Numerical Linear Algebra
where the algebra stops being the arithmetic
Concept

Kernel matrix — where it appears

A matrix whose entries are the values of a function at pairs of points. It has no zero entries and no shorter description than its entries, and its blocks between well-separated clusters of points are numerically low rank.

Named by 6 essays across 2 fields — each of them below, with the objects they name alongside it.

051015202530354010⁻¹⁷10⁻¹⁴10⁻¹¹10⁻⁸10⁻⁵10⁻²10¹singular value, in orderσ ⁄ σ₁eight digitsan independent draw per entry1 ⁄ ra cliff, and a control1/r rank at 10⁻⁸5log r rank at 10⁻⁸5noise rank at 10⁻⁸96σ₂ ⁄ σ₁0.024σ₆ ⁄ σ₁2.8·10⁻⁹the block has full rankand five useful columns

A block nobody can call sparse

A 96 × 96 block of a kernel matrix has ninety-six nonzero singular values and five that matter. It has no zero entries, it is not described by fewer numbers than it contains, and neither of the two ways this collection already knows to make a large matrix affordable applies to it.

hierarchy · off diagonal rank 0369121501122334455digits asked for, −log₁₀ εcolumns keptwhat the geometry promiseswhat the matrix costsa rank is a number of digitscolumns a decade0.55bound, a decade3.3rank at 10⁻⁸5bound at 10⁻⁸28q0.5the shape is rightand the constant is not

A rank that is a number of digits

Ask a kernel block for two digits and it costs two columns; ask for fourteen and it costs nine. The curve is a straight line at 0.55 columns a decade, and the bound the geometry gives is a straight line too — at 3.32, which is the same shape and six times the price.

hierarchy · off diagonal rank 45678903691215log₂ of the points a sidecolumns above 10⁻⁸two intervals that touchtwo that do notthe measurement that is a null resultadmissible, n = 325admissible, n = 2565touching, n = 329touching, n = 25613stored ⁄ dense at largest0.039the rank belongs to the geometryand not to the sampling

The size the rank does not notice

Sample a kernel block at 32, 64, 128 and 256 points a side and it needs five columns, five, five and five. Sample the touching block next to it at the same four sizes and it needs nine, eleven, twelve and thirteen. Same kernel, same accuracy, one number and a logarithm.

hierarchy · off diagonal rank -1012301020304050log₂ of the segment lengthcolumns above 10⁻⁸cos(κr) ⁄ r at κ = 401 ⁄ r, same pointsthe case with no answerq, held fixed0.51/r at L = 0.561/r at L = 86cos(κr)/r at L = 0.512cos(κr)/r at L = 853the geometry did not moveand the rank did

The kernel with nothing to compress

Hold the geometry fixed at q = ½, fix the wavelength, and scale the picture up by sixteen. A smooth kernel needs six columns at every scale. An oscillatory one needs twelve, sixteen, twenty-two, thirty-three, fifty-three, and there is no scale at which it stops.

hierarchy · off diagonal rank 545545545455554545545545545454555555454545545545545455554545545545rows and columns, in the order the points arrivedark: kept dense · light: two thin factors, rank printedthe strong partitionblocks112kept dense46largest rank5numbers stored2.7·10⁴‖A − A_H‖ ⁄ ‖A‖3.4·10⁻¹⁰the picture is decidedbefore a number is read

Which pairs are allowed to be small

A hierarchical representation is a partition of the matrix into blocks, and the rule that produces it reads four numbers per pair of index clusters and not one entry of the matrix. On a 256-square it yields 112 blocks, 66 of them stored as two thin factors, none of rank above five.

hierarchy · admissibility 0481216202402468101214unknowns on the separatorcolumns above 10⁻⁸the same matrix, renumberedin the separator's own orderthe ordering the geometry hands overseparator 73separator 236renumbered, largest11the block, largest11share of the square stored0.52the fill is totaland it is not independent

The fill that is not independent

Eliminate both halves of a grid and what is left on the separator is 100 per cent nonzero — the sparsity field's result, unchanged. Its off-diagonal block is 11 by 12 and six columns describe it to eight digits. Renumber the separator and the same block needs all eleven.

sparsity · fill

Named alongside it

The objects these essays reach for when they reach for this one.

Off diagonal rankNumerical rankAdmissibilityHierarchical matrixLow-rank approximationSeparable expansionSpectral decayAsymptotic analysisTruncated svdBlock methodsCluster treeCounterexample

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