Common-normalization parity obstruction (polynomial layer)
ProvedSP4GradedLaurent.common_normalization_parityLet be finite index sets, let be a permutation, and let all polynomials below be finite Laurent polynomials with integer coefficients. Write
The source data consist of a central row and paired rows . The target and correction data are , and the column targets are . Let , , and be integers.
Assume cellwise Euler zero and even-shift conjugation:
Assume the following exact identities of Laurent polynomials, with the same shift in every row and the same shift in every column:
Finally assume the target Euler normalizations and equality of the two translated adjacent-degree total profiles:
Then
This is the polynomial layer of a common-normalization obstruction: an odd total correction coefficient sum is incompatible with these identities. The polynomials may have arbitrary integer coefficients. Interpreting correction coefficients as ranks of actual differential blocks requires a separate graded-complex argument; no such rank interpretation, Floer-theoretic realization, or geometric exclusion is asserted here.
import Definitions.Def_SP4GradedLaurent set_option autoImplicit false open scoped BigOperators open SP4GradedLaurent
theorem SP4GradedLaurent.common_normalization_parity
{ι κ : Type*} [Fintype ι] [Fintype κ]
(flip : κ ≃ κ) (k : ι → κ → ℤ) (l : ι → ℤ)
(X0 : κ → GradedPolynomial) (Xp Xm : ι → κ → GradedPolynomial)
(U0 : GradedPolynomial) (Up Um Qp Qm : ι → GradedPolynomial)
(G : κ → GradedPolynomial) (lam mu : ℤ)
(hcell : ∀ i j, euler (Xp i j) = 0)
(hconj : ∀ i j, Xm i (flip j) = shift (2 * k i j) (Xp i j))
(htarget : ∀ i, Um i = shift (2 * l i) (Up i))
(hrow0 : ∑ j, X0 j = tensorV (shift lam U0))
(hrowp : ∀ i, ∑ j, Xp i j = tensorV (shift lam (Up i)) + tensorV (Qp i))
(hrowm : ∀ i, ∑ j, Xm i j = tensorV (shift lam (Um i)) + tensorV (Qm i))
(hcolumn : ∀ j, X0 j + ∑ i, Xp i j + ∑ i, Xm i j = tensorV (shift mu (G j)))
(hU : euler U0 + ∑ i, euler (Up i) + ∑ i, euler (Um i) = 1)
(hG : ∑ j, euler (G j) = 1)
(hnorm : tensorV (Finsupp.single lam 1) = tensorV (Finsupp.single mu 1)) :
lam = mu ∧ Even (∑ i, mass (Qp i)) := by sorry