@inbook{eb1be8a0301248eebac3b4aa7566c4cd,
title = "Quantum chemistry methods with multiwavelet bases on massive parallel computers",
abstract = "Multiresolution analysis (MRA) is a general-purpose numerical framework to solve integral and partial differential equations that has proven to be especially successful in applications in physics and chemistry. MRA allows construction of an orthonormal basis with dynamic adaptive resolution and systematic improvability, hence, providing guaranteed finite precision. Sparse representation of many kernels allows for efficient computation. Multiresolution Adaptive Numerical Environment for Scientific Simulation code uses MRA in a multiwavelet basis with low-rank separation of functions and operators for efficient computation in many dimensions. In this chapter, we describe some of the key elements of this approach, some of its applications in chemistry (including static and time-dependent problems) and examine some of its strengths and weaknesses.",
keywords = "DFT, HF, MADNESS, MP2, Multiresolution analysis, Numerical basis sets, Parallel computing, Parallel Eigensolver, Poisson equation, TBB, Wavelets",
author = "{\'A}lvaro V{\'a}zquez-Mayagoitia and Thornton, \{W. Scott\} and Hammond, \{Jeff R.\} and Harrison, \{Robert J.\}",
note = "Publisher Copyright: {\textcopyright} 2014 Elsevier B.V.",
year = "2014",
doi = "10.1016/B978-0-444-63378-1.00001-X",
language = "English",
series = "Annual Reports in Computational Chemistry",
publisher = "Elsevier Ltd.",
pages = "3--24",
booktitle = "Annual Reports in Computational Chemistry",
}