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Eq. (38), corrected: the self-scaled restart matrix applied to a vector

Proved
ShannoCG.SCONB.scaledRestart_mulVec

by mikedeng1 · Sep 29, 2026 · Mathlib 0df444a (Lean v4.33.1)

conjugate-gradientp2o-batch-p200bp2o-gran-per-chapterp2o-plan-paperp2o-v1quasi-newton

Let pt,yt∈Rnp_t, y_t \in \mathbb R^npt​,yt​∈Rn with pt′yt≠0p_t' y_t \ne 0pt′​yt​=0, let γt=pt′yt/yt′yt\gamma_t = p_t'y_t / y_t'y_tγt​=pt′​yt​/yt′​yt​ and let H^k\hat H_kH^k​ be the self-scaled restart matrix (37). Then for every g∈Rng \in \mathbb R^ng∈Rn

H^kg=pt′ytyt′yt g−pt′gyt′yt yt+(2 pt′gpt′yt−yt′gyt′yt)pt.\hat H_k g = \frac{p_t' y_t}{y_t' y_t}\, g - \frac{p_t' g}{y_t' y_t}\, y_t + \left(2\,\frac{p_t' g}{p_t' y_t} - \frac{y_t' g}{y_t' y_t}\right) p_t.H^k​g=yt′​yt​pt′​yt​​g−yt′​yt​pt′​g​yt​+(2pt′​yt​pt′​g​−yt′​yt​yt′​g​)pt​.

The paper prints this identity for g=gk+1g = g_{k+1}g=gk+1​ as (38) with coefficient pt′gk+1pt′yt−yt′gk+1yt′yt\frac{p_t'g_{k+1}}{p_t'y_t} - \frac{y_t'g_{k+1}}{y_t'y_t}pt′​yt​pt′​gk+1​​−yt′​yt​yt′​gk+1​​ on ptp_tpt​, without the factor 222. Expanding (37) gives the factor 222, as in the paper's own (39), which is this identity with g=ykg = y_kg=yk​. The printed and corrected versions agree when pt′gk+1=0p_t'g_{k+1} = 0pt′​gk+1​=0, the only case the paper uses.

Formalization Note The corrected identity is stated for an arbitrary vector ggg. The hypothesis pt′yt≠0p_t'y_t \ne 0pt′​yt​=0 is needed: without it Lean's total division makes the two sides differ.

Preamble
import Mathlib
import Definitions.Def_ShannoCG_SCONB_gammaScale
import Definitions.Def_ShannoCG_SCONB_scaledRestart

open Matrix
Formal statement
namespace ShannoCG.SCONB

/-- Shanno, *Conjugate Gradient Methods with Inexact Searches*, Math. Oper. Res. 3(3) (1978), §IV, p. 250 (PDF 7), eq. (38), **corrected**: for the self-scaled restart matrix (37),
`Ĥ_k g = (p_t'y_t / y_t'y_t) g − (p_t'g / y_t'y_t) y_t + (2 p_t'g / p_t'y_t − y_t'g / y_t'y_t) p_t`.

The paper prints the coefficient of `p_t` as `p_t'g_{k+1}/p_t'y_t − y_t'g_{k+1}/y_t'y_t`, without the
factor `2`; expanding (37) gives the `2`, exactly as in the paper's own (39) (which is this identity
with `g = y_k`). The two versions agree when `p_t'g_{k+1} = 0`, the only case the paper uses (42).

**Formalization Note.** Stated for an arbitrary vector `g` (the paper's `g_{k+1}`; with `g = y_k` it is
(39)). The hypothesis `p_t ⬝ᵥ y_t ≠ 0` is needed: when it fails, Lean's total division makes the
two sides differ. -/
theorem scaledRestart_mulVec {n : ℕ} (pt yt g : Fin n → ℝ) (hpy : pt ⬝ᵥ yt ≠ 0) :
    scaledRestart pt yt *ᵥ g =
      gammaScale pt yt • g - ((pt ⬝ᵥ g) / (yt ⬝ᵥ yt)) • yt
        + (2 * ((pt ⬝ᵥ g) / (pt ⬝ᵥ yt)) - (yt ⬝ᵥ g) / (yt ⬝ᵥ yt)) • pt := by sorry

end ShannoCG.SCONB
Source
Shanno, Conjugate Gradient Methods with Inexact Searches, Math. Oper. Res. 3(3) (1978) 244–256, DOI 10.1287/moor.3.3.244, p. 250 (PDF p. 7), §IV, eq. (38) (corrected: factor 2 on the p_t'g_{k+1}/p_t'y_t term, as in eq. (39))
Human review
  • Endorsed by Shuze Chen · Oct 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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