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Finite-precision direct factorizations and least squares — Examples

1 · Prerequisites

2 · Summary

These computations exhibit a nonzero rounded Cholesky residual, loss of a Gram-matrix pivot under binary64 normal-equation formation, forward sensitivity in an ill-conditioned design, compensation after cancellation, one exact TwoSum recovery, and explicit subnormal and overflow range failures. The TwoSum example checks all six rounded nodes and binary64 range success, and its general binary exact-transform theorem is proved locally. Householder-dependent examples use the locally repaired stability results.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

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Subnormal and overflow branches return range failure

Example

Use binary64 and the no-subnormal success policy. Put N_min=2^-1022 and the least positive subnormal 2^-1074. Inputs N_min and -(N_min+2^-1074) are normal, but their exact sum is -2^-1074, so the only tree sum in pairwise summation returns range-failure. Also N_max+N_max overflows at the root and returns range-failure. These are policy branches, not claims that IEEE hardware lacks gradual underflow.

Facts & Assumptions

Given: binary64 normal endpoints and the no-subnormal range rule.

[F2]

Balanced pairwise summation with range-failure status: each internal sum is rounded and the first failure is returned.

Verification

1.1givenF1algebra

The exact first sum is 2^-1022-(2^-1022+2^-1074)=-2^-1074, a nonzero subnormal; [F1] therefore returns range-failure.

2.1givenF1F2algebra∎

The exact sum N_max+N_max exceeds the largest finite normal magnitude, so the root triggers the same status under [F2].

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Neumaier summation recovers a low order term after cancellation

Example

In binary64 RNE sum (1,2^-53,-1). Ordinary left-to-right summation rounds 1+2^-53 to 1 by ties-to-even, then returns zero after adding -1. Neumaier step 2 gives s_1=1, t_2=1, q_2=0, a_2=2^-53, c_2=2^-53; step 3 gives t_3=0, q_3=1, a_3=0, c_3=2^-53. The final result is 2^-53, the exact sum. The finite error identity accounts for each branch correction and the final rounding.

Facts & Assumptions

Given: binary64 round-to-nearest, ties-to-even.

[F1]

Neumaier compensated summation with range-failure status: the method branches on the larger magnitude and returns the rounded sum plus compensation.

[F2]

Kahan and Neumaier summation satisfy explicit finite data-dependent error bounds: its identity includes each executed correction and final rounding.

Verification

1.1givenF3algebra

The value 2^-53 is half an ulp at 1, so 1+2^-53 rounds to 1. Ordinary summation then returns 0.

1.2givenF1F3algebra

Neumaier step 2 selects |s_1|>=|x_2| and gives t_2=1,q_2=0,a_2=2^-53,c_2=2^-53; step 3 gives t_3=0,q_3=1,a_3=0,c_3=2^-53.

2.1step 1.2F2algebra∎

The final exact addition 0+2^-53 is 2^-53, which is the exact sum; [F2] records this correction without claiming uniform relative accuracy.

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A rounded two by two Cholesky factor and its residual

Example

In binary64 round-to-nearest, ties-to-even, let A=(11/21/21). For every nonzero real v=(v1,v2)T, vTAv=(v1+v2/2)2+3v22/4>0, so A is positive definite. The rounded recurrence gives l^11=1, l^21=1/2, p2=3/4 exactly, and l^22=fl⁡(3/4). Since 3/2 is irrational and every binary64 number is rational, l^222≠3/4. Therefore E=L^L^T−A=(000l^222−3/4)≠0. The successful factor satisfies the backward bound, but its residual is not zero.

Facts & Assumptions

Given: the real symmetric matrix and binary64 RNE arithmetic.

[F1]

Failure-aware rounded Cholesky factorization: successful factorization uses the rounded pivot and square-root recurrence.

[F3]

Operationwise real and complex floating point arithmetic with rounded square roots and fused multiply-add: positive square roots and basic operations are rounded to nearest, ties to even.

Verification

1.1givenF1F3algebra

The displayed quadratic form proves positive definiteness. The first pivot is 1, l^21=(1/2)/1=1/2, and the second pivot is 1−(1/2)2=3/4 exactly, so the procedure succeeds through the square-root step.

2.1step 1.1F2algebra∎

Every binary64 value is rational, whereas sqrt(3/4)=sqrt(3)/2 is irrational; hence l-hat_22^2!=3/4. Multiplication of the displayed factor gives exactly the stated nonzero E, to which [F2] applies.

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TwoSum recovers a rounded away low part

Example

In binary64 nearest-even arithmetic, take a=1 and b=2−53. The call to TwoSum error-free transformation succeeds and returns (s,e)=(1,2−53). It preserves s+e=a+b exactly although the leading rounded sum loses the low part.

Facts & Assumptions

Given: binary64 nearest-even arithmetic with p=53, emin⁡=−1022, emax⁡=1023, a=1 and b=2−53.

[F1]

TwoSum error-free transformation evaluates the six separately rounded operations displayed in its definition.

[F2]

TwoSum returns the exact rounding error of a floating point sum proves s+e=a+b for every successful call in a binary format of precision at least two.

[F3]

Operationwise real and complex floating point arithmetic with rounded square roots and fused multiply-add requires zero or normal exact intermediates and nearest-even rounding.

Verification

1.1givenF1F3algebra

The spacing above 1 is 2−52, so 1+2−53 is the midpoint between 1 and 1+2−52. The even-significand endpoint is 1; hence s=1. The next exact operands give z=1−1=0, v=1−0=1, w=1−1=0, and t=2−53−0=2−53. Each is representable, so each subtraction is exact.

2.1step 1.1F1F2F3algebra∎

The final exact intermediate is w+t=2−53, hence e=2−53. The first exact sum 1+2−53 and every later nonzero exact intermediate (1 or 2−53) are normal and within range; the zero intermediates are allowed by [F3]. Thus the call succeeds, its format satisfies [F2], and s+e=1+2−53=a+b exactly, also directly verified by these outputs.

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A full rank least squares problem where rounded normal equations lose the pivot

Example

In binary64 RNE take A=((1,1),(0,2^-27)). Its determinant 2^-27 is nonzero. The exact Gram matrix is A^T A=((1,1),(1,1+2^-54)). The spacing above 1 is 2^-52, so the midpoint is 1+2^-53; 1+2^-54 lies strictly below it and rounds to 1. Thus the formed Gram matrix has equal rows and is singular. Reduced QR works directly on A and avoids forming this rounded Gram matrix; the computed stability statement remains conditional on its own hypotheses.

Facts & Assumptions

Given: binary64 RNE and A=((1,1),(0,2^-27)).

[F1]

Reduced QR over the reals solves full-column-rank least squares without squaring the condition number: exact reduced QR solves full-rank least squares without forming the Gram matrix.

[F2]

Computed reduced QR least squares is backward stable for full column rank: the computed guarantee is conditional on the listed QR and solve premises.

Verification

1.1givenalgebra

The determinant is 2^-27, while direct multiplication gives (A^T A)_22=1+2^-54.

2.1step 1.1F3algebra

Since 2^-54<2^-53, the exact entry is strictly below the RNE midpoint above 1 and rounds to 1. The rounded Gram matrix has equal rows and is singular.

3.1step 1.1step 2.1F1F2∎

The exact result [F1] acts on the full-rank A without a Gram formation. The computed conclusion [F2] applies only if its separate successful-step hypotheses hold.

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An ill conditioned design with large forward sensitivity

Example

Let A=diag(1,2^-40), with condition number 2^40. For b=(1,0)^T the unique solution is x=(1,0)^T; for b-tilde=(1,2^-40)^T it is x-tilde=(1,1)^T. The relative data change is 2^-40 while the relative solution change is 1. Thus backward stability does not imply small forward error for an ill-conditioned design.

Facts & Assumptions

Given: the diagonal design and right-hand sides.

[F2]

Computed reduced QR least squares is backward stable for full column rank: its guarantee controls perturbations of data under its hypotheses.

[F3]

The condition number kappa_p(A) = ||A||_p ||A^{-1}||_p of a nonsingular linear system: κ2(A)=∥A∥2∥A−1∥2.

[F4]

The matrix norm induced by a published vector p-norm: ∥M∥2=sup⁡∥z∥2=1∥Mz∥2.

Verification

1.1givenF1algebra

Direct multiplication by A^-1=diag(1,2^40) gives x=A^-1b=(1,0)^T and x-tilde=A^-1b-tilde=(1,1)^T; uniqueness follows from [F1].

2.1step 1.1algebra

The input difference and x norm are both measured against unit vectors: ||b-tilde-b||_2/||b||_2=2^-40 and ||x-tilde-x||_2/||x||_2=1.

3.1step 1.1step 2.1F2F3F4algebra∎

For every z, ∥Az∥22=z12+2−80z22≤∥z∥22, with equality at e1, so [F4] gives ∥A∥2=1. Likewise ∥A−1z∥22=z12+280z22≤280∥z∥22, with equality at e2, hence ∥A−1∥2=240. Thus [F3] gives κ2(A)=240. The exact data calculation proves order-one forward change under a relative 2−40 right-hand-side perturbation; backward stability [F2] alone is not a forward-accuracy guarantee.

Sources