Quantum Scenery: um novo software de química quântica semiempírico para sistemas de memória distribuída

• Ano de defesa: 2019
• Autor(a) principal: Maia, Júlio Daniel de Carvalho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Informática; Programa de Pós-Graduação em Informática; UFPB
• Palavras-chave em Português: Modelagem molecular; Algoritmos distribuídos; Química quântica; Métodos semiempíricos; Molecular modeling; Distributed algorithms; Quantum chemistry; Semiempirical methods; Programa de Computador; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/15213

Efficient quantum molecular models are of highly importance when treating biomolecules and complex molecular systems. Programming efforts in optimizing less demanding computational models were lacking for a very long time. However, adopting less accurate quantum models for calculating properties is fundamental when modeling chemical and biological processes. This works focuses on introducing a new quantum chemistry software based on a distributed, SPMD paradigm for quantum properties, using the linear algebra library ScaLAPACK. Early results show that this introduced software is accurate when predicting the semiempirical total energy of molecular systems. A module for optimizing molecular geometries is also introduced based on gradients from the total energy. This module is capable of predicting energy minima geometries for smaller systems.