L
Leslie Greengard
Researcher at New York University
Publications - 217
Citations - 19581
Leslie Greengard is an academic researcher from New York University. The author has contributed to research in topics: Integral equation & Fast multipole method. The author has an hindex of 53, co-authored 205 publications receiving 17857 citations. Previous affiliations of Leslie Greengard include Yale University & National Institute of Standards and Technology.
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Integral equation methods for Stokes flow in doubly-periodic domains
TL;DR: In this paper, a fast integral-equation technique is presented for the calculation of Stokes flow in doubly-periodic domains, which is faster, more flexible, and easily incorporated into the fast multipole method.
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An Integral Evolution Formula for the Wave Equation
TL;DR: In this article, a time-symmetric evolution formula for the scalar wave equation is presented, which is related to the classical D'Alembert or spherical means representations but applies equally well in two space dimensions.
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Electrostatics and heat conduction in high contrast composite materials
Leslie Greengard,June-Yub Lee +1 more
TL;DR: In this paper, a robust integral equation method for the calculation of the electrostatic and thermal properties of systems made of piecewise homogeneous, high contrast materials is presented, which is related to the perturbation approach proposed by Tausch and White.
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On the Numerical Evaluation of Electrostatic Fields in Dense Random Dispersions of Cylinders
Hongwei Cheng,Leslie Greengard +1 more
TL;DR: A new integral equation method is presented for the solution of the interface problem which uses a recently developed method of images to resolve the close-to-touching interactions and the fast multipole method to compute far field interactions.
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A mathematical tool for exploring the dynamics of biological networks
Paolo Emilio Barbano,Marina Spivak,Marc Flajolet,Angus C. Nairn,Angus C. Nairn,Paul Greengard,Leslie Greengard +6 more
TL;DR: The results suggest that the entire topology of the network is needed to impart stability to one portion of thenetwork at the expense of the rest, which could have significant implications for systems biology, in that large, complex pathways may have properties that are not easily replicated with simple modules.