dc.creator Avila, Gustavo en_US dc.creator Carrington, Tucker, Jr. en_US dc.date.accessioned 2011-07-12T17:29:08Z dc.date.available 2011-07-12T17:29:08Z dc.date.issued 2011 en_US dc.identifier 2011-RI-08 en_US dc.identifier.uri http://hdl.handle.net/1811/49380 dc.description Author Institution: Chemistry Department, Queen's University, Kingston, Ontario K7L 3N6, Canada en_US dc.description.abstract Spectra are computed by solving the time-independent Schrodinger equation. If the number of atoms in a molecule is greater than about 4 the dimensionality of the Schrodinger equation makes solution very difficult. Standard discretization strategies for large dimensional systems $D\ge 9$ yield matrices and vectors that are too large for modern computers. This is the so-called "curse of dimensionality". Both the basis size and quadrature grid size are problems. Several ingenious schemes have been developed in the last decades to reduce the basis size. We have focused on reducing the size of the quadrature grid. The Smolyak algorithm allows one to create non-product quadrature grids with structure. Because of the structure they can be used with pruned product basis sets and the Lanczos algorithm to compute spectra. In this talk we shall explain the nature of these grids and why they are useful for computing spectra. en_US dc.language.iso en en_US dc.publisher Ohio State University en_US dc.title NON-PRODUCT SMOLYAK GRIDS FOR COMPUTING SPECTRA: HOW AND WHY? en_US dc.type Article en_US dc.type Image en_US dc.type Presentation en_US
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