An isometric representation problem in quantum multimolecular polyhedra and similarity: (2) synisometry

 

Authors
Carb?-Dorca Carr?, Ram?n
Format
Article
Status
publishedVersion
Description

Collective distances in quantum multimolecular polyhedra (QMP), which can be set as a scalar indices associated to the QMP variance vector, enhance the role of the pair density similarity matrix. This paper describes a simplified efficient algorithm to compute triple, quadruple or higher order density similarity hypermatrices via an approximate isometry: a synisometric decomposition of the pair similarity matrix. Synisometries pretend to avoid the use of Minkowski metrics in QMP description problems, where the double density similarity matrix possesses negative eigenvalues. The synisometric decomposition of the similarity matrix opens the way to the general use of higher order approximate similarity elements in quantum QSAR and in the construction of scalar condensed vector statistical-like indices, for instance skewness and kurtosis. This might lead the way to describe, without excessive complication and within a real field computational framework, the collective structure of quantum multimolecular polyhedra.
http://link.springer.com/article/10.1007%2Fs10910-015-0525-3

Publication Year
2015
Language
eng
Topic
QUANTUM MOLECULAR SIMILARITY
QUANTUM MULTIMOLECULAR POLYHEDRA
QUANTUM OBJECT SETS
DENSITY FUNCTIONS DISCRETE ISOMETRIC AND SYNISOMETRIC REPRESENTATION
COLLECTIVE DISTANCES
COLLECTIVE SIMILARITY INDICES
Repository
Repositorio SENESCYT
Get full text
http://repositorio.educacionsuperior.gob.ec/handle/28000/4033
Rights
openAccess
License
closedAccess