2,498 research outputs found

    Parallel algorithm with spectral convergence for nonlinear integro-differential equations

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    We discuss a numerical algorithm for solving nonlinear integro-differential equations, and illustrate our findings for the particular case of Volterra type equations. The algorithm combines a perturbation approach meant to render a linearized version of the problem and a spectral method where unknown functions are expanded in terms of Chebyshev polynomials (El-gendi's method). This approach is shown to be suitable for the calculation of two-point Green functions required in next to leading order studies of time-dependent quantum field theory.Comment: 15 pages, 9 figure

    An approximation method for the solution of nonlinear integral equations

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    A Chebyshev collocation method has been presented to solve nonlinear integral equations in terms of Chebyshev polynomials. This method transforms the integral equation to a matrix equation which corresponds to a system of nonlinear algebraic equations with unknown Chebyshev coefficients. Finally, some examples are presented to illustrate the method and results discussed. (c) 2005 Elsevier Inc. All rights reserved

    Volterra integral equations and fractional calculus: Do neighbouring solutions intersect?

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    This is the author's PDF version of an article published in Journal of integral equations and applications. The definitive version is available at rmmc.asu.edu/jie/jie.html.This journal article considers the question of whether or not the solutions to two Volterra integral equations which have the same kernel but different forcing terms may intersect at some future time

    High Order Methods for a Class of Volterra Integral Equations with Weakly Singular Kernels

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    The solution of the Volterra integral equation, (āˆ—)x(t)=g1(t)+tg2(t)+āˆ«0tK(t,s,x(s))tāˆ’sds,0ā‰¦tā‰¦T, ( * )\qquad x(t) = g_1 (t) + \sqrt {t}g_2 (t) + \int _0^t \frac {K(t,s,x(s))} {\sqrt {t - s} } ds, \quad 0 \leqq t \leqq T, where g1(t)g_1 (t), g2(t)g_2 (t) and K(t,s,x)K(t,s,x) are smooth functions, can be represented as x(t)=u(t)+tv(t)x(t) = u(t) + \sqrt {t}v(t) ,0ā‰¦tā‰¦T0 \leqq t \leqq T, where u(t)u(t), v(t)v(t) are, smooth and satisfy a system of Volterra integral equations. In this paper, numerical schemes for the solution of (*) are suggested which calculate x(t)x(t) via u(t)u(t), v(t)v(t) in a neighborhood of the origin and use (*) on the rest of the interval 0ā‰¦tā‰¦T0 \leqq t \leqq T. In this way, methods of arbitrarily high order can be derived. As an example, schemes based on the product integration analogue of Simpson's rule are treated in detail. The schemes are shown to be convergent of order h7/2h^{{7 / 2}} . Asymptotic error estimates are derived in order to examine the numerical stability of the methods

    On approximate solutions of semilinear evolution equations

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    A general framework is presented to discuss the approximate solutions of an evolution equation in a Banach space, with a linear part generating a semigroup and a sufficiently smooth nonlinear part. A theorem is presented, allowing to infer from an approximate solution the existence of an exact solution. According to this theorem, the interval of existence of the exact solution and the distance of the latter from the approximate solution can be evaluated solving a one-dimensional "control" integral equation, where the unknown gives a bound on the previous distance as a function of time. For example, the control equation can be applied to the approximation methods based on the reduction of the evolution equation to finite-dimensional manifolds: among them, the Galerkin method is discussed in detail. To illustrate this framework, the nonlinear heat equation is considered. In this case the control equation is used to evaluate the error of the Galerkin approximation; depending on the initial datum, this approach either grants global existence of the solution or gives fairly accurate bounds on the blow up time.Comment: 33 pages, 10 figures. To appear in Rev. Math. Phys. (Shortened version; the proof of Prop. 3.4. has been simplified
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