Math 2.0

Linear and multilinear algebra; matrix theory Definition

Tensor algebra

Builds on Vector spaceTensor product of vector spaces

Definition

Let FF be a field and let VV be a vector space over FF. For k≥1k \ge 1, let Tk(V)=V⊗⋯⊗VT^k(V) = V \otimes \cdots \otimes V be the tensor product of kk copies of VV, and let T0(V)=FT^0(V) = F. The tensor algebra of VV is the vector space T(V)=⨁k≥0Tk(V),T(V) = \bigoplus_{k \ge 0} T^k(V), with the bilinear multiplication determined by (v1⊗⋯⊗vk)⋅(w1⊗⋯⊗wl)=v1⊗⋯⊗vk⊗w1⊗⋯⊗wl(v_1 \otimes \cdots \otimes v_k) \cdot (w_1 \otimes \cdots \otimes w_l) = v_1 \otimes \cdots \otimes v_k \otimes w_1 \otimes \cdots \otimes w_l for vi,wj∈Vv_i, w_j \in V, and with unit 1∈T0(V)1 \in T^0(V).

Remarks

T(V)T(V) is an associative unital algebra over FF, graded by the degree kk, and V=T1(V)V = T^1(V) sits inside it. Universal property: for every associative unital FF-algebra AA and every linear map f ⁣:V→Af \colon V \to A, there is exactly one unital algebra homomorphism fˉ ⁣:T(V)→A\bar f \colon T(V) \to A with fˉ(v)=f(v)\bar f(v) = f(v) for v∈Vv \in V. Example: if V=FxV = F x has dimension 11, then Tk(V)=Fx⊗kT^k(V) = F x^{\otimes k}, and x⊗k↦xkx^{\otimes k} \mapsto x^k is an isomorphism T(V)≅F[x]T(V) \cong F[x]; the check is that both products add degrees. Non-example: for V=F2V = F^2 with basis x,yx, y, the polynomial ring F[x,y]F[x, y] is not T(V)T(V), because x⊗y≠y⊗xx \otimes y \ne y \otimes x in T(V)T(V) while xy=yxxy = yx in F[x,y]F[x, y]. If VV has a basis (ei)i∈I(e_i)_{i \in I}, then T(V)T(V) is the free associative algebra on the set II. The same construction works for a module over a commutative ring.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Tensor_algebra
About this page
TagVTFQYCP1WA
URIm2://VTFQYCP1WA
Kinddefinition
WritingW0 stub
MSC15A72, 15A69, 16S10
DefinesTensor algebra
UsesVector space, Tensor product of vector spaces
Changed2 November 2026

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