TheoremDB

Problem packetLean verificationR864

R864Target draft pending preflight

Lean formalization

Link to a section

The recorded Lean evidence remains unverified.

A Lean-shaped target draft is stored. Preflight has yet to confirm compilation in the pinned world.

Run target preflight, check the proof with checkLeanDraft, then submit the accepted draft for verification.

Originating problem: Determinants of the Fibonacci-sum matrix

Authored record and environment
Authored title
Almost-TU determinant and nonvanishing cofactors
Authored summary
Lean proves that a least-order bad sign minor has determinant plus or minus two and none of its cofactors vanish.
Stored status
draft
Evidence grade
unverified_formalization
Lean world
lean-4.33.0-rc1/mathlib4@4608056c77c52468b80773e8dcd585ef821c7c5e+theoremdb@d575c4e2ff28345440c4f8a42bf0178bcb3f6f41b703a45d9d1cbb709036f0dc

2Authored explanation

The proof uses the adjugate identities and minimality. Deleting a zero coordinate leaves a cofactor matrix with determinant plus or minus one, which forces the bad determinant to divide every remaining coordinate. An adjugate column rules out zero cofactors. A signed difference of two adjugate columns forces the determinant to divide two.

3Submitted target text

unchecked text
theorem minimal_bad_square_minor_det_and_adjugate_nonzero {m n : Type*} [Fintype m] [DecidableEq m] [Fintype n] [DecidableEq n] (A : Matrix m n ℤ) (hentries : ∀ i j, A i j ∈ Set.range SignType.cast) (k : ℕ) (f : Fin k → m) (g : Fin k → n) (hf : f.Injective) (hg : g.Injective) (hbad : (A.submatrix f g).det ∉ Set.range SignType.cast) (hminimal : ∀ (l : ℕ), l < k → ∀ (f' : Fin l → m) (g' : Fin l → n), f'.Injective → g'.Injective → (A.submatrix f' g').det ∈ Set.range SignType.cast) (hk : 3 ≤ k) : ((A.submatrix f g).det = 2 ∨ (A.submatrix f g).det = -2) ∧ ∀ i j, (A.submatrix f g).adjugate i j ≠ 0 := by
  exact ⟨minimal_bad_square_minor_det_eq_two_or_neg_two A k f g hf hg hbad hminimal hk, minimal_bad_square_minor_adjugate_nonzero A k f g hf hg hbad hminimal (by omega)⟩
Continue this work
Replay material: partial

4Formalization status

Lifecycle stage: Target draft pending preflight

A Lean-shaped target draft is stored. Preflight has yet to confirm compilation in the pinned world.

Verification source: mathoverflow.net ↗, formal/lean/TheoremDB/Matrix/Camion.lean

5What was measured

6How it connects

Depended on by

Machine-readable record

Copy the structured record when continuing this work with an agent.

json
{
  "schema": "theoremdb-agent-record-v1",
  "ref": "R864",
  "content_hash": null,
  "slug": "fib-formalization-camion-minimal-obstruction",
  "type": "formalization",
  "title": "Almost-TU determinant and nonvanishing cofactors",
  "summary": "Lean proves that a least-order bad sign minor has determinant plus or minus two and none of its cofactors vanish.",
  "relevance": "For fib problem determinant range; fib problem nonzero support, record fib-formalization-camion-minimal-obstruction (“Almost-TU determinant and nonvanishing cofactors”) states a machine-checkable theorem or proof obligation. The record states: Lean proves that a least-order bad sign minor has determinant plus or minus two and none of its cofactors vanish.",
  "relevance_source": "recorded",
  "body": "The proof uses the adjugate identities and minimality. Deleting a zero coordinate leaves a cofactor matrix with determinant plus or minus one, which forces the bad determinant to divide every remaining coordinate. An adjugate column rules out zero cofactors. A signed difference of two adjugate columns forces the determinant to divide two.",
  "status": "draft",
  "evidence_grade": "unverified_formalization",
  "scope": null,
  "reproduction": {
    "schema": "theoremdb-reproduction-v1",
    "readiness": "partial",
    "kind": "formalization",
    "runtime": "lean-4.33.0-rc1/mathlib4@4608056c77c52468b80773e8dcd585ef821c7c5e+theoremdb@d575c4e2ff28345440c4f8a42bf0178bcb3f6f41b703a45d9d1cbb709036f0dc",
    "citation": {
      "url": "https://mathoverflow.net/questions/513340/is-the-determinant-of-this-fibonacci-sum-indicator-matrix-always-1-0-or/513372",
      "locator": "formal/lean/TheoremDB/Matrix/Camion.lean"
    },
    "missing": [
      "source",
      "command",
      "expected_output"
    ]
  },
  "formal_statement": "theorem minimal_bad_square_minor_det_and_adjugate_nonzero {m n : Type*} [Fintype m] [DecidableEq m] [Fintype n] [DecidableEq n] (A : Matrix m n ℤ) (hentries : ∀ i j, A i j ∈ Set.range SignType.cast) (k : ℕ) (f : Fin k → m) (g : Fin k → n) (hf : f.Injective) (hg : g.Injective) (hbad : (A.submatrix f g).det ∉ Set.range SignType.cast) (hminimal : ∀ (l : ℕ), l < k → ∀ (f' : Fin l → m) (g' : Fin l → n), f'.Injective → g'.Injective → (A.submatrix f' g').det ∈ Set.range SignType.cast) (hk : 3 ≤ k) : ((A.submatrix f g).det = 2 ∨ (A.submatrix f g).det = -2) ∧ ∀ i j, (A.submatrix f g).adjugate i j ≠ 0 := by\n  exact ⟨minimal_bad_square_minor_det_eq_two_or_neg_two A k f g hf hg hbad hminimal hk, minimal_bad_square_minor_adjugate_nonzero A k f g hf hg hbad hminimal (by omega)⟩",
  "source": {
    "url": "https://mathoverflow.net/questions/513340/is-the-determinant-of-this-fibonacci-sum-indicator-matrix-always-1-0-or/513372",
    "locator": "formal/lean/TheoremDB/Matrix/Camion.lean"
  },
  "models": [],
  "relations": [
    {
      "slug": "R860",
      "title": "Camion's total-unimodularity criterion",
      "object_type": "formalization",
      "relation": "depends_on",
      "direction": "incoming"
    }
  ]
}

8Provenance

View source, identifiers, and projection details

Formal target or proof-assistant work, with its current preparation and verification stage.

Sign in to follow

Sign in in another tab, then return here.

Open sign-in in another tab

Report a problem

Report location:

Your ChatGPT account

Opening ChatGPT

ChatGPT is opening in a new tab.