PureTensor
pure tensor noun, mathematics
Let V and W be vector spaces over a field K.
V,W vector spaces over K The tensor product V ⊗ W is a vector space equipped with a bilinear map that is universal: for every vector space U over K, every bilinear map V × W → U factors uniquely through it.
⊗:V×W⟶V⊗W,(v,w)⟼v⊗w ∀U a vector space over K,∀β:V×W→U bilinear∃!β~:V⊗W→U linear with β=β~∘⊗ Bilinearity means the product distributes over addition in each slot and scalars pass through:
(v1+v2)⊗w=v1⊗w+v2⊗w,v⊗(w1+w2)=v⊗w1+v⊗w2 (λv)⊗w=v⊗(λw)=λ(v⊗w),λ∈K Definition. A tensor t ∈ V ⊗ W is pure (also called simple, elementary, or decomposable) if it is the product of a single vector from each factor. The zero tensor is pure, since 0 = 0 ⊗ w.
t=v⊗wfor some v∈V,w∈W Every tensor is a finite sum of pure tensors. The least number of terms needed is its tensor rank (the zero tensor is the empty sum, of rank 0), and the nonzero pure tensors are exactly the tensors of rank one.
t=i=1∑rvi⊗wi,rank(t)=min{r≥0:t=i=1∑rvi⊗wi} t=0:t pure⟺rank(t)=1 In bases (eᵢ) of V and (fⱼ) of W the products eᵢ ⊗ fⱼ form a basis of V ⊗ W. A pure tensor has an outer-product coefficient array, and a tensor is pure exactly when its coefficient array has matrix rank at most one.
v=i∑viei,w=j∑wjfj,v⊗w=i,j∑viwjei⊗fj t=i,j∑Tijei⊗fj is pure⟺rank[(Tij)i,j]≤1 Not every tensor need be pure. With e₁, e₂ linearly independent in V and f₁, f₂ linearly independent in W, the following tensor has rank two:
e1⊗f1+e2⊗f2 is not pure With more factors the definition is the same: for vector spaces V₁, …, Vₙ over K, a pure tensor in V₁ ⊗ ⋯ ⊗ Vₙ is one of the form
v1⊗v2⊗⋯⊗vn∈V1⊗V2⊗⋯⊗Vn,vk∈Vk