§3.1, p. 15 — ρ(g)x(u) = x(g⁻¹u) is a linear representation: ρ(g)(ρ(h)x) = ρ(gh)x
ProvedGeomDL.Blueprint.exists_representation_actgeometric-deep-learninggroup-actionp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-bookp2o-v1representation-theory
Let a group act on a domain . There is a real linear representation of on the space of real signals , that is, a group homomorphism from into the linear maps of , whose operators are the action (3):
for all , signals and points .
This is the book's passage from group actions on the domain to group representations on signal spaces.
Formalization Note The representation is Mathlib's Representation ℝ G (Ω → ℝ), a monoid homomorphism into the linear endomorphisms; may be infinite, in which case is a linear operator rather than a matrix, as the book's side-note on p. 15 says.
Preamble
import Mathlib import Definitions.Def_GeomDL_Blueprint_Defs
Formal statement
namespace GeomDL.Blueprint
/-- Bronstein et al., §3.1, p. 15: "Written in the language of group representations, the action
of G on signals x ∈ X(Ω) is defined as ρ(g)x(u) = x(g⁻¹u). We again verify that
(ρ(g)(ρ(h)x))(u) = (ρ(gh)x)(u)." There is a real linear representation `ρ` of `G` on `Ω → ℝ`
(a monoid hom `G →* ((Ω → ℝ) →ₗ[ℝ] (Ω → ℝ))`) whose operators are the action (3), and
`ρ(g)(ρ(h)x) = ρ(gh)x`. -/
theorem exists_representation_act {G Ω : Type*} [Group G] [MulAction G Ω] :
∃ ρ : Representation ℝ G (Ω → ℝ),
(∀ (g : G) (x : Ω → ℝ) (u : Ω), ρ g x u = x (g⁻¹ • u)) ∧
(∀ (g h : G) (x : Ω → ℝ), ρ g (ρ h x) = ρ (g * h) x) := by sorry
end GeomDL.Blueprint
Source
Bronstein et al., Geometric Deep Learning (arXiv:2104.13478v2), §3.1, p. 15, "Written in the language of group representations ..."
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.