Display formulas for numerical surfaces #
The n = 2 specialisation of AlgebraicGeometry.Numerical.NumericalVarietyData.chi_eq_sum.
This is an optional display specialization of the dimension-general API. It contains no
foundational surface object: NumericalVarietyData 2 A N is the general variety interface at
dimension two, and the discriminant itself now lives in
Numerical/GrothendieckGroup/Discriminant.lean for
arbitrary dimension.
Main results #
chi_eq—χ(E) = r·∫td₂(X) + ∫c₁(E)·td₁(X) + ∫ch₂(E).- compatibility aliases for the dimension-general numerical discriminant.
Writing td₁(X) = −K_X/2 and ch₂(E) = (c₁² − 2c₂)/2 turns chi_eq into the classical
χ(E) = r·χ(O_X) + ½c₁(c₁ − K_X) − c₂. Those substitutions need K_X and c₂, which are
Layer B objects, so they are not asserted here.
χ(O_X) for a surface, read off the top Todd component: taking E of rank one with
vanishing higher Chern components in chi_eq leaves exactly ∫_X td₂(X).
Equations
Instances For
Riemann–Roch for surfaces.
χ(E) = rank(E) · ∫_X td₂(X) + ∫_X c₁(E)·td₁(X) + ∫_X ch₂(E).
The Bogomolov–Gieseker discriminant Δ(E) = c₁(E)² − 2·rank(E)·ch₂(E), a class in
codimension two.
Equivalently Δ(E) = 2·r·c₂(E) − (r − 1)·c₁(E)² once c₂ is available; the ch-form is
used here because c₂ is a Layer B object. Bogomolov's inequality — ∫_X Δ(E) ≥ 0 for
E slope-semistable with respect to a polarisation — is not stated at this layer: there
is no stability notion in NumericalVarietyData, and asserting it here would hide a real
theorem behind a class field.
Equations
Instances For
The discriminant lives in codimension two.
∫_X Δ(E) = ∫_X c₁(E)² − 2·rank(E)·∫_X ch₂(E): the scalar the
Bogomolov–Gieseker inequality is about.