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

1. Tensors as operators of finite rank

Lemma 1.1. Let EE and FF be normed spaces, and u∈E⊙Fu\in E\odot F.

  1. u=∑i=1nxi⊗yiu=\sum_{i=1}^nx_i\otimes y_i for some xi∈Ex_i\in E and linearly independent y1,…,yn∈Fy_1,\ldots,y_n\in F, with n=0n=0 when u=0u=0.
  2. If y1,…,yny_1,\ldots,y_n are linearly independent and ∑ixi⊗yi=0\sum_ix_i\otimes y_i=0, then every xix_i is 00.
  3. For f∈E∗f\in E^* and g∈F∗g\in F^*, the number ⟨u,f⊗g⟩=∑if(xi)g(yi)\langle u,f\otimes g\rangle=\sum_if(x_i)g(y_i) does not depend on the representation u=∑ixi⊗yiu=\sum_ix_i\otimes y_i. Moreover u=0u=0 if and only if ⟨u,f⊗g⟩=0\langle u,f\otimes g\rangle=0 for all f∈E∗f\in E^* and g∈F∗g\in F^*.

Proof. (1) Start with any representation of uu. 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 yiy_i are linearly independent, there are linear functionals g1,…,gng_1,\ldots,g_n on their span with gj(yi)=δijg_j(y_i)=\delta_{ij}. They are bounded, because the span is finite-dimensional, and the Hahn–Banach theorem extends them to elements of F∗F^*. The linear map E⊙F→EE\odot F\to E given by x⊗y↦gj(y)xx\otimes y\mapsto g_j(y)x sends ∑ixi⊗yi\sum_ix_i\otimes y_i to xjx_j. So xj=0x_j=0.

(3) The number is the value at uu of the linear functional defined by the bilinear form (x,y)↦f(x)g(y)(x,y)\mapsto f(x)g(y), so it depends only on uu. If it vanishes for all ff and gg, write uu as in (1) and take g=gjg=g_j from (2). Then f(xj)=0f(x_j)=0 for every f∈E∗f\in E^*, so xj=0x_j=0 by the Hahn–Banach theorem, and u=0u=0. □\square

Extending (3) linearly in the second variable, ⟨u,v⟩=∑i,kfk(xi)gk(yi)\langle u,v\rangle=\sum_{i,k}f_k(x_i)g_k(y_i) for v=∑kfk⊗gk∈E∗⊙F∗v=\sum_kf_k\otimes g_k\in E^*\odot F^* is a well-defined bilinear pairing of E⊙FE\odot F with E∗⊙F∗E^*\odot F^*. By (3), E∗⊙F∗E^*\odot F^* separates the points of E⊙FE\odot F. The pairing also separates the points of E∗⊙F∗E^*\odot F^*: if ⟨x⊗y,v⟩=0\langle x\otimes y,v\rangle=0 for all x,yx,y, write v=∑kfk⊗gkv=\sum_kf_k\otimes g_k with linearly independent gkg_k. For each xx the functional ∑kfk(x)gk\sum_kf_k(x)g_k is then zero, so every fk(x)=0f_k(x)=0, and v=0v=0.

Proposition 1.2 (tensors as operators). Let EE and FF be normed spaces. For u=∑ixi⊗yi∈E⊙Fu=\sum_ix_i\otimes y_i\in E\odot F define Tu:E∗→F,Tu(f)=∑if(xi) yi.(1.1) T_u:E^*\to F,\qquad T_u(f)=\sum_if(x_i)\,y_i . \tag{1.1}

  1. TuT_u is a well-defined operator of finite rank, ∥Tu∥≤∑i∥xi∥∥yi∥\|T_u\|\le\sum_i\|x_i\|\|y_i\|, and g(Tuf)=⟨u,f⊗g⟩g(T_uf)=\langle u,f\otimes g\rangle for f∈E∗f\in E^*, g∈F∗g\in F^*. The map u↦Tuu\mapsto T_u is linear and injective.
  2. Put ut=∑iyi⊗xi∈F⊙Eu^{\mathrm t}=\sum_iy_i\otimes x_i\in F\odot E. The adjoint Tu∗:F∗→E∗∗T_u^*:F^*\to E^{**} takes its values in jE(E)j_E(E), and Tu∗=jE∘TutT_u^*=j_E\circ T_{u^{\mathrm t}}.

Proof. (1) The operator f↦f(x)yf\mapsto f(x)y depends bilinearly on (x,y)(x,y), and this gives the linear map u↦Tuu\mapsto T_u. The norm bound is the triangle inequality, and the range lies in the span of the yiy_i. If Tu=0T_u=0, then ⟨u,f⊗g⟩=g(Tuf)=0\langle u,f\otimes g\rangle=g(T_uf)=0 for all f,gf,g, so u=0u=0 by Lemma 1.1(3).

(2) For g∈F∗g\in F^* and f∈E∗f\in E^*, (Tu∗g)(f)=g(Tuf)=∑if(xi)g(yi)=f(∑ig(yi)xi)=jE(Tutg)(f)(T_u^*g)(f)=g(T_uf)=\sum_if(x_i)g(y_i)=f\big(\sum_ig(y_i)x_i\big)=j_E(T_{u^{\mathrm t}}g)(f). □\square

So E⊙FE\odot F is a space of operators of finite rank from E∗E^* to FF. Through u↦utu\mapsto u^{\mathrm t} it is also a space of operators of finite rank from F∗F^* to EE, and the adjoint of each of the two operators of uu is the other one followed by jEj_E or jFj_F.

2. Cross norms: the injective and the projective norm

From now on EE, FF, GG are Banach spaces.

Definition 2.1. A norm β\beta on E⊙FE\odot F is a cross norm if β(x⊗y)=∥x∥∥y∥\beta(x\otimes y)=\|x\|\|y\| for all x∈Ex\in E and y∈Fy\in F. We write E⊗βFE\otimes_\beta F for the normed space (E⊙F,β)(E\odot F,\beta) and E⊗^βFE\hat\otimes_\beta F for its completion.

Definition 2.2. For u∈E⊙Fu\in E\odot F put λ(u)=sup⁡{∣⟨u,f⊗g⟩∣: f∈E∗, g∈F∗, ∥f∥≤1, ∥g∥≤1},(2.1) \lambda(u)=\sup\big\{|\langle u,f\otimes g\rangle|:\ f\in E^*,\ g\in F^*,\ \|f\|\le1,\ \|g\|\le1\big\}, \tag{2.1} γ(u)=inf⁡{∑i=1n∥xi∥∥yi∥: u=∑i=1nxi⊗yi}.(2.2) \gamma(u)=\inf\Big\{\sum_{i=1}^n\|x_i\|\|y_i\|:\ u=\sum_{i=1}^nx_i\otimes y_i\Big\}. \tag{2.2} They are the injective and the projective norm. [Ryan] writes ε\varepsilon and π\pi for them.

Theorem 2.3.

  1. λ(u)=∥Tu∥\lambda(u)=\|T_u\| for every u∈E⊙Fu\in E\odot F. So λ\lambda is a norm, and u↦Tuu\mapsto T_u extends to an isometry of E⊗^λFE\hat\otimes_\lambda F onto the norm closure of {Tu:u∈E⊙F}\{T_u:u\in E\odot F\} in B(E∗,F)B(E^*,F).
  2. λ≤γ\lambda\le\gamma, and both are cross norms.
  3. If β\beta is a seminorm on E⊙FE\odot F with β(x⊗y)≤∥x∥∥y∥\beta(x\otimes y)\le\|x\|\|y\| for all x,yx,y, then β≤γ\beta\le\gamma. In particular γ\gamma is the largest cross norm.
  4. ∣⟨u,v⟩∣≤λ(u) γ(v)|\langle u,v\rangle|\le\lambda(u)\,\gamma(v) for u∈E⊙Fu\in E\odot F and v∈E∗⊙F∗v\in E^*\odot F^*. Here γ(v)\gamma(v) is the projective norm of vv, formed with the norms of E∗E^* and F∗F^*.

Proof. (1) By Proposition 1.2(1) and the Hahn–Banach theorem in the form ∥y∥=sup⁡∥g∥≤1∣g(y)∣\|y\|=\sup_{\|g\|\le1}|g(y)|, λ(u)=sup⁡∥f∥≤1 sup⁡∥g∥≤1∣g(Tuf)∣=sup⁡∥f∥≤1∥Tuf∥=∥Tu∥. \lambda(u)=\sup_{\|f\|\le1}\ \sup_{\|g\|\le1}|g(T_uf)|=\sup_{\|f\|\le1}\|T_uf\|=\|T_u\| . The operator norm is a norm on B(E∗,F)B(E^*,F), and u↦Tuu\mapsto T_u is linear and injective, so λ\lambda is a norm. Since B(E∗,F)B(E^*,F) is complete, the isometry extends to the completion, with the closure of its range as image.

(2) For every representation of uu and all ∥f∥,∥g∥≤1\|f\|,\|g\|\le1, ∣∑if(xi)g(yi)∣≤∑i∥xi∥∥yi∥|\sum_if(x_i)g(y_i)|\le\sum_i\|x_i\|\|y_i\|. Hence λ≤γ\lambda\le\gamma. The function γ\gamma is a seminorm: scaling the xix_i of a representation of uu gives γ(cu)≤∣c∣γ(u)\gamma(cu)\le|c|\gamma(u), with equality for c≠0c\ne0 by applying this to c−1c^{-1}; and joining representations of uu and u′u' gives γ(u+u′)≤γ(u)+γ(u′)\gamma(u+u')\le\gamma(u)+\gamma(u'). As λ≤γ\lambda\le\gamma and λ\lambda is a norm, so is γ\gamma. Finally, λ(x⊗y)=sup⁡f,g∣f(x)∣∣g(y)∣=∥x∥∥y∥\lambda(x\otimes y)=\sup_{f,g}|f(x)||g(y)|=\|x\|\|y\| by the Hahn–Banach theorem, and λ(x⊗y)≤γ(x⊗y)≤∥x∥∥y∥\lambda(x\otimes y)\le\gamma(x\otimes y)\le\|x\|\|y\|.

(3) For every representation, β(u)≤∑iβ(xi⊗yi)≤∑i∥xi∥∥yi∥\beta(u)\le\sum_i\beta(x_i\otimes y_i)\le\sum_i\|x_i\|\|y_i\|.

(4) By (2.1) and homogeneity, ∣⟨u,f⊗g⟩∣≤λ(u)∥f∥∥g∥|\langle u,f\otimes g\rangle|\le\lambda(u)\|f\|\|g\|. Summing over a representation v=∑kfk⊗gkv=\sum_kf_k\otimes g_k and taking the infimum gives the claim. □\square

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