Kantorovich theorem

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The Kantorovich theorem, or Newton–Kantorovich theorem, is a mathematical statement on the semi-local convergence of Newton's method. It was first stated by Leonid Kantorovich in 1948.[1][2] It is similar to the form of the Banach fixed-point theorem, although it states existence and uniqueness of a zero rather than a fixed point.[3]

Newton's method constructs a sequence of points that under certain conditions 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.[1][2]


Let be an open subset and a differentiable function with a Jacobian that is locally Lipschitz continuous (for instance if is twice differentiable). That is, it is assumed that for any there is an open subset such that and there exists a constant such that for any

holds. The norm on the left is the operator norm. In other words, for any vector the inequality

must hold.

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 . Let be the Lipschitz constant for the Jacobian over this ball (assuming it exists).

As a last preparation, construct recursively, as long as it is possible, the sequences , , according to


Now if then

  1. a solution of exists inside the closed ball and
  2. 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


  1. a solution exists inside the closed ball
  2. it is unique inside the bigger ball
  3. and the convergence to the solution of is dominated by the convergence of the Newton iteration of the quadratic polynomial towards its smallest root ,[4] if , then
  4. The quadratic convergence is obtained from the error estimate[5]


In 1986, Yamamoto proved that the error evaluations of the Newton method such as Doring (1969), Ostrowski (1971, 1973),[6][7] Gragg-Tapia (1974), Potra-Ptak (1980),[8] Miel (1981),[9] Potra (1984),[10] can be derived from the Kantorovich theorem.[11]


There is a q-analog for the Kantorovich theorem.[12][13] For other generalizations/variations, see Ortega & Rheinboldt (1970).[14]


Oishi and Tanabe claimed that the Kantorovich theorem can be applied to obtain reliable solutions of linear programming.[15]


  1. ^ a b Deuflhard, P. (2004). Newton Methods for Nonlinear Problems. Affine Invariance and Adaptive Algorithms. Springer Series in Computational Mathematics. Vol. 35. Berlin: Springer. ISBN 3-540-21099-7.
  2. ^ a b Zeidler, E. (1985). Nonlinear Functional Analysis and its Applications: Part 1: Fixed-Point Theorems. New York: Springer. ISBN 0-387-96499-1.
  3. ^ Dennis, John E.; Schnabel, Robert B. (1983). "The Kantorovich and Contractive Mapping Theorems". Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Englewood Cliffs: Prentice-Hall. pp. 92–94. ISBN 0-13-627216-9.
  4. ^ Ortega, J. M. (1968). "The Newton-Kantorovich Theorem". Amer. Math. Monthly. 75 (6): 658–660. doi:10.2307/2313800. JSTOR 2313800.
  5. ^ Gragg, W. B.; Tapia, R. A. (1974). "Optimal Error Bounds for the Newton-Kantorovich Theorem". SIAM Journal on Numerical Analysis. 11 (1): 10–13. Bibcode:1974SJNA...11...10G. doi:10.1137/0711002. JSTOR 2156425.
  6. ^ Ostrowski, A. M. (1971). "La method de Newton dans les espaces de Banach". C. R. Acad. Sci. Paris. 27 (A): 1251–1253.
  7. ^ Ostrowski, A. M. (1973). Solution of Equations in Euclidean and Banach Spaces. New York: Academic Press. ISBN 0-12-530260-6.
  8. ^ Potra, F. A.; Ptak, V. (1980). "Sharp error bounds for Newton's process". Numer. Math. 34: 63–72. doi:10.1007/BF01463998.
  9. ^ Miel, G. J. (1981). "An updated version of the Kantorovich theorem for Newton's method". Computing. 27 (3): 237–244. doi:10.1007/BF02237981.
  10. ^ Potra, F. A. (1984). "On the a posteriori error estimates for Newton's method". Beiträge zur Numerische Mathematik. 12: 125–138.
  11. ^ Yamamoto, T. (1986). "A method for finding sharp error bounds for Newton's method under the Kantorovich assumptions". Numerische Mathematik. 49 (2–3): 203–220. doi:10.1007/BF01389624.
  12. ^ Rajkovic, P. M.; Stankovic, M. S.; Marinkovic, S. D. (2003). "On q-iterative methods for solving equations and systems". Novi Sad J. Math. 33 (2): 127–137.
  13. ^ Rajković, P. M.; Marinković, S. D.; Stanković, M. S. (2005). "On q-Newton–Kantorovich method for solving systems of equations". Applied Mathematics and Computation. 168 (2): 1432–1448. doi:10.1016/j.amc.2004.10.035.
  14. ^ Ortega, J. M.; Rheinboldt, W. C. (1970). Iterative Solution of Nonlinear Equations in Several Variables. SIAM. OCLC 95021.
  15. ^ Oishi, S.; Tanabe, K. (2009). "Numerical Inclusion of Optimum Point for Linear Programming". JSIAM Letters. 1: 5–8. doi:10.14495/jsiaml.1.5.

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