Tensor products of subspaces intersect factorwise:
ProvedQLLL.TensorProduct.range_mapIncl_inf_range_mapInclLet be a field and let be vector spaces over . For subspaces and write for the subspace of spanned by the pure tensors with , . In Lean this subspace is Mathlib's LinearMap.range (TensorProduct.mapIncl A B), the image of the map induced by the two inclusions. For subspaces and ,
This is the linear-algebra fact behind the tensor-product computation in Lemma 11 of Ambainis, Kempe and Sattath, where constraints acting on disjoint qubits are shown to be mutually R-independent. It is the intersection counterpart of the standard identity for sums of tensor products of subspaces, and is a candidate for Mathlib.
Formalization Note No finite-dimensionality is assumed. On the platform the name carries a QLLL. prefix so that it cannot clash with Mathlib if an equivalent lemma is added there later.
import Mathlib
open TensorProduct LinearMap Function
variable {K V W : Type*} [Field K]
[AddCommGroup V] [Module K V] [AddCommGroup W] [Module K W]
open _root_.TensorProduct
variable (A A' : Submodule K V) (B B' : Submodule K W)theorem QLLL.TensorProduct.range_mapIncl_inf_range_mapIncl :
LinearMap.range (TensorProduct.mapIncl A B)
⊓ LinearMap.range (TensorProduct.mapIncl A' B')
= LinearMap.range (TensorProduct.mapIncl (A ⊓ A') (B ⊓ B')) := by sorry