One-Slot Delta Collapse With Two Tensors
ProvedFunctionalInequalities.Analysis.CoordinateTensor.slot_sum_two_readablefunctional-inequalitieskls-conjecturekls-modularkls-readablelog-concave
This auxiliary lemma evaluates a two-tensor coordinate sum with delta constraints.
For coordinate tensors , a real matrix , and order and dimension , the sum
is equal to
Here . The lemma is an internal algebraic component of the energy-form derivative calculation.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis.CoordinateTensor. Shown in its original module context. Proof omitted.
private lemma slot_sum_two
(S T : (Fin r → Fin n) → ℝ) (M : Matrix (Fin n) (Fin n) ℝ) :
(∑ J : Fin r → Fin n, ∑ K : Fin r → Fin n,
S J * T K * (∑ s : Fin r,
(∏ u ∈ Finset.univ.erase s, if J u = K u then (1 : ℝ) else 0) *
(-M (J s) (K s)))) =
-inner S (actSum M T)
Module navigation
Module: Analysis/Tensor/EnergyForm.
Definition modules: Analysis/Tensor/SlotAction.
Supporting theorems: sum_mul_prod_delta_erase.
Previous: fderiv_fderiv_apply_eq_deriv_deriv_line · Next: two_slot_sum.
Source excerpt, lines 679–685 · Frozen source 408915f.
Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Tensor_EnergyForm
variable {n r : ℕ}
Formal statement
lemma FunctionalInequalities.Analysis.CoordinateTensor.slot_sum_two_readable
(S T : (Fin r → Fin n) → ℝ) (M : Matrix (Fin n) (Fin n) ℝ) :
(∑ J : Fin r → Fin n, ∑ K : Fin r → Fin n,
S J * T K * (∑ s : Fin r,
(∏ u ∈ Finset.univ.erase s, if J u = K u then (1 : ℝ) else 0) *
(-M (J s) (K s)))) =
-inner S (actSum M T) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Tensor/EnergyForm.lean#L678-L736 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Tensor.EnergyForm`, declaration `_private.FunctionalInequalities.Analysis.Tensor.EnergyForm.0.FunctionalInequalities.Analysis.CoordinateTensor.slot_sum_two`; the repository is private at upload time).