Hybrid Quantum-Classical Algorithms

Abstract

Hybrid algorithms combine classical and quantum computing to create a whole that improves the performance of classical algorithms. There are many ways to understand this combination, in this thesis two are studied. First, it is an approach that combines classical and quantum modules communicating with each other to create a search & sample optimization algorithm. The second one is a classical algorithm that studies thecost and performance of quantum algorithms applied to chemistry. Hybrid algorithms are interesting due to the limitations of both classical and quantum computing. Some hard problems solved by classical computing are limited in performance and scalability because due to the exponentially growing number of states to be evaluated. On the other hand, currently, quantum computing is limited because quantum hardware is not yet developed enough to execute algorithms that process large amounts of data. By combining both technologies, it is possible to obtain an algorithm capable of processing large volumes of data with greater speed...

La situación actual de Computación Cuántica no difiere mucho de la de un gigante con pies de barro. Sin que se haya podido demostrar una ventaja cuántica en un problema real, ya se ha desarrollado una fuerte inversión tanto a nivel industrial como académico para diseñar algoritmos cuánticos. Este gigante, formado por, algoritmos puramente teóricos, promesas de ventajas exponenciales e infinitud de aplicaciones, se asienta sobre un terreno inestable en el que sólo existen dispositivos cuánticos de pequeño tamaño incapaces de sostener al gigante y embarrado por la alta capacidad de procesamiento de la computación clásica. Esta tesis trata de combinar barro y gigante para fortalecer la base de la estructura, amén de sacrificar cierta altura del coloso...