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TheoremStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedprecheck passaudited 2026-08-29
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Right-hand-side perturbations in Ax = b are amplified by the condition number

Statement

Let n1, let pQ with p1, let AGLn(R), let b,δbRn with b0, let x=A1b, and let δxRn satisfy A(x+δx)=b+δb. Then

δxpxp    κp(A)δbpbp.

In words: the relative perturbation of the solution is at most the condition number κp(A) of The condition number kappa_p(A) = ||A||_p ||A^{-1}||_p of a nonsingular linear system times the relative perturbation of the right-hand side.

Facts & Assumptions

Given: An invertible matrix AGLn(R) with n1, vectors b,δbRn with b0, x=A1b and δx=A1δb.

[L2]

Compatibility of the induced norm: AypApyp for every y (Induced matrix norms are compatible with matrix-vector multiplication, submultiplicative, and satisfy ||I|| = 1).

[L3]

κp(A)=ApA1p (The condition number kappa_p(A) = ||A||_p ||A^{-1}||_p of a nonsingular linear system).

Proof

technique · direct
1.1

Subtracting the two equations gives Aδx=A(x+δx)Ax=(b+δb)b=δb, and multiplying on the left by A1 with [L1] gives δx=A1δb.

givenL1algebra
1.2

Since b=Ax, [L2] gives bp=AxpApxp, and b0 forces bp>0 and xp>0, so 1/xpAp/bp.

givenL2algebra
2.1

By [L2] applied to A1 at the vector δb, step 1.1 gives δxp=A1δbpA1pδbp.

step 1.1L2algebra
3.1

Multiplying the bound of step 2.1 by the bound of step 1.2 gives δxp/xpA1pApδbp/bp, and [L3] identifies the coefficient product as κp(A), which is the stated bound.

step 2.1step 1.2L3algebra
4.1

Step 3.1 proves the stated bound.

step 3.1

Remarks

  • The bound is sharp at p=2. The constant κ2(A) is optimal, but the two equalities in the proof are attained on different singular directions: choose x along a right singular vector for the largest singular value of A, so b=Ax has norm σmaxx2, and choose δb along a left singular vector for the smallest singular value, so A1δb2=σmin1δb2. Then the bound is attained with coefficient σmax/σmin=κ2(A).

Depends on

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Sources