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      An O(N) and parallel approach to integral problems by a kernel-independent fast multipole method: Application to polarization and magnetization of interacting particles

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          Abstract

          Large classes of materials systems in physics and engineering are governed by magnetic and electrostatic interactions. Continuum or mesoscale descriptions of such systems can be cast in terms of integral equations, whose direct computational evaluation requires O(N^2) operations, where N is the number of unknowns. Such a scaling, which arises from the many-body nature of the relevant Green's function, has precluded wide-spread adoption of integral methods for solution of large-scale scientific and engineering problems. In this work, a parallel computational approach is presented that relies on using scalable open source libraries and utilizes a kernel-independent Fast Multipole Method to evaluate the integrals in O(N) operations, with O(N) memory cost, thereby substantially improving the scalability and efficiency of computational integral methods. We demonstrate the accuracy, efficiency, and scalability of our approach in the contest of two examples. In the first, we solve a boundary value problem for a ferroelectric/ferromagnetic volume in free space. In the second, we solve an electrostatic problem involving polarizable dielectric bodies in an unbounded dielectric medium. The results from these test cases show that our parallel approach, which is built on a kernel-independent FMM, can enable highly efficient and accurate simulations and allow for considerable flexibility in a broad range of applications.

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          A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs

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            Demagnetizing factors for rectangular ferromagnetic prisms

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              Hybrid method for computing demagnetizing fields

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                Author and article information

                Journal
                2016-05-05
                2016-07-25
                Article
                10.1063/1.4960436
                1605.01715
                f2ce16bb-9978-49e1-b54c-0a237d0a513e

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                J. Chem. Phys. 145, 064307 (2016)
                29 pages, 8 figures
                physics.comp-ph cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.soft

                Condensed matter,Mathematical & Computational physics,Nanophysics
                Condensed matter, Mathematical & Computational physics, Nanophysics

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