A short survey on Kantorovich-like theorems for Newton's method

We survey influential quantitative results on the convergence of the Newton iterator towards simple roots of continuously differentiable maps defined over Banach spaces. We present a general statement of Kantorovich's theorem, with a concise proof from scratch, dedicated to wide audience. From it, we quickly recover known results, and gather historical notes together with pointers to recent articles

Semilocal convergence of a k-step iterative process and its application for solving a special kind of conservative problems

[EN] In this paper, we analyze the semilocal convergence of k-steps Newton's method with frozen first derivative in Banach spaces. The method reaches order of convergence k + 1. By imposing only the assumption that the Fr,chet derivative satisfies the Lipschitz continuity, we define appropriate recurrence relations for obtaining the domains of convergence and uniqueness. We also define the accessibility regions for this iterative process in order to guarantee the semilocal convergence and perform a complete study of their efficiency. Our final aim is to apply these theoretical results to solve a special kind of conservative systems.Hernández-Verón, MA.; Martínez Molada, E.; Teruel-Ferragud, C. (2017). Semilocal convergence of a k-step iterative process and its application for solving a special kind of conservative problems. Numerical Algorithms. 76(2):309-331. https://doi.org/10.1007/s11075-016-0255-zS309331762Amat, S., Busquier, S., Bermúdez, C., Plaza, S.: On two families of high order Newton type methods. Appl. Math. Comput. 25, 2209–2217 (2012)Argyros, I.K., Hilout, S., Tabatabai, M.A.: Mathematical Modelling with Applications in Biosciences and Engineering. Nova Publishers, New York (2011)Argyros, I.K., George, S.: A unified local convergence for Jarratt-type methods in Banach space under weak conditions. Thai. J. Math. 13, 165–176 (2015)Argyros, I.K., Hilout, S.: On the local convergence of fast two-step Newton-like methods for solving nonlinear equations. J. Comput. Appl. Math. 245, 1–9 (2013)Argyros, I.K., Ezquerro, J.A., Gutiérrez, J.M., Hernández, M.A., Hilout, S.: On the semilocal convergence of efficient Chebyshev–Secant-type methods. J. Comput. Appl. Math. 235, 3195–2206 (2011)Cordero, A., Hueso, J.L., Martínez, E., Torregrosa, J.R.: Generating optimal derivative free iterative methods for nonlinear equations by using polynomial interpolation. Math. Comput. Mod. 57, 1950–1956 (2013)Ezquerro, J.A., Grau-Sánchez, M., Hernández, M. A., Noguera, M.: Semilocal convergence of secant-like methods for differentiable and nondifferentiable operators equations. J. Math. Anal. Appl. 398(1), 100–112 (2013)Honorato, G., Plaza, S., Romero, N.: Dynamics of a higher-order family of iterative methods. J. Complexity 27(2), 221–229 (2011)Jerome, J.W., Varga, R.S.: Generalizations of Spline Functions and Applications to Nonlinear Boundary Value and Eigenvalue Problems, Theory and Applications of Spline Functions. Academic Press, New York (1969)Kantorovich, L.V., Akilov, G.P.: Functional analysis Pergamon Press. Oxford (1982)Keller, H.B.: Numerical Methods for Two-Point Boundary-Value Problems. Dover Publications, New York (1992)Na, T.Y.: Computational Methods in Engineering Boundary Value Problems. Academic Press, New York (1979)Ortega, J.M.: The Newton-Kantorovich theorem. Amer. Math. Monthly 75, 658–660 (1968)Ostrowski, A.M.: Solutions of Equations in Euclidean and Banach Spaces. Academic Press, New York (1973)Plaza, S., Romero, N.: Attracting cycles for the relaxed Newton’s method. J. Comput. Appl. Math. 235(10), 3238–3244 (2011)Porter, D., Stirling, D.: Integral Equations: A Practical Treatment, From Spectral Theory to Applications. Cambridge University Press, Cambridge (1990)Traub, J.F.: Iterative Methods for the Solution of Equations. Prentice-Hall. Englewood Cliffs, New Jersey (1964)Argyros, I.K., George, S.: Extending the applicability of Gauss-Newton method for convex composite optimization on Riemannian manifolds using restricted convergence domains. Journal of Nonlinear Functional Analysis 2016 (2016). Article ID 27Xiao, J.Z., Sun, J., Huang, X.: Approximating common fixed points of asymptotically quasi-nonexpansive mappings by a k+1-step iterative scheme with error terms. J. Comput. Appl. Math 233, 2062–2070 (2010)Qin, X., Dehaish, B.A.B., Cho, S.Y.: Viscosity splitting methods for variational inclusion and fixed point problems in Hilbert spaces. J. Nonlinear Sci. Appl. 9, 2789–2797 (2016

Estudio sobre convergencia y dinámica de los métodos de Newton, Stirling y alto orden

Las matemáticas, desde el origen de esta ciencia, han estado al servicio de la sociedad tratando de dar respuesta a los problemas que surgían. Hoy en día sigue siendo así, el desarrollo de las matemáticas está ligado a la demanda de otras ciencias que necesitan dar solución a situaciones concretas y reales. La mayoría de los problemas de ciencia e ingeniería no pueden resolverse usando ecuaciones lineales, es por tanto que hay que recurrir a las ecuaciones no lineales para modelizar dichos problemas (Amat, 2008; véase también Argyros y Magreñán, 2017, 2018), entre otros. El conflicto que presentan las ecuaciones no lineales es que solo en unos pocos casos es posible encontrar una solución única, por tanto, en la mayor parte de los casos, para resolverlas hay que recurrir a los métodos iterativos. Los métodos iterativos generan, a partir de un punto inicial, una sucesión que puede converger o no a la solución

Métodos iterativos para la resolución de problemas aplicados transformados a sistemas no lineales

[ES] La resolución de ecuaciones y sistemas no lineales es un tema de gran interés teórico-práctico, pues muchos modelos matemáticos de la ciencia o de la industria se expresan mediante sistemas no lineales o ecuaciones diferenciales o integrales que, mediante técnicas de discretización, dan lugar a dichos sistemas. Dado que generalmente es difícil, si no imposible, resolver analíticamente las ecuaciones no lineales, la herramienta más extendida son los métodos iterativos, que tratan de obtener aproximaciones cada vez más precisas de las soluciones partiendo de determinadas estimaciones iniciales. Existe una variada literatura sobre los métodos iterativos para resolver ecuaciones y sistemas, que abarca conceptos como, eficiencia, optimalidad, estabilidad, entre otros importantes temas. En este estudio obtenemos nuevos métodos iterativos que mejoran algunos conocidos en términos de orden o eficiencia, es decir que obtienen mejores aproximaciones con menor coste computacional. La convergencia de los métodos iterativos suele estudiarse desde el punto de vista local. Esto significa que se obtienen resultados de convergencia imponiendo condiciones a la ecuación en un entorno de la solución. Obviamente, estos resultados no son aplicables si no la conocemos. Otro punto de vista, que abordamos en este trabajo, es el estudio semilocal que, imponiendo condiciones en un entorno de la estimación inicial, proporciona un entorno de dicho punto que contiene la solución y garantiza la convergencia del método iterativo a la misma. Finalmente, desde un punto de vista global, estudiamos el comportamiento de los métodos iterativos en función de la estimación inicial, mediante el estudio de la dinámica de las funciones racionales asociadas a estos métodos. La presente memoria recoge los resultados de varios artículos de nuestra autoría, en los que se tratan distintos aspectos de la materia, como son, las peculiaridades de la convergencia en el caso de raíces múltiples, la posibilidad de aumentar el orden de un método óptimo de orden cuatro a orden ocho, manteniendo la optimalidad en el caso de raíces múltiples, el estudio de la convergencia semilocal en un método de alto orden, así como el comportamiento dinámico de algunos métodos iterativos.[CA] La resolució d'equacions i sistemes no lineals és un tema de gran interés teoricopràctic, perquè molts models matemàtics de la ciència o de la indústria s'expressen mitjançant sistemes no lineals o equacions diferencials o integrals que, mitjançant tècniques de discretizació, donen lloc a aquests sistemes. Atés que generalment és difícil, si no impossible, resoldre analíticament les equacions no lineals, l'eina més estesa són els mètodes iteratius, que tracten d'obtindre aproximacions cada vegada més precises de les solucions partint de determinades estimacions inicials. Existeix una variada literatura sobre els mètodes iteratius per a resoldre equacions i sistemes, que abasta conceptes com ordre d'aproximació, eficiència, optimalitat, estabilitat, entre altres importants temes. En aquest estudi obtenim nous mètodes iteratius que milloren alguns coneguts en termes d'ordre o eficiència, és a dir que obtenen millors aproximacions amb menor cost computacional. La convergència dels mètodes iteratius sol estudiar-se des del punt de vista local. Això significa que s'obtenen resultats de convergència imposant condicions a l'equació en un entorn de la solució. Òbviament, aquests resultats no són aplicables si no la coneixem. Un altre punt de vista, que abordem en aquest treball, és l'estudi semilocal que, imposant condicions en un entorn de l'estimació inicial, proporciona un entorn d'aquest punt que conté la solució i garanteix la convergència del mètode iteratiu a aquesta. Finalment, des d'un punt de vista global, estudiem el comportament dels mètodes iteratius en funció de l'estimació inicial, mitjançant l'estudi de la dinàmica de les funcions racionals associades a aquests mètodes. La present memòria recull els resultats de diversos articles de la nostra autoria, en els quals es tracten diferents aspectes de la matèria, com són, les peculiaritats de la convergència en el cas d'arrels múltiples, la possibilitat d'augmentar l'ordre d'un mètode òptim d'ordre quatre a ordre huit, mantenint l'optimalitat en el cas d'arrels múltiples, l'estudi de la convergència semilocal en un mètode d'alt ordre, així com el comportament dinàmic d'alguns mètodes iteratius.[EN] The resolution of nonlinear equations and systems is a subject of great theoretical and practical interest, since many mathematical models in science or industry are expressed through nonlinear systems or differential or integral equations that, by means of discretization techniques, give rise to such systems. Since it is generally difficult, if not impossible, to solve nonlinear equations analytically, the most widely used tool is iterative methods, which try to obtain increasingly precise approximations of the solutions based on certain initial estimates. There is a varied literature on iterative methods for solving equations and systems, which covers concepts of order of approximation, efficiency, optimality, stability, among other important topics. In this study we obtain new iterative methods that improve some known ones in terms of order or efficiency, that is, they obtain better approximations with lower computational cost. The convergence of iterative methods is usually studied locally. This means that convergence results are obtained by imposing conditions on the equation in a neighbourhood of the solution. Obviously, these results are not applicable if we do not know it. Another point of view, which we address in this work, is the semilocal study that, by imposing conditions in a neighbourhood of the initial estimation, provides an environment of this point that contains the solution and guarantees the convergence of the iterative method to it. Finally, from a global point of view, we study the behaviour of iterative methods as a function of the initial estimation, by studying the dynamics of the rational functions associated with these methods. This report collects the results of several articles of our authorship, in which different aspects of the matter are dealt with, such as the peculiarities of convergence in the case of multiple roots, the possibility of increasing the order of an optimal method from order four to order eight, maintaining optimality in the case of multiple roots, the study of semilocal convergence in a high-order method, as well as the dynamic behaviour of some iterative methods.Cevallos Alarcón, FA. (2023). Métodos iterativos para la resolución de problemas aplicados transformados a sistemas no lineales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19349

Atomistic and ab initio prediction and optimization of thermoelectric and photovoltaic properties

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 123-130).The accurate prediction of physical properties in the vast spaces of nanoscale structures and chemical compounds is made increasingly possible through the use of atomistic and ab initio computation. In this thesis we investigate lattice thermal conductivities KL and electronic band gaps E,, which are relevant to thermoelectric and photovoltaic applications, respectively, and develop or modify computational tools for predicting and optimizing these properties. For lattice thermal conductivity, we study SiGe nanostructures, which are technologically important for thermoelectric applications. From computing aL for various SiGe nanostructures, we establish that the Kubo-Green approach using classical molecular dynamics (MD) gives additional quantitative predictions not available from phenomenological models, such as the existences of a minimum value of KL as the nanostructure size is varied and of configurational dependence of KL. We carry out the minimizatin of KL in the space of atomic configurations in SiGe alloy nanowires and demonstrate the feasibility of using the cluster expansion technique to parameterize KL. We find that the use of coarse graining and a meta cluster expansion approach is effective, in conjunction with a genetic algorithm, to find configurations which drastically lower KL. The low values of KL obtained, close to the bulk amorphous limit, are due to the absence of long-range order, and such absence allows a local cluster expansion approach to optimize KL. We examine ab initio bandgap prediction for semiconductor compounds, and address the large errors of Kohn-Sham band gaps in density functional theory (DFT).(cont.) We apply corrections using the self-energy approach in the GW approximation, which includes non-local screened exchange and correlation, and find that the G₀W₀ approximation significantly reduces prediction errors compared to Kohn-Sham band gaps, though at much higher computational cost. We propose a new method involving total energies in DFT to predict the fundamental gap, by use of the properties of the screening or exchange-correlation hole in an electron gas. With this method, we are able to efficiently predict band gaps that are in agreement with experimental values.by Maria Kai Yee Chan.Ph.D

Ship steering control using feedforward neural networks

One significant problem in the design of ship steering control systems is that the dynamics of the vessel change with operating conditions such as the forward speed of the vessel, the depth of the water and loading conditions etc. Approaches considered in the past to overcome these difficulties include the use of self adaptive control systems which adjust the control characteristics on a continuous basis to suit the current operating conditions. Artificial neural networks have been receiving considerable attention in recent years and have been considered for a variety of applications where the characteristics of the controlled system change significantly with operating conditions or with time. Such networks have a configuration which remains fixed once the training phase is complete. The resulting controlled systems thus have more predictable characteristics than those which are found in many forms of traditional self-adaptive control systems. In particular, stability bounds can be investigated through simulation studies as with any other form of controller having fixed characteristics. Feedforward neural networks have enjoyed many successful applications in the field of systems and control. These networks include two major categories: multilayer perceptrons and radial basis function networks. In this thesis, we explore the applicability of both of these artificial neural network architectures for automatic steering of ships in a course changing mode of operation. The approach that has been adopted involves the training of a single artificial neural network to represent a series of conventional controllers for different operating conditions. The resulting network thus captures, in a nonlinear fashion, the essential characteristics of all of the conventional controllers. Most of the artificial neural network controllers developed in this thesis are trained with the data generated through simulation studies. However, experience is also gained of developing a neuro controller on the basis of real data gathered from an actual scale model of a supply ship. Another important aspect of this work is the applicability of local model networks for modelling the dynamics of a ship. Local model networks can be regarded as a generalized form of radial basis function networks and have already proved their worth in a number of applications involving the modelling of systems in which the dynamic characteristics can vary significantly with the system operating conditions. The work presented in this thesis indicates that these networks are highly suitable for modelling the dynamics of a ship

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Time-dependent density-functional description of nuclear dynamics

The basic concepts and recent developments in the time-dependent density-functional theory (TDDFT) for describing nuclear dynamics at low energy are presented. The symmetry breaking is inherent in nuclear energy density functionals, which provides a practical description of important correlations at the ground state. Properties of elementary modes of excitation are strongly influenced by the symmetry breaking and can be studied with TDDFT. In particular, a number of recent developments in the linear response calculation have demonstrated their usefulness in the description of collective modes of excitation in nuclei. Unrestricted real-time calculations have also become available in recent years, with new developments for quantitative description of nuclear collision phenomena. There are, however, limitations in the real-time approach; for instance, it cannot describe the many-body quantum tunneling. Thus, the quantum fluctuations associated with slow collective motions are explicitly treated assuming that time evolution of densities is determined by a few collective coordinates and momenta. The concept of collective submanifold is introduced in the phase space associated with the TDDFT and used to quantize the collective dynamics. Selected applications are presented to demonstrate the usefulness and quality of the new approaches. Finally, conceptual differences between nuclear and electronic TDDFT are discussed, with some recent applications to studies of electron dynamics in the linear response and under a strong laser fie

Extending the applicability of the local and semilocal convergence of Newton's method

We present a local as well a semilocal convergence analysis for Newton's method in a Banach space setting. Using the same Lipschitz constants as in earlier studies, we extend the applicability of Newton's method as follows: local case: a larger radius is given as well as more precise error estimates on the distances involved. Semilocal case: the convergence domain is extended; the error estimates are tighter and the information on the location of the solution is at least as precise as before. Numerical examples further justify the theoretical results