A Concise Introduction to Geometric Numerical Integration by Sergio Blanes, Fernando Casas

By Sergio Blanes, Fernando Casas

Discover How Geometric Integrators guard the most Qualitative houses of constant Dynamical Systems

A Concise creation to Geometric Numerical Integration offers the most issues, ideas, and purposes of geometric integrators for researchers in arithmetic, physics, astronomy, and chemistry who're already accustomed to numerical instruments for fixing differential equations. It additionally bargains a bridge from conventional education within the numerical research of differential equations to realizing fresh, complicated examine literature on numerical geometric integration.

The ebook first examines high-order classical integration tools from the constitution renovation standpoint. It then illustrates the right way to build high-order integrators through the composition of easy low-order tools and analyzes the belief of splitting. It subsequent stories symplectic integrators built without delay from the idea of producing capabilities in addition to the real type of variational integrators. The authors additionally clarify the connection among the protection of the geometric houses of a numerical procedure and the saw favorable errors propagation in long-time integration. The booklet concludes with an research of the applicability of splitting and composition the right way to sure periods of partial differential equations, reminiscent of the Schrödinger equation and different evolution equations.

The motivation of geometric numerical integration isn't just to advance numerical equipment with more desirable qualitative habit but in addition to supply extra exact long-time integration effects than these bought by means of general-purpose algorithms. obtainable to researchers and post-graduate scholars from different backgrounds, this introductory ebook will get readers on top of things at the principles, tools, and purposes of this box. Readers can reproduce the figures and effects given within the textual content utilizing the MATLAB® courses and version documents on hand online.

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Extra info for A Concise Introduction to Geometric Numerical Integration (Chapman & Hall/CRC Monographs and Research Notes in Mathematics)

Sample text

It is worth remarking that the trapezoidal rule behaves with respect to the error as a symplectic method, since it is conjugate to symplectic. 7 we show the results obtained (in double logarithmic scale) when e = 0, in other words, when a circular trajectory is considered. Now the error in energy drops to round off for the trapezoidal method,2 whereas the error in phase space is only slightly smaller than that corresponding to the St¨ ormer–Verlet method S2 . 62) is only slightly smaller than that of S2 , the error in phase space behaves much better.

In general, the energy H(q, p) is not conserved by the scheme, although the energy error is of order O(h2 ) over exponentially large time intervals. As a matter of fact, no integration method can preserve energy and symplecticity in general, as established by the classical theorem of Ge and Marsden [109]. More specifically, assume ψt is the numerical flow corresponding to a symplectic integrator preserving the energy for the autonomous Hamiltonian H, and that ϕt H=c denotes the exact flow restricted to the surface H = c.

2 Efficiency plots When accurate results are desired, high order methods are usually preferable to low order schemes. The former are in general more costly per time step, but this extra cost can be compensated if larger steps can be used. Generally speaking, one can say that the most efficient scheme is the one providing a prescribed accuracy with the lowest computational effort. Since the computational cost may depend on the implementation, the particular compiler used and the architecture of the computer, it is customary to estimate this cost by counting how many times the most costly part of the 2 The error corresponds, in fact, to the truncation error due to the value of the tolerance used to solve the implicit equations.

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