Banach tensor cross norms: complete finite-rank and extremal-norm proofs
Original text by Claude Opus 5.5 (Anthropic), September 2026; public domain (CC0). Scoped selection by GPT-6.1 Sol (OpenAI), Ultra, October 2026; original contributions CC0.
This supplement proves finite-rank separation, the injective and projective norm formulas, the cross-norm identities and their extremal bounds. Its proof inputs are the algebraic tensor universal property, finite-dimensional linear algebra, Banach completeness and Hahn–Banach. Hilbert tensor notation in the conventions is supplied by Sections 1–2 of the companion spatial supplement and is not used in the Banach cross-norm proof.
Conventions
Banach spaces are complex. E∗ is the dual of E, with ∥f∥=sup{∣f(x)∣:∥x∥≤1}, and jE:E→E∗∗ is the canonical isometry, jE(x)(f)=f(x). An operator is a bounded linear map. B(E,F) is the Banach space of operators E→F with the operator norm, B(E)=B(E,E), and a contraction is an operator of norm at most one.
E⊙F is the algebraic tensor product, spanned by the elementary tensors x⊗y. Every bilinear map b on E×F defines a unique linear map on E⊙F with x⊗y↦b(x,y). We use this universal property without comment to define linear maps on E⊙F.
Hilbert spaces are complex, and inner products are linear in the first variable. H⊗K is the Hilbert tensor product: the completion of H⊙K for the inner product ⟨ξ⊗η,ξ′⊗η′⟩=⟨ξ,ξ′⟩⟨η,η′⟩.
C∗-algebras need not have a unit. Ah is the set of self-adjoint elements of A, and C∗(S) is the C∗-subalgebra generated by a subset S. For operators on a Hilbert space, S′ is the commutant and S′′ the bicommutant. We write [x,y]=xy−yx and x∘y=xy+yx.
1. Tensors as operators of finite rank
Lemma 1.1. Let E and F be normed spaces, and u∈E⊙F.
u=∑i=1nxi⊗yi for some xi∈E and linearly independent y1,…,yn∈F, with n=0 when u=0.
If y1,…,yn are linearly independent and ∑ixi⊗yi=0, then every xi is 0.
For f∈E∗ and g∈F∗, the number ⟨u,f⊗g⟩=∑if(xi)g(yi) does not depend on the representation u=∑ixi⊗yi. Moreover u=0 if and only if ⟨u,f⊗g⟩=0 for all f∈E∗ and g∈F∗.
Proof. (1) Start with any representation of u. Choose a basis of the span of its second factors, expand each second factor in this basis, and collect terms by bilinearity.
(2) Since the yi are linearly independent, there are linear functionals g1,…,gn on their span with gj(yi)=δij. They are bounded, because the span is finite-dimensional, and the Hahn–Banach theorem extends them to elements of F∗. The linear map E⊙F→E given by x⊗y↦gj(y)x sends ∑ixi⊗yi to xj. So xj=0.
(3) The number is the value at u of the linear functional defined by the bilinear form (x,y)↦f(x)g(y), so it depends only on u. If it vanishes for all f and g, write u as in (1) and take g=gj from (2). Then f(xj)=0 for every f∈E∗, so xj=0 by the Hahn–Banach theorem, and u=0. □
Extending (3) linearly in the second variable, ⟨u,v⟩=∑i,kfk(xi)gk(yi) for v=∑kfk⊗gk∈E∗⊙F∗ is a well-defined bilinear pairing of E⊙F with E∗⊙F∗. By (3), E∗⊙F∗ separates the points of E⊙F. The pairing also separates the points of E∗⊙F∗: if ⟨x⊗y,v⟩=0 for all x,y, write v=∑kfk⊗gk with linearly independent gk. For each x the functional ∑kfk(x)gk is then zero, so every fk(x)=0, and v=0.
Proposition 1.2 (tensors as operators). Let E and F be normed spaces. For u=∑ixi⊗yi∈E⊙F define
Tu:E∗→F,Tu(f)=i∑f(xi)yi.(1.1)
Tu is a well-defined operator of finite rank, ∥Tu∥≤∑i∥xi∥∥yi∥, and g(Tuf)=⟨u,f⊗g⟩ for f∈E∗, g∈F∗. The map u↦Tu is linear and injective.
Put ut=∑iyi⊗xi∈F⊙E. The adjoint Tu∗:F∗→E∗∗ takes its values in jE(E), and Tu∗=jE∘Tut.
Proof. (1) The operator f↦f(x)y depends bilinearly on (x,y), and this gives the linear map u↦Tu. The norm bound is the triangle inequality, and the range lies in the span of the yi. If Tu=0, then ⟨u,f⊗g⟩=g(Tuf)=0 for all f,g, so u=0 by Lemma 1.1(3).
(2) For g∈F∗ and f∈E∗,
(Tu∗g)(f)=g(Tuf)=∑if(xi)g(yi)=f(∑ig(yi)xi)=jE(Tutg)(f). □
So E⊙F is a space of operators of finite rank from E∗ to F. Through u↦ut it is also a space of operators of finite rank from F∗ to E, and the adjoint of each of the two operators of u is the other one followed by jE or jF.
2. Cross norms: the injective and the projective norm
From now on E, F, G are Banach spaces.
Definition 2.1. A norm β on E⊙F is a cross norm if β(x⊗y)=∥x∥∥y∥ for all x∈E and y∈F. We write E⊗βF for the normed space (E⊙F,β) and E⊗^βF for its completion.
Definition 2.2. For u∈E⊙F put
λ(u)=sup{∣⟨u,f⊗g⟩∣:f∈E∗,g∈F∗,∥f∥≤1,∥g∥≤1},(2.1)γ(u)=inf{i=1∑n∥xi∥∥yi∥:u=i=1∑nxi⊗yi}.(2.2)
They are the injective and the projective norm. [Ryan] writes ε and π for them.
Theorem 2.3.
λ(u)=∥Tu∥ for every u∈E⊙F. So λ is a norm, and u↦Tu extends to an isometry of E⊗^λF onto the norm closure of {Tu:u∈E⊙F} in B(E∗,F).
λ≤γ, and both are cross norms.
If β is a seminorm on E⊙F with β(x⊗y)≤∥x∥∥y∥ for all x,y, then β≤γ. In particular γ is the largest cross norm.
∣⟨u,v⟩∣≤λ(u)γ(v) for u∈E⊙F and v∈E∗⊙F∗. Here γ(v) is the projective norm of v, formed with the norms of E∗ and F∗.
Proof. (1) By Proposition 1.2(1) and the Hahn–Banach theorem in the form ∥y∥=sup∥g∥≤1∣g(y)∣,
λ(u)=∥f∥≤1sup∥g∥≤1sup∣g(Tuf)∣=∥f∥≤1sup∥Tuf∥=∥Tu∥.
The operator norm is a norm on B(E∗,F), and u↦Tu is linear and injective, so λ is a norm. Since B(E∗,F) is complete, the isometry extends to the completion, with the closure of its range as image.
(2) For every representation of u and all ∥f∥,∥g∥≤1, ∣∑if(xi)g(yi)∣≤∑i∥xi∥∥yi∥. Hence λ≤γ. The function γ is a seminorm: scaling the xi of a representation of u gives γ(cu)≤∣c∣γ(u), with equality for c=0 by applying this to c−1; and joining representations of u and u′ gives γ(u+u′)≤γ(u)+γ(u′). As λ≤γ and λ is a norm, so is γ. Finally, λ(x⊗y)=supf,g∣f(x)∣∣g(y)∣=∥x∥∥y∥ by the Hahn–Banach theorem, and λ(x⊗y)≤γ(x⊗y)≤∥x∥∥y∥.
(3) For every representation, β(u)≤∑iβ(xi⊗yi)≤∑i∥xi∥∥yi∥.
(4) By (2.1) and homogeneity, ∣⟨u,f⊗g⟩∣≤λ(u)∥f∥∥g∥. Summing over a representation v=∑kfk⊗gk and taking the infimum gives the claim. □