℕ) (rX : Fin HS)
(hrX : 38 ≤ rX.val ∧ rX.val < 56)
(hpos : ∀ a ∈ P :: L :: hdShape A B Cs m N, 1 ≤ a) (w Bb : ℕ) (R : List Item)
(hV : zsz ((vol (P :: L :: hdShape A B Cs m N) : ℕ) : ℤ) ≤ Bb)
(hQ2 : zsz ((2 * N : ℕ) : ℤ) ≤ Bb)
{LN LQ LX LB LC : List Item} (t : IState HS) (hNQ : t.G sNQ = .int (-(N : ℤ)) :: LN)
(hQQ : t.G sQQ = .int (N : ℤ) :: LQ)
(hX : t.G rX = .int ((vol (P :: L :: A) : ℕ) : ℤ) :: LX)
(hB : t.G rVB = .int ((vol B : ℕ) : ℤ) :: LB)
(hC : t.G rVC = .int ((vol Cs : ℕ) : ℤ) :: LC) :
∀ (Ts : List (TSh m)) (xs : List ℤ), (∀ T ∈ Ts, TOK T N Bb) →
xs.length = vol (P :: L :: hdShape A B Cs m N) → Bnd w xs → t.G 0 = ints xs ++ R →
FSp (stepsU m rX Ts) t
(t.upd 0 (ints (AModel.runArr ((hdLayout A B Cs m N).cons2 P L) 0 (Ts.map (·.eval N)) xs) ++ R))
(cStepsUF rX (vol (P :: L :: hdShape A B Cs m N)) w Bb Ts)
Context. The lemma belongs to the part KFD: the fine uniform level step: stepG_fspec / stepU_fspec: the KIL4 step programs (unchanged) with fine cost
cStepGF; the data bound w and the global bound Bb are separate.
cStepGF_le: cStepGF ≤ tKF·(10^13 (V+1)(w+2) + 10^10 (Bb+2)²).
Formalization Note. This lemma belongs to the item-language (IL) layer of the integer-multiplication-kappa campaign: tape-level programs (register programs over 64 item stacks of the NLogN multitape framework, definition bundles IntMul_HvdH_M_Defs1–IntMul_HvdH_M_Defs8) that implement the data-movement primitives of the OpenAI preprint Integer multiplication below (field moves, row split/merge, shifts, the uniform Proposition 11 interchange, Lemma 12 with fine -per-element costs, Gaussian record primitives, Proposition 14 pieces) with exact list denotations from the array-model bundles IntMul_Kappa_K_Defs* and explicit cost bounds. All names refer to the definition bundles up to IntMul_Kappa_K_Defs18.
-- OpenAI-preprint / κ-improvement development (integer-multiplication-kappa), generated by skeleton subtraction.
import Definitions.Def_IntMul_Kappa_K_Defs18
set_option autoImplicit false
set_option relaxedAutoImplicit false
set_option maxHeartbeats 1000000
set_option linter.unusedSimpArgs false
set_option linter.unnecessarySeqFocus false
set_option linter.unusedVariables false
open NLogN
open IntMul RS
open NLogN.KFD
open KIL AModel AModelL12
variable {m : ℕ}
theorem NLogN.KFD.stepsU_fspec {N : ℕ} [NeZero N] (A B Cs : Shape) (P L : ℕ) (rX : Fin HS)
(hrX : 38 ≤ rX.val ∧ rX.val < 56)
(hpos : ∀ a ∈ P :: L :: hdShape A B Cs m N, 1 ≤ a) (w Bb : ℕ) (R : List Item)
(hV : zsz ((vol (P :: L :: hdShape A B Cs m N) : ℕ) : ℤ) ≤ Bb)
(hQ2 : zsz ((2 * N : ℕ) : ℤ) ≤ Bb)
{LN LQ LX LB LC : List Item} (t : IState HS) (hNQ : t.G sNQ = .int (-(N : ℤ)) :: LN)
(hQQ : t.G sQQ = .int (N : ℤ) :: LQ)
(hX : t.G rX = .int ((vol (P :: L :: A) : ℕ) : ℤ) :: LX)
(hB : t.G rVB = .int ((vol B : ℕ) : ℤ) :: LB)
(hC : t.G rVC = .int ((vol Cs : ℕ) : ℤ) :: LC) :
∀ (Ts : List (TSh m)) (xs : List ℤ), (∀ T ∈ Ts, TOK T N Bb) →
xs.length = vol (P :: L :: hdShape A B Cs m N) → Bnd w xs → t.G 0 = ints xs ++ R →
FSp (stepsU m rX Ts) t
(t.upd 0 (ints (AModel.runArr ((hdLayout A B Cs m N).cons2 P L) 0 (Ts.map (·.eval N)) xs) ++ R))
(cStepsUF rX (vol (P :: L :: hdShape A B Cs m N)) w Bb Ts) := by sorry