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MADNESS applied to density functional theory in chemistry and nuclear physics

G I Fann1, R J Harrison2, G Beylkin3, J Jia1, R Hartman-Baker1, W A Shelton4 and S Sugiki4

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We describe some recent mathematical results in constructing computational methods that lead to the development of fast and accurate multiresolution numerical methods for solving quantum chemistry and nuclear physics problems based on Density Functional Theory (DFT). Using low separation rank representations of functions and operators in conjunction with representations in multiwavelet bases, we developed a multiscale solution method for integral and differential equations and integral transforms. The Poisson equation, the Schrodinger equation, and the projector on the divergence free functions provide important examples with a wide range of applications in computational chemistry, nuclear physics, computational electromagnetic and fluid dynamics.

We have implemented this approach along with adaptive representations of operators and functions in the multiwavelet basis and low separation rank (LSR) approximation of operators and functions. These methods have been realized and implemented in a software package called Multiresolution Adaptive Numerical Evaluation for Scientific Simulation (MADNESS).


PACS

82.20.-w Chemical kinetics and dynamics

02.60.Nm Integral and integrodifferential equations

03.65.Ge Solutions of wave equations: bound states

21.60.Jz Nuclear Density Functional Theory and extensions (includes Hartree–Fock and random-phase approximations)

07.05.Bx Computer systems: hardware, operating systems, computer languages, and utilities

Subjects

Computational physics

Instrumentation and measurement

Nuclear physics

Quantum information and quantum mechanics

Chemical physics and physical chemistry

Dates

Issue 1 (2007)



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