Paper VIII visual guide · Visual 9 of 32 · CLOSED LOW-RANK PRODUCT ALGEBRA

The cross term has somewhere to go

Traditional pp. 16, 17 / Theorem 5.1, Corollary 5.2.

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Let \(A=D_A+u_av_a^T\) be the running operator. Take \(D_B={\operatorname{diag}}(1,2,3,4,5,6)\), \(u_b=(1,0,1,0,1,0)^T\), and \(v_b=(0,1,0,1,0,1)^T\). Define \(B=D_B+u_bv_b^T\).

\[ U_C=[D_Au_b+u_a(v_a^Tu_b)\ \ u_a],\qquad V_C=[v_b\ \ D_B^Tv_a]. \]
Every term of a factored operator product
Original drawing. Read the description below; expand the labels and data for selectable text.

Reading the drawing

The blocks and thin factors show the local product and all correction terms. Keeping the factors avoids materializing a dense product but does not remove cross interactions.

Drawing labels and data 30 labels

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  • \(U_C\)
Drawing grid 1 · rows top to bottom, columns left to right
Row / columnColumn 1Column 2
Row 1\(6\)\(1\)
Row 2\(4\)\(1\)
Row 3\(6\)\(1\)
Row 4\(4\)\(1\)
Row 5\(6\)\(1\)
Row 6\(4\)\(1\)
  • \(V_C\)
Drawing grid 2 · rows top to bottom, columns left to right
Row / columnColumn 1Column 2
Row 1\(0\)\(1\)
Row 2\(1\)\(2\)
Row 3\(0\)\(3\)
Row 4\(1\)\(4\)
Row 5\(0\)\(5\)
Row 6\(1\)\(6\)
  • \(AB=D_AD_B+U_CV_C^T\)
  • \(U_A(V_A^TU_B)V_B^T\)
  • must be retained

Two input rank-one corrections produce at most rank two, not three.

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Why there are only two columns

Expanding \(AB\) gives three correction terms, but two share the right factor \(v_b^T\):

\[ D_Au_bv_b^T+u_a(v_a^Tu_b)v_b^T =\bigl(D_Au_b+u_a(v_a^Tu_b)\bigr)v_b^T. \]

The remaining term is \(u_av_a^TD_B\). Thus \(AB=D_AD_B+U_CV_C^T\) with at most two correction directions. Counting the three expanded summands as independent ranks would overestimate this representation.

The scalar \(v_a^Tu_b\) is three. Removing the quadratic term would therefore remove \(3u_av_b^T\), which is nonzero. The checker compares the complete product to the factor construction and rejects a calculation that omits this contribution.

Before and after recompression

A rank bound on stored factors is not always the actual matrix rank. Repeated products may introduce dependent columns. Recompression can remove those dependencies exactly, or remove small singular directions approximately under an explicit error budget.

Read this as

Closure of a representation class is an algebraic statement about all product terms. It is not permission to drop an interaction merely because it is second order in the factors.

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