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An inexact Newton residual gives a local error recurrence
Statement
For , call a linear map invertible when it has a two-sided linear inverse, extending the positive-dimensional convention of Invertible Euclidean linear maps. Let be an integer, let be open, be , and satisfy with invertible. Suppose a closed Euclidean ball with is convex and
where and for ; for set the norm of the unique linear map to . Let and fix . There are constants , , and such that, whenever , , and satisfy
then is invertible, , and
Facts & Assumptions
Given: as in the Statement.
Continuously differentiable maps, local inverses, and local diffeomorphisms: means total differentiability at every point and continuity of the derivative-matrix entries.
The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case: the Jacobian matrix records the first partial derivatives in the standard coordinates.
Newton maps are uniform contractions near a point with invertible derivative: if is invertible for a map, then on a sufficiently small closed ball every is invertible and its inverse has a uniform operator-norm bound.
Vector Newton remainder under a Lipschitz Jacobian: for , , and -Lipschitz on , .
Invertible Euclidean linear maps: for , an invertible square linear map has a two-sided linear inverse; the Statement explicitly extends this convention to .
The Euclidean inner product on : is the Euclidean norm.
Proof
Given: The hypotheses and notation in the Statement.
If , the space is a singleton by [F6]. Its unique map is linear and satisfies , so taking verifies both inverse identities in the Statement's convention. Thus is invertible, and in this space. Take , , and . Every claimed estimate is , so the assertion holds. For the remainder assume , so the imported positive-dimensional Newton lemmas and operator-norm comparisons apply.
Put . The inverse identity gives , and the operator-norm definition gives . By [F3], choose a smaller radius and such that every on is invertible and . Decrease if necessary so , and set .
Let . By [F4] and , . Since and , this gives .
The linear residual equation and steps 1.2–2.1 imply .
Put . From , . Step 1.2 and [F4] give , so . Also and step 3.1 bounds . The triangle inequality and yield . Set equal to this nonnegative coefficient; this is the claimed recurrence, and step 1.2 supplies invertibility.
Depends on
- Vector Newton remainder under a Lipschitz Jacobian
- Newton maps are uniform contractions near a point with invertible derivative
- Continuously differentiable maps, local inverses, and local diffeomorphisms
- The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Invertible Euclidean linear maps
Used by
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Sources
- Ron S. Dembo, Stanley C. Eisenstat, and Trond Steihaug, Inexact Newton Methods, SIAM Journal on Numerical Analysis 19 (1982), 400–408 (standard reference, not scraped)
- Jorge Nocedal and Stephen J. Wright, Numerical Optimization, 2nd ed. (standard reference, not scraped)