High-performance simulation of interacting multiparticle quantum walks with Apache Spark

• Ano de defesa: 2018
• Autor(a) principal: Albuquerque, André Luiz Figueiredo de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Engenharia de Sistemas e Computação; UFRJ
• Palavras-chave em Português: quantum walk; simulation; high performance computing; map-reduce; apache spark; CNPQ::ENGENHARIAS
• Link de acesso: http://hdl.handle.net/11422/13167

Although many quantum algorithms have been developed in the last few decades with considerable speedup when compared to their best classical counterparts, the task of building a general purpose quantum computer is still a technological challenge. While the hardware necessary to run quantum algorithms is not available, researchers rely on classical simulations. However, the most interesting simulations are very demanding of computational resources due to the amount of data growing exponentially with the instance sizes and, thus, high performance computing techniques are necessary. Multiparticle quantum walks have been receiving a great deal of attention recently as a tool for designing quantum algorithms and for modeling physical phenomena. In the present work, we show that Apache Spark, a framework for large-scale data processing, can be used to simulate quantum walks with multiple interacting particles, with instance sizes that are impractical on single-processor, general-purpose computers. We also provide a prototype for quantum walks simulations, suitable to computer clusters, being developed atop of Spark.