Row-matrix evaluation of
ProvedNearEnemy.eval_innerPoly_rowsevaluation-mapsmatrix-rowsnear-enemypolynomial-method
Let be vectors in EuclideanSpace ℝ ι (the two rows of a projection matrix), let select a row, and let be a vector in EuclideanSpace ℝ ι. Evaluating innerPoly k v at the row-matrix gives the inner product of the selected row with :
This specializes the general evaluation lemma to the concrete two-row matrix form used for planar projections. It is applied whenever a degeneracy condition (e.g. a vanishing minor or inner product) must be read off as the zero set of an explicit nonzero polynomial in the projection entries.
Preamble
import Mathlib
import Definitions.Def_NearEnemyDefs
universe u_1
open scoped RealInnerProductSpace
open scoped Classical
open MvPolynomial
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable {ι : Type*} [Fintype ι]
open NearEnemy
Formal statement
theorem NearEnemy.eval_innerPoly_rows (p q : EuclideanSpace ℝ ι) (k : Fin 2)
(v : EuclideanSpace ℝ ι) :
eval (fun ki ↦ ![p, q] ki.1 ki.2) (innerPoly k v) = ⟪![p, q] k, v⟫ := by sorry
Source
Prior art: Lund-Sheffer-de Zeeuw, Bisector energy and few distinct distances, SoCG 2015, LIPIcs vol. 34, 537-552, DOI 10.4230/LIPIcs.SOCG.2015.537, footnote 1 on p. 538, state that E(P) = 2n(n-1) when every pair of distinct points has a distinct perpendicular bisector, with the count of trivial quadruples that proves the floor (this footnote is not in arXiv:1411.6868v1); the asymptotic floor E(P) = Omega(n^2) is in their section 3.4. The generic planar projection that is injective, keeps general position and transports distances is Erdos-Furedi-Pach-Ruzsa, The grid revisited, Discrete Math. 111 (1993), proof of Theorem 3.1. Formalized in https://github.com/mysticflounder/lean-formalizations/blob/dd46c17a2a034d7bfa0df02e7f77834d35592864/lean/LeanFormalizations/Geometry/Euclidean/NearEnemyTheorem.lean#L992-L996