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The fast multipole method (FMM) is a numerical technique that was developed to speed up the calculation of long-ranged forces in the n-body problem.It does this by expanding the system Green's function using a multipole expansion, which allows one to group sources that lie close together and treat them as if they are a single source.
This formulation is naturally combined with fast multipole method (FMM) acceleration, and the entire method is known as charge-based BEM-FMM. The combination of BEM and FMM is a common technique in different areas of computational electromagnetics and, in the context of bioelectromagnetism, it provides improvements over the finite element method .
Vladimir Rokhlin Jr. (born August 4, 1952) is a mathematician [1] [2] and professor of computer science and mathematics at Yale University. [3] He is the co-inventor with Leslie Greengard of the fast multipole method (FMM) in 1985, recognised as one of the top-ten algorithms of the 20th century.
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FMM may refer to: Confederation of Malagasy Workers (Malagasy: Fivondronamben'ny Mpiasa Malagasy) Fast multipole method; Functional membrane microdomain; Father Michael McGivney Catholic Academy, in Markham, Ontario, Canada; Fellowship in Manufacturing Management, a program of Cranfield University, England
Rigorous coupled-wave analysis (RCWA), also known as Fourier modal method (FMM), [1] is a semi-analytical method in computational electromagnetics that is most typically applied to solve scattering from periodic dielectric structures. It is a Fourier-space method so devices and fields are represented as a sum of spatial harmonics.
The FMM is required for all visitors entering via air, regardless of length of stay, and the cost is included in the traveler's airfare and remitted by the airline. [303] Passport card or enhanced drivers license is valid for land and sea travel. [citation needed] Exit stamp required if you entered using paper FMM (All land POEs) [citation needed]
The fast multipole method (FMM) can reduce both CPU time and memory requirement from O(N 2) to O(N) or O(NlogN). With the help of FMM, the SBM can be fully capable of solving a large scale problem of several million unknowns on a desktop.