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Fixed points, local Newton behavior, and failure boundaries

Example

The examples use exact arithmetic. The first is a fixed-point iteration on the complete metric space R with distance d(u,v)=∣u−v∣. The remaining examples concern the square residual F(x)=x2−2 or the double-root residual H(x)=(x−1)2.

Facts & Assumptions

Given: The fixed-point algorithm and the exact-Jacobian finite-budget Newton algorithm; the cited Banach and local Newton results; and the positive square root r=2.

[F1]

Fixed-point iteration with a residual stop and finite budget: the map G:X→X is iterated from x0; at each iterate the procedure checks d(G(xk),xk)≤ε before the finite update-budget status.

[F3]

A contraction of a nonempty complete metric space into itself has exactly one fixed point, the limit of the iterates from any starting point: a contraction of a nonempty complete metric space into itself has one fixed point, and its iterates from every starting point converge to it.

[F6]

Newton correction for a square vector residual: an invertible linear map and residual have a unique correction solving As=−r; a noninvertible map returns the singular-jacobian status.

[F7]

Finite-budget Newton for a square vector residual: an exact-Jacobian update applies the correction and sets xk+1=xk+sk when the trial is in U.

[F8]

Updated-Jacobian Newton has local quadratic convergence at a simple root: if a simple root has a Lipschitz Jacobian and a uniform local inverse bound, sufficiently close exact Newton iterates satisfy a quadratic error estimate and remain local.

[F9]

Newton maps are uniform contractions near a point with invertible derivative: for a fixed B=DF(a)−1, the map Ty(x)=x+B(y−F(x)) is a contraction on a small ball about a; this is a fixed-inverse map.

[F10]

Square roots exist: a unique a≥0 with (a)2=a; the positives are {x2:x≠0}: the positive square root r=2 exists uniquely and satisfies r>0 and r2=2.

[F11]

Metric space: d(x,y)=0 iff x=y, symmetry, and the triangle inequality; pseudometric and ultrametric: a metric is a real-valued function satisfying separation, symmetry, and the triangle inequality.

[F12]

Squaring is monotone on the nonnegatives: squaring is strictly increasing on nonnegative reals.

Verification

Given: G(x)=(x+1)/2 on R; F(x)=x2−2 with root r=2; and H(x)=(x−1)2 with root 1.

1.1givenF2F3F11algebra

The distance d(u,v)=∣u−v∣ is a metric by [F11], and R with it is complete by [F2]. This metric space is nonempty because 0∈R, as R is a field by [F11]. For all u,v∈R, ∣G(u)−G(v)∣=12∣u−v∣, so G is a contraction with factor q=1/2. Its fixed-point equation gives x=1, and [F3] gives convergence of the iterates from every x0.

1.2givenF1F4F5algebrainduction

The recurrence xk+1=(xk+1)/2 gives xk=1−2−k(1−x0) by induction. Hence d(G(xk),xk)=2−(k+1)∣1−x0∣, which tends to zero by [F5]; the finite-budget algorithm therefore meets any ε>0 if allowed enough updates. For ε=0 and x0≠1, no finite iterate meets the test, so a finite budget returns iteration-budget-exhausted. Also [F4] gives ∣xk−1∣≤2−k∣x1−x0∣/(1−1/2)=2−k∣1−x0∣, agreeing with the exact formula.

1.3givenF6F7F10algebra

For x>0, [F6] solves 2xs=−(x2−2), so the exact Newton update in [F7] is x+=(x2+2)/(2x). Direct subtraction using [F10] gives x+−r=(x−r)2/(2x). If ∣x−r∣≤r/2, then x≥r/2 and ∣x+−r∣≤∣x−r∣2/r≤∣x−r∣/2. Thus the ball of radius r/2 is invariant and the error decreases at least linearly by a factor 1/2, with the sharper quadratic bound ∣e+∣≤∣e∣2/r.

1.4givenF6F7F9algebra

At a=1, F′(1)=2 and the fixed-inverse map from [F9] with y=0 is T0(x)=x−12(x2−2). Starting at 1, it gives T0(1)=3/2 and T0(3/2)=11/8. Updated-Jacobian Newton uses the [F6] correction at x=3/2, where F′(3/2)=3, and gives x2=17/12. Since 11/8≠17/12, the fixed-inverse and updated-Jacobian maps differ; [F9] does not itself assert a Newton convergence theorem.

2.1step 1.3F5F10F12algebra

The start x0=3/2 lies in the radius-r/2 ball of step 1.3 because 1<r<3, which follows from r2=2 and [F12]. Iteration gives ∣xk−r∣≤2−k∣x0−r∣→0 by [F5]. Also ∣F(xk)∣=∣xk−r∣ ∣xk+r∣; since ∣xk−r∣≤r/2, we have 0<xk≤3r/2 and hence ∣xk+r∣≤5r/2, so the residual tends to zero and any positive tolerance is eventually met if the update budget is large enough.

2.2givenstep 1.3F5F6F7F8algebra

For the double-root residual H(x)=(x−1)2 and any x>1, [F6] and [F7] give the Newton formula x+=x−(x−1)2/(2(x−1))=(x+1)/2, so e+:=x+−1=e/2 for e:=x−1>0. Iterating gives ek=2−ke0→0 by [F5]. Suppose a local quadratic bound held on some radius δ>0, so ∣e+∣≤C∣e∣2 for every 0<e<δ and some finite C≥0. Since e+=e/2, it would require 1/2≤Ce for every such e. If C>0, choose 0<e<min⁡{δ,1/(2C)}; if C=0, choose any 0<e<δ. Either choice contradicts the required inequality. Unlike the simple-root bound in step 1.3, H′(1)=0, so the simple-root hypothesis in [F8] fails.

3.1step 1.3F6F10algebra∎

For F(x)=x2−2, the start x0=0 lies outside the radius-r/2 ball of step 1.3 because r>0. At 0, F(0)=−2 and F′(0)=0, so [F6] returns the singular-jacobian status before any update, despite the two exact roots ±r.

Depends on

Used by

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Sources