The black-box fast multipole method

By William Fong, Eric F Darve. Journal of Computational Physics, 2009

300 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/34360863d08ddf5546a27def78430b2addfcb8e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Lexing Ying
2. Victor Minden
3. Daniel Foreman-Mackey
4. David W. Hogg
5. Leslie Greengard
6. Peter K. Kitanidis
7. Sivaram Ambikasaran
8. Jonghyun Lee

In Electrical and Electronic Engineering

1. Lexing Ying
2. Victor Minden
3. David W. Hogg
4. Leslie Greengard
5. Peter K. Kitanidis
6. Jonghyun Lee
7. J. Brinkmann
8. Michael L. Minion

Citations in the corpus

• A Simple Solver for the Fractional Laplacian in Multiple Dimensions (2018, methodology): “We use Chebyshev polynomials for far-field compression in the vein of Fong and Darve [16], though we do not require the full FMM machinery as we are interested only in the lattice sum and not a full approximate operator.”
• Large‐scale hydraulic tomography and joint inversion of head and tracer data using the Principal Component Geostatistical Approach (PCGA) (2014, methodology): “…spaces of Q. Combined with fast matrix linear algebra methods such FFT [Nowak et al., 2003], the fast-multipole method [Greengard and Rokhlin, 1987; Fong and Darve, 2009] or hierachical matrices [Ambikasaran et al., 2013; Saibaba and Kitanidis, 2012], one can achieve a computational cost of OðmK…”
• Fast Direct Methods for Gaussian Processes (2014, methodology): “Taylor series approximations [41] and Monte Carlo methods have been suggested [9], as well as conjugate gradient-type methods combined with trace estimators [15].”