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Filtered γ₂ factorization norm for query mismatch masks

Definition

Let D⊆{0,1}N be a nonempty finite domain with N≥1, and let Δ={Δi}i=1N be its input-mismatch masks from Input-mismatch masks and entrywise filtering. For any complex matrix A indexed by D×D, define

γ2(A∣Δ):=inf⁡max⁡ ⁣{max⁡x∈D∑i∥ux,i∥2, max⁡y∈D∑i∥vy,i∥2},

where the infimum is over finite-dimensional complex inner-product spaces and vector families satisfying Axy=∑i(Δi)xy⟨ux,i∣vy,i⟩D(x,y∈D). Set the value to +∞ if no such families exist. Every feasible family may be taken in dimension at most 2∣D∣ for each i.

Facts & Assumptions

Given: A finite matrix A and the mismatch masks Δ on the same nonempty finite Boolean input set D.

[F1]

Input-mismatch masks and entrywise filtering: Δ_i(x,y)=1 exactly when x_i≠y_i; J−F vanishes on the diagonal and on equal-output pairs.

[F2]

Real and complex inner product spaces, with the inner product linear in the first argument: finite real or complex vector spaces have a positive-definite inner product.

[F3]

Dirac Notation Conversion: the Dirac pairing is linear in the ket (second argument) and conjugate-linear in the bra (first argument).

Proof

1.1givenF1F2F3construct

For each i, encode two finite vector families u_{x,i},v_{y,i} in a common finite-dimensional complex inner-product space. Their filtered factorization represents A exactly when A_{xy}=Σ_i(Δ_i){xy}⟨u{x,i}|v_{y,i}⟩_D for every ordered pair (x,y). The Dirac convention [F3] makes this expression conjugate-linear in each u factor and linear in each v factor.

2.1givenF1F2F3step 1.1construct

The cost of a representation is max{max_xΣ_i||u_{x,i}||²,max_yΣ_i||v_{y,i}||²}; take the infimum over all finite-dimensional representations. If A_{xx}≠0 for some x, all Δ_i(x,x)=0 and no representation exists. If A has zero diagonal, each off-diagonal pair differs in some coordinate; assigning its entry to the first differing mask and writing A(i) for each resulting matrix, take ux,i=(Axy(i)‾)y∈D and vy,i=ey in C∣D∣. Then ⟨ux,i∣vy,i⟩D=Axy(i), so this is a feasible representation.

3.1givenF2step 1.1step 2.1∎

Thus the value is +∞ exactly when the diagonal support obstruction occurs, and otherwise the infimum ranges over a nonempty finite-dimensional class with a finite nonnegative cost. For any feasible family, restricting the ambient space for each i to the span of its 2|D| vectors preserves all inner products and norms and gives dimension at most 2|D|. Nonemptiness of D ensures that both maxima in the cost are defined.

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