Newton's method constructs a sequence of points that—with good luck—will converge to a solution of an equation or a vector solution of a system of equation . The Kantorovich theorem gives conditions on the initial point of this sequence. If those conditions are satisfied then a solution exists close to the initial point and the sequence converges to that point.
Let be an open subset and a differentiable function with a Jacobian that is locally Lipschitz continuous (for instance if it is twice differentiable). That is, it is assumed that for any open subset there exists a constant such that for any
holds. The norm on the left is some operator norm that is compatible with the vector norm on the right. This inequality can be rewritten to only use the vector norm. Then for any vector the inequality
Now choose any initial point . Assume that is invertible and construct the Newton step
The next assumption is that not only the next point but the entire ball is contained inside the set X. Let be the Lipschitz constant for the Jacobian over this ball.
As a last preparation, construct recursively, as long as it is possible, the sequences , , according to
Now if then
- a solution of exists inside the closed ball and
- the Newton iteration starting in converges to with at least linear order of convergence.
A statement that is more precise but slightly more difficult to prove uses the roots of the quadratic polynomial
and their ratio
- a solution exists inside the closed ball
- it is unique inside the bigger ball
- and the convergence to the solution of is dominated by the convergence of the Newton iteration of the quadratic polynomial towards its smallest root , if , then
- The quadratic convergence is obtained from the error estimate
- Ortega, J. M. (1968). "The Newton-Kantorovich Theorem". Amer. Math. Monthly 75 (6): 658–660. JSTOR 2313800.
- Gragg, W. B.; Tapia, R. A. (1974). "Optimal Error Bounds for the Newton-Kantorovich Theorem". SIAM Journal on Numerical Analysis 11 (1): 10–13. doi:10.1137/0711002. JSTOR 2156425.
- John H. Hubbard and Barbara Burke Hubbard: Vector Calculus, Linear Algebra, and Differential Forms: A Unified Approach, Matrix Editions, ISBN 978-0-9715766-3-6 (preview of 3. edition and sample material including Kant.-thm.)
- Kantorowitsch, L. (1948): Functional analysis and applied mathematics (russ.). UMN3, 6 (28), 89–185.
- Kantorowitsch, L. W.; Akilow, G. P. (1964): Functional analysis in normed spaces.
- P. Deuflhard: Newton Methods for Nonlinear Problems. Affine Invariance and Adaptive Algorithms., Springer, Berlin 2004, ISBN 3-540-21099-7 (Springer Series in Computational Mathematics, Vol. 35)